Results for “Personality” — Page 53

DOE OSTI2014

WE-E-BRE-03: Biological Validation of a Novel High-Throughput Irradiator for Predictive Radiation Sensitivity Bioassays

Purpose: The large dose-response variation in both tumor and normal cells between individual patients has led to the recent implementation of predictive bioassays of patient-specific radiation sensitivity in order to personalize radiation therapy. This exciting new clinical paradigm has led us to develop a novel high-throughput, variable dose-rate irradiator to accompany these efforts. Here we present the biological validation of this irradiator through the use of human cells as a relative dosimeter assessed by two metrics, DNA double-strand break repair pathway modulation and intercellular reactive oxygen species production. Methods: Immortalized human tonsilar epithelial cells were cultured in 96-well micro titer plates and irradiated in groups of eight wells to absorbed doses of 0, 0.5, 1, 2, 4, and 8 Gy. High-throughput immunofluorescent microscopy was used to detect γH2AX, a DNA double-strand break repair mechanism recruiter. The same analysis was performed with the cells stained with CM-H2DCFDA that produces a fluorescent adduct when exposed to reactive oxygen species during the irradiation cycle. Results: Irradiations of the immortalized human tonsilar epithelial cells at absorbed doses of 0, 0.5, 1, 2, 4, and 8 Gy produced excellent linearity in γH2AX and CM-H2DCFDA with R2 values of 0.9939 and 0.9595 respectively. Single cell gel electrophoresis experimentation for the detection of physical DNA double-strand breaks in ongoing. Conclusions: This work indicates significant potential for our high-throughput variable dose rate irradiator for patient-specific predictive radiation sensitivity bioassays. This irradiator provides a powerful tool by increasing the efficiency and number of assay techniques available to help personalize radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

SU-E-J-10: Imaging Dose and Cancer Risk in Image-Guided Radiotherapy of Cancers

Purpose: To systematically evaluate imaging doses and cancer risks to organs-at-risk as a Result of cumulative doses from various radiological imaging procedures in image-guided radiotherapy (IGRT) in a large cohort of cancer patients. Methods: With IRB approval, imaging procedures (computed tomography, kilo-voltage portal imaging, megavoltage portal imaging and kilo-voltage cone-beam computed tomography) of 4832 cancer patients treated during 4.5 years were collected with their gender, age and circumference. Correlations between patient’s circumference and Monte Carlo simulated-organ dose were applied to estimate organ doses while the cancer risks were reported as 1+ERR using BEIR VII models. Results: 80 cGy or more doses were deposited to brain, lungs and RBM in 273 patients (maximum 136, 278 and 267 cGy, respectively), due largely to repetitive imaging procedures and non-personalized imaging settings. Regardless of gender, relative cancer risk estimates for brain, lungs, and RBM were 3.4 (n = 55), 2.6 (n = 49), 1.8 (n = 25) for age group of 0–19; 1.2 (n = 87), 1.4 (n = 98), 1.3 (n = 51) for age group of 20–39; 1.0 (n = 457), 1.1 (n = 880), 1.8 (n=360) for age group of 40–59; 1.0 (n = 646), 1.1 (n = 1400), 2.3 (n = 716) for age group of 60–79 and 1.0 (n = 108),1.1 (n = 305),1.6 (n = 147) for age group of 80–99. Conclusion: The cumulative imaging doses and associated cancer risks from multi-imaging procedures were patient-specific and site-dependent, with up to 2.7 Gy imaging dose deposited to critical structures in some pediatric patients. The associated cancer risks in brain and lungs for children of age 0 to 19 were 2–3 times larger than those for adults. This study indicated a pressing need for personalized imaging protocol to maximize its clinical benefits while reducing associated cancer risks. Sichuan University Scholarship.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-213-01: Roentgen and the Birth of Modern Medical Physics

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-213-00: History Symposium: Radiological Physics Pioneers: Roentgen and the AAPM Award Eponyms - William Coolidge, Edith Quimby, and Marvin Williams - Who Were They and What Did They Do?

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

WE-G-213-02: The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who Were They and What Did They Do?

Roentgen and the Birth of Modern Medical Physics – Perry Sprawls Wilhelm Roentgen is well known for his discovery of x-radiation. What is less known and appreciated is his intensive research following the discovery to determine the characteristics of the “new kind of radiation” and demonstrate its great value for medical purposes. In this presentation we will imagine ourselves in Roentgen’s mind and follow his thinking, including questions and doubts, as he designs and conducts a series of innovative experiments that provided the foundation for the rapid growth of medical physics. Learning Objectives: Become familiar with the personal characteristics and work of Prof. Roentgen that establishes him as an inspiring model for the medical physics profession. Observe the thought process and experiments that determined and demonstrated the comprehensive characteristics of x-radiation. The AAPM Award Eponyms: William D. Coolidge, Edith H. Quimby, and Marvin M.D. Williams - Who were they and what did they do? – Lawrence N. Rothenberg William David Coolidge (1873–1975) William Coolidge was born in Hudson, NY in 1873. He obtained his BS at the Massacusetts Institute of Technology in 1896. Coolidge then went to the University of Leipzig, Germany for graduate study with physicists Paul Drude and Gustave Wiedemann and received a Ph.D. in 1899. While in Germany he met Wilhelm Roentgen. Coolidge returned to the US to teach at MIT where he was associated with Arthur A. Noyes of the Chemistry Department, working on the electrical conductivity of aqueous solutions. Willis R. Whitney, under whom Coolidge had worked before going to Germany, became head of the newly formed General Electric Research Laboratory and he invited Coolidge to work with him. In 1905, Coolidge joined the staff of the GE laboratory and was associated with it for the remainder of his life. He developed ductile tungsten filaments to replace fragile carbon filaments as the material for electric light bulb filaments. Until that innovation light bulbs had a notoriously short life. He later incorporated the ductile tungsten as a filament material for a hot cathode, fully evacuated x-ray tube, first described in 1912, which allowed higher current and x-ray output, and greater reliability than had previously been possible. These “Coolidge x-ray tubes” were far superior to the cold cathode, partial pressure gas x-ray tubes that had been in use since Roentgen’s discovery of x-rays in 1895. The Coolidge tube with incremental developments is now the key component for x-ray production in all of our modern x-ray imaging devices, such as CT scanners, interventional radiology systems, and mammography units. Coolidge was also involved in the development of sectional x-ray tubes for research and treatment that were initially designed to reach 800 kV. Additional improvements led to 1 MV and 2 MV devices. In 1932 Coolidge became director of the General Electric Research Laboratory, and in 1940, was made Vice-President and Director of Research. In 1945 he retired and was named Director Emeritus of the laboratory. Coolidge held 83 patents and was recognized for these and many other achievements by election to the National Academy of Engineers, a place in the Engineering Hall of Fame and the National Inventor’s Hall of Fame. The AAPM’s highest honor, the Coolidge Award, was named after him. He accepted Honorary Membership in the AAPM and was the first recipient of the AAPM Coolidge Award, which was presented to him in a special ceremony in Schenectady, NY in 1972 when he was 100 years old. Edith Hinckley Quimby (1891–1982) Edith Quimby was born in Rockford, IL in 1891. She graduated from Whitman College in Walla Walla, WA with a B.S. in 1913, and then obtained a masters degree from the University of California at Berkeley. Later in her career, after many significant achievements, Quimby was awarded honorary doctorates by Whitman College and Rutgers University. Edith Quimby was hired by Giacchino Failla as a radiation physicist at Memorial Hospital for Cancer in New York City. Failla had studied with Madame Curie and obtained his doctoral degree in her laboratory. After many groundbreaking medical physics studies from 1919 until 1942, they both moved to Columbia University. Dr. Quimby developed a widely employed dosimetry system for single plane implants with radium and radon seeds, and a dosimetry methodology for internal radionuclides. She was author of more than 75 scientific publications, and of significant textbooks including the first comprehensive physics textbook for radiologists “Physical Foundations of Radiology”, which was co-authored with Otto Glasser, Lauriston Taylor and James Weatherwax in the first edition, with Russell Morgan added for the second edition and Paul Goodwin for the fourth edition. With Sergei Feitelberg, M.D. she published two editions of “Radioactive Isotopes in Medicine and Biology: Basic Physics and Instrumentation”. Quimby became a renowned examiner for the American Board of Radiology when the third ABR examination, given in 1936, added physics. She served as President of the American Radium Society, received the RSNA Gold Medal, and also numerous prestigious awards given to women in science. Edith Quimby was a Charter Member of AAPM. The AAPM Lifetime Achievement Award was renamed the Edith H. Quimby Lifetime Achievement Award in her honor in 2011. Marvin Martin Dixon Williams (1902–1981) Marvin Williams was born in Walla Walla, WA in 1902, and attended the same college as Edith Quimby, graduating from Whitman College in 1926. He was greatly influenced to go into medical physics by her accomplishments. During his early career, Williams worked with James Weatherwax in Philadelphia while he was working toward an M.S. from the University of Pennsylvania. In 1931 Williams was awarded a Ph.D. in Biophysics from the University of Minnesota, with the work actually performed at the Mayo Clinic Graduate School of the University. While completing his Ph.D. studies, Marvin met Dr. Paul Hodges who had returned from the Peiping Union Medical College in Peiping (now Beijing), China. Hodges suggested that a physicist be sent to Peiping to install x-ray therapy equipment and a radon plant. Williams accepted the position and, in 1931, he and his wife Orpha left for China. Before going to China, Williams had spent time with the physics group at Memorial Hospital to learn about the operation of a radon plant. In China, he constructed the radon plant, employing 0.25 g of radium, and also installed the x-ray therapy unit. Williams and his wife returned to the US in 1935, and he accepted a research position at the Mayo Clinic. In 1950, he became Professor of Biophysics at Mayo, where he taught physics and biophysics until his retirement in 1967. Williams was also very active in the American Board of Radiology where, from 1944 through 1977, he examined over 3000 radiologists and 250 physicists. Marvin Williams was a Charter member of AAPM, served as the fourth President of AAPM in 1963, and was the fourth recipient the AAPM Coolidge Award in 1975. The Marvin Williams Award was originally established as the highest award of the American College of Medical Physics. When various functions of the ACMP were absorbed into the AAPM in 2012, the Marvin M D Williams Professional Achievement Award became one of the AAPM’s highest honors. Learning Objectives: Become familiar with the persons in whose honor the three major AAPM Award are named Learn about the achievements and activities which influenced the AAPM to name these awards in their honor.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-P-20: Predicting Waiting Times in Radiation Oncology Using Machine Learning

Purpose: Waiting times remain one of the most vexing patient satisfaction challenges facing healthcare. Waiting time uncertainty can cause patients, who are already sick or in pain, to worry about when they will receive the care they need. These waiting periods are often difficult for staff to predict and only rough estimates are typically provided based on personal experience. This level of uncertainty leaves most patients unable to plan their calendar, making the waiting experience uncomfortable, even painful. In the present era of electronic health records (EHRs), waiting times need not be so uncertain. Extensive EHRs provide unprecedented amounts of data that can statistically cluster towards representative values when appropriate patient cohorts are selected. Predictive modelling, such as machine learning, is a powerful approach that benefits from large, potentially complex, datasets. The essence of machine learning is to predict future outcomes by learning from previous experience. The application of a machine learning algorithm to waiting time data has the potential to produce personalized waiting time predictions such that the uncertainty may be removed from the patient’s waiting experience. Methods: In radiation oncology, patients typically experience several types of waiting (eg waiting at home for treatment planning, waiting in the waiting room for oncologist appointments and daily waiting in the waiting room for radiotherapy treatments). A daily treatment wait time model is discussed in this report. To develop a prediction model using our large dataset (with more than 100k sample points) a variety of machine learning algorithms from the Python package sklearn were tested. Results: We found that the Random Forest Regressor model provides the best predictions for daily radiotherapy treatment waiting times. Using this model, we achieved a median residual (actual value minus predicted value) of 0.25 minutes and a standard deviation residual of 6.5 minutes. This means that the majority of our estimates are within 6.5 minutes of the actual wait time. Conclusion: The goal of this project was to define an appropriate machine learning algorithm to estimate waiting times based on the collective knowledge and experience learned from previous patients. Our results offer an opportunity to improve the information that is provided to patients and family members regarding the amount of time they can expect to wait for radiotherapy treatment at our centre. AJ acknowledges support by the CREATE Medical Physics Research Training Network grant of the Natural Sciences and Engineering Research Council (Grant number: 432290) and from the 2014 Q+ Initiative of the McGill University Health Centre.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-F-J-28: Development of a New Imaging Filter to Remove the Shadows From the Carbon Fiber Grid Table Top

Purpose: For the image guided radiation therapy (IGRT), the shadows caused by the construction of the treatment couch top adversely affect the visual evaluation. Therefore, we developed the new imaging filter in order to remove the shadows. The performance of the new filter was evaluated using the clinical images. Methods: The new filter was composed of the band-pass filter (BPF) weighted by the k factor and the low-pass filter (LPF). In the frequency region, the stop bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the BPF, and the pass bandwidth were 8.3×10{sup 3} mm{sup −1} on u direction and 11.1×10{sup 3} mm{sup −1} on v direction for the LPF. After adding the filter, the shadows from the carbon fiber grid table top (CFGTT, Varian) on the kV-image was removed. To check the filter effect, we compared the clinical images, which are thorax and thoracoabdominal region, with to without the filter. The subjective evaluation tests was performed by adapting a three-point scale (agree, neither agree nor disagree, disagree) about the 15 persons in the department of radiation oncology. Results: We succeeded in removing all shadows of CFGTT using the new filter. This filter is very useful shown by the results of the subjective evaluation having the 23/30 persons agreed to the filtered clinical images. Conclusion: We concluded that the proposed method was useful tool for the IGRT and the new filter leads to improvement of the accuracy of radiation therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

SU-G-IeP3-13: Real-Time Patient and Staff Dose Monitoring in Fluoroscopy Guided Interventions

Purpose: Interventional radiology procedures involve the use of X-rays, which can pose a large radiation burden on both patients and staff. Although some reports on radiation dose are available, most studies focus on limited types of procedures and only report patient dose. In our cathlabs a dedicated real-time patient and staff monitoring system was installed in November 2015. The aim of this study was to investigate the patient and staff dose exposure for different types of interventions. Methods: Radiologists involved in fluoroscopy guided interventional radiology procedures wore personal dose meters (PDM, DoseAware, Philips) on their lead-apron that measured the personal dose equivalent Hp(10), a measure for the effective dose (E). Furthermore, reference PDMs were installed in the C-arms of the fluoroscopy system (Allura XPer, Philips). Patient dose-area-product (DAP) and PDM doses were retrieved from the monitoring system (DoseWise, Philips) for each procedure. A total of 399 procedures performed between November 2015 and February 2016 were analyzed with respect to the type of intervention. Interventions were grouped by anatomy and radiologist position. Results: The mean DAP for the different types of interventions ranged from 2.86±2.96 Gycm{sup 2} (percutaneous gastrostomy) to 147±178 Gycm{sup 2} (aortic repair procedures). The radiologist dose (E) ranged from 5.39±7.38 µSv (cerebral interventions) to 84.7±106 µSv (abdominal interventions) and strongly correlated with DAP (R{sup 2}=0.83). The E normalized to DAP showed that the relative radiologist dose was higher for interventions in larger body parts (e.g. abdomen) compared to smaller body parts (e.g. head). Conclusion: Using a real-time dose monitoring system we were able to assess the staff and patient dose revealing that the relative staff dose strongly depended on the type of procedure and patient anatomy. This could be explained by the position of the radiologist with respect to the patient and X-ray tube. To facilitate this study L Vergoossen received a scholarship from Philips Medical Systems.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-A-207B-00: Shear-Wave Imaging and a QIBA US Biomarker Update

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-A-207B-01: Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2016

TH-A-207B-02: QIBA Ultrasound Elasticity Imaging System Biomarker Qualification and User Testing of Systems

Imaging of tissue elastic properties is a relatively new and powerful approach to one of the oldest and most important diagnostic tools. Imaging of shear wave speed with ultrasound is has been added to most high-end ultrasound systems. Understanding this exciting imaging mode aiding its most effective use in medicine can be a rewarding effort for medical physicists and other medical imaging and treatment professionals. Assuring consistent, quantitative measurements across the many ultrasound systems in a typical imaging department will constitute a major step toward realizing the great potential of this technique and other quantitative imaging. This session will target these two goals with two presentations. A. Basics and Current Implementations of Ultrasound Imaging of Shear Wave Speed and Elasticity - Shigao Chen, Ph.D. Learning objectives-To understand: Introduction: Importance of tissue elasticity measurement Strain vs. shear wave elastography (SWE), beneficial features of SWE The link between shear wave speed and material properties, influence of viscosity Generation of shear waves External vibration (Fibroscan) ultrasound radiation force Point push Supersonic push (Aixplorer) Comb push (GE Logiq E9) Detection of shear waves Motion detection from pulse-echo ultrasound Importance of frame rate for shear wave imaging Plane wave imaging detection How to achieve high effective frame rate using line-by-line scanners Shear wave speed calculation Time to peak Random sample consensus (RANSAC) Cross correlation Sources of bias and variation in SWE Tissue viscosity Transducer compression or internal pressure of organ Reflection of shear waves at boundaries B. Elasticity Imaging System Biomarker Qualification and User Testing of Systems – Brian Garra, M.D. Learning objectives-To understand: Goals Review the need for quantitative medical imaging Provide examples of quantitative imaging biomarkers Acquaint the participant with the purpose of the RSNA Quantitative Imaging Biomarker Alliance and the need for such an organization Review the QIBA process for creating a quantitative biomarker Summarize steps needed to verify adherence of site, operators, and imaging systems to a QIBA profile Underlying Premise and Assumptions Objective, quantifiable results are needed to enhance the value of diagnostic imaging in clinical practice Reasons for quantification Evidence based medicine requires objective, not subjective observer data Computerized decision support tools (eg CAD) generally require quantitative input. Quantitative, reproducible measures are more easily used to develop personalized molecular medical diagnostic and treatment systems What is quantitative imaging? Definition from Imaging Metrology Workshop The Quantitative Imaging Biomarker Alliance Formation 2008 Mission Structure Example Imaging Biomarkers Being Explored Biomarker Selection Groundwork Draft Protocol for imaging and data evaluation QIBA Profile Drafting Equipment and Site Validation Technical Clinical Site and Equipment QA and Compliance Checking Ultrasound Elasticity Estimation Biomarker US Elasticity Estimation Background Current Status and Problems Biomarker Selection-process and outcome US SWS for Liver Fibrosis Biomarker Work Groundwork Literature search and analysis results Phase I phantom testing-Elastic phantoms Phase II phantom testing-Viscoelastic phantoms Digital Simulated Data Protocol and Profile Drafting Protocol: based on UPICT and existing literature and standards bodies protocols Profile-Current claims, Manufacturer specific appendices What comes after the profile Profile Validation Technical validation Clinical validation QA and Compliance Possible approaches Site Operator testing Site protocol re-evaluation Imaging system Manufacturer testing and attestation User acceptance testing and periodic QA Phantom Tests Digital Phantom Based Testing Standard QA Testing Remediation Schemes Profile Evolution Towards additional applications Towards higher accuracy and precision Supported in part by NIH contract HHSN268201300071C from NIBIB. Collaboration with GE Global Research, no personal support.; S. Chen, Some technologies described in this presentation have been licensed. Mayo Clinic and Dr. Chen have financial interests these technologies.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2026

Predictive analytics to direct clinical attention to complex patients with elevated suicide risk: enhancement of the Veterans Health Administration REACH VET model

Suicide is a major public health concern, particularly among Veterans. The U.S. Department of Veterans Affairs Veterans Health Administration (VHA) employs the Recovery Engagement and Coordination for Health–Veterans Enhanced Treatment (REACH VET) model to prioritise high-risk patients for targeted clinical attention. REACH VET 1.0 (RV 1.0) was developed on 2008–2011 data. To reflect changes in clinical practice and populations, VHA updated it to REACH VET 2.0 (RV 2.0). This study describes its development and validation. RV 2.0 used longitudinal data from 7,248,170 VHA patients (4,967 suicide deaths) in 2018–2019, with 650 time-varying demographic, clinical and area-level predictors derived from a 2-year lookback (2016–2019). An ensemble of Elastic-Net logistic regression models was trained on 2018 data and evaluated monthly at the population level in 2019, focusing on the top 0.1% intervention risk tier. Analyses assessed model discrimination, suicide detection, risk concentration, subgroup consistency (sex, age and race/ethnicity) and performance relative to RV 1.0 using the same percentile-based risk strata. RV 2.0 outperformed RV 1.0 across all risk strata, with better discrimination (C-statistic 0.76 vs 0.69) and consistent performance across demographic subgroups. Within the top 0.1% of predicted risk, RV 2.0 identified more deaths, higher suicide rates and greater mortality risk concentration both when averaged across the 12 monthly 2019 test sets (5.6 vs 3.6; 83.6 vs 53.7 per 100,000 person-years; 21.0 vs 14.1) and when annualised for 2019 (67 vs 43; 2.7% vs 1.7%; 1,003 vs 644 per 100,000 person-years; 26.7 vs 17.1). RV 2.0 improves suicide risk stratification among Veterans, demonstrating better performance and consistent prediction across subgroups and highlighting the need for regular model updates and evaluation.

Peluso, Alina [Oak Ridge National Laboratory (ORNL↗

DOE OSTI2025

From reactors to stars

This Eur. Phys. J. A volume 58 is dedicated to the life and work of Dr. Franz Käppeler from Karlsruhe Institute for Technology (KIT) who died on 20 November 2021, after a short illness. He was one of the leading experimentalists in the field of experimental nuclear astrophysics in Germany and worldwide for decades. Many of the authors of this volume knew Franz personally and many others were directly or indirectly inspired by his work and personality. All references in this introductory article refer to publications in this volume, not necessary to actual work by Dr. Käppeler.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2019

Using Digital Trace Data to Identify Regions and Cities

A greater understanding of human dynamics as they play out in both physical space and through inter-personal communication is vital for the design and development of intelligent and resilient cities. Physical context provides insight in to the space-time distribution of population and their activity patterns, while inter-personal communication can, for the first time, be measured at scale through virtual interactions. The confluence of these two enables spatial social network analysis in the built environment for edge computing, knowledge discovery, and artificial intelligence activities. In this work, we propose a novel method to discover such dynamics. We use a dataset of 72 million tweets to develop a spatially embedded network of communication, and then use community detection algorithms to explore regional and urban delineation in the United States. We find that the broad spatial delineation of communities and community sub-structure is consistent with major United States socio-cultural regions, states, and major metropolitan areas. We describe how these methods could be extended to generate a measure of socially cohesive regions that can be consistently applied anywhere there is a sufficiently rich data source. We hope the proposed methods will generate new perspectives on smart and resilient cities.

Brelsford, Christa↗

DOE OSTI2019

Dataset: Inferring Thermal Comfort using Body Shape Information Utilizing Depth Sensors

Thermal comfort is very important for well-being and productivity of building occupants. It has been shown that body shape is a useful feature to determine thermal comfort of individuals [2]. It is because, the heat dissipation rate of individuals depends on the body surface area. As a result, a tall and skinny person can tolerate higher room temperature than a rounded body shape person [5]. In order to test this hypothesis, we performed a year-long experiment in 2017, where we recruited 77 participants and put each of them in a thermally controlled conference room in CMU for 3 hours and recorded their subjective responses regarding thermal comfort at different temperature ranging from 60°F to 80°F. In addition, we collected depth data of individuals using a vertically mounted Microsoft Kinect for XBOX One at the entrance of the conference room to capture their body shape. We also collected biometric features (e.g., Galvanic Skin Response (GSR), skin temperature) using a Microsoft Health Band worn by the subjects. The resulting dataset provides rich information regarding how different features can be used to infer thermal comfort of the individuals.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2020

The Minos Computing Library: Efficient Parallel Programming for Extremely Heterogeneous Systems

Hardware specialization has become the silver bullet to achieve efficient high performance, from Systems-on-Chip systems, where hardware specialization can be ``extreme'', to large-scale HPC systems. As the complexity of the systems increases, so does the complexity of programming such architectures in a portable way. This work introduces the Minos Computing Library (MCL), as system software, programming model, and programming model runtime that facilitate programming extremely heterogeneous systems. MCL supports the execution of several multi-threaded applications within the same compute node, performs asynchronous execution of application tasks, efficiently balances computation across hardware resources, and provides performance portability. We show that code developed on a personal desktop automatically scales up to fully utilize powerful workstations with 8 GPUs and down to power-efficient embedded systems. MCL provides up to 17.5x speedup over OpenCL on NVIDIA DGX-1 systems and up to 1.88x speedup on single-GPU systems. In multi-application workloads, MCL dynamically resource allocation provides up to 2.43x performance improvement over manual, static allocation of computing resources.

Gioiosa, Roberto↗

DOE OSTI2024

In Silico Human Mobility Data Science: Leveraging Massive Simulated Mobility Data (Vision Paper)

Human mobility data science using trajectories or check-ins of individuals has many applications. Recently, we have seen a plethora of research efforts that tackle these applications. However, research progress in this field is limited by a lack of large and representative datasets. The largest and most commonly used dataset of individual human trajectories captures fewer than 200 individuals, while datasets of individual human check-ins capture fewer than 100 check-ins per city per day. Thus, it is not clear if findings from the human mobility data science community would generalize to large populations. Since obtaining massive, representative, and individual-level human mobility data is hard to come by due to privacy considerations, the vision of this work is to embrace the use of data generated by large-scale socially realistic microsimulations. Informed by both real data and leveraging social and behavioral theories, massive spatially explicit microsimulations may allow us to simulate entire megacities at the person level. The simulated worlds, which do not capture any identifiable personal information, allow us to perform “in silico” experiments using the simulated world as a sandbox in which we have perfect information and perfect control without jeopardizing the privacy of any actual individual. In silico experiments have become commonplace in other scientific domains such as chemistry and biology, permitting experiments that foster the understanding of concepts without any harm to individuals. This work describes challenges and opportunities for leveraging massive and realistic simulated alternate worlds for in silico human mobility data science.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

FiberFlex: Real-time FPGA-based Intelligent and Distributed Fiber Sensor System for Pedestrian Recognition

In recent years, security monitoring of public places and critical infrastructure has heavily relied on the widespread use of cameras, raising concerns about personal privacy violations. To balance the need for effective security monitoring with the protection of personal privacy, we explore the potential of optical fiber sensors for this application. This article proposes FiberFlex, an intelligent and distributed fiber sensor system. Ultizing Field Programmable Gate Arrays (FPGA) high-level synthesis (HLS) acceleration, FiberFlex offers real-time pedestrian detection by co-designing the entire pipeline of optical signal acquisition, processing, and recognition networks based on the principles of optical fiber sensing. As a promising alternative to traditional camera-based monitoring systems, FiberFlex achieves pedestrian detection by analyzing the vibration patterns caused by pedestrian footsteps, enabling security monitoring while preserving individual privacy. FiberFlex comprises three modules: First , fiber-optic sensing system: A fiber-optic distributed acoustic sensing (DAS) system is built and used to measure the ground vibration waves generated by people walking. Second , algorithms: We first collect the training data by measuring the ground vibration waves, label the data, and use the data to train the neural network models to perform pedestrian recognition. Third , hardware accelerators: We use HLS tools to design hardware modules on FPGA for data collection and pre-processing and integrate them with the downstream neural network accelerators to perform in-line real-time pedestrian detection. The final detection results are sent back from FPGA to the host CPU. We implement our system FiberFlex with the in-house built DAS system and AMD/Xilinx Kintex7 FPGA KC705 board and verify the whole system using the real-world collected data. We conduct recognition tests on five test subjects of varying ages, heights, and weights in a fixed sensing area. Each subject experienced 20 real-time recognition tests using their daily walking habits, and the subjects were given adequate rest between tests. After 100 tests on five test subjects, the overall real-time recognition accuracy exceeded \(88.0\%\) . The whole system uses 55 W of power, 33 W in the optical DAS system and 22 W in the FPGA. Relying on its end-to-end interdisciplinary design, FiberFlex seamlessly combines fiber-optic sensors with FPGA accelerators to enable low-power real-time security monitoring without compromising privacy, making it a valuable addition to the existing security monitoring network. According to FiberFlex, more valuable research can be conducted in the future, such as fall monitoring for the elderly, migration of identification networks between different application scenarios, and improvement of anti-interference performance in more complex environments. In future perception networks, where the “eyes” are not feasible, let’s use fiber optic touch instead.

Distributed↗