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Photoacoustic detection and optical spectroscopy of high-intensity focused ultrasound-induced thermal lesions in biologic tissue

Purpose: The aims of this study are: (a) to investigate the capability of photoacoustic (PA) method in detecting high-intensity focused ultrasound (HIFU) treatments in muscle tissuesin vitro; and (b) to determine the optical properties of HIFU-treated and native tissues in order to assist in the interpretation of the observed contrast in PA detection of HIFU treatments. Methods: A single-element, spherically concaved HIFU transducer with a centre frequency of 1 MHz was utilized to create thermal lesions in chicken breast tissuesin vitro. To investigate the detectability of HIFU treatments photoacoustically, PA detection was performed at 720 and 845 nm on seven HIFU-treated tissue samples. Within each tissue sample, PA signals were acquired from 22 locations equally divided between two regions of interest within two volumes in tissue – a HIFU-treated volume and an untreated volume. Optical spectroscopy was then carried out on 10 HIFU-treated chicken breast specimens in the wavelength range of 500–900 nm, in 1-nm increments, using a spectrophotometer with an integrating sphere attachment. The authors’ optical spectroscopy raw data (total transmittance and diffuse reflectance) were used to obtain the optical absorption and reduced scattering coefficients of HIFU-induced thermal lesions and native tissues by employing the inverse adding-doubling method. The aforementioned interaction coefficients were subsequently used to calculate the effective attenuation coefficient and light penetration depth of HIFU-treated and native tissues in the wavelength range of 500–900 nm. Results: HIFU-treated tissues produced greater PA signals than native tissues at 720 and 845 nm. At 720 nm, the averaged ratio of the peak-to-peak PA signal amplitude of HIFU-treated tissue to that of native tissue was 3.68 ± 0.25 (mean ± standard error of the mean). At 845 nm, the averaged ratio of the peak-to-peak PA signal amplitude of HIFU-treated tissue to that of native tissue was 3.75 ± 0.26 (mean ± standard error of the mean). The authors’ spectroscopic investigation has shown that HIFU-treated tissues have a greater optical absorption and reduced scattering coefficients than native tissues in the wavelength range of 500–900 nm. In fact, at 720 and 845 nm, the ratio of the optical absorption coefficient of HIFU-treated tissues to that of native tissues was 1.13 and 1.17, respectively; on the other hand, the ratio of the reduced scattering coefficient of HIFU-treated tissues to that of native tissues was 13.22 and 14.67 at 720 and 845 nm, respectively. Consequently, HIFU-treated tissues have a higher effective attenuation coefficient and a lower light penetration depth than native tissues in the wavelength range 500–900 nm. Conclusions: Using a PA approach, HIFU-treated tissues interrogated at 720 and 845 nm optical wavelengths can be differentiated from untreated tissues. Based on the authors’ spectroscopic investigation, the authors conclude that the observed PA contrast between HIFU-induced thermal lesions and untreated tissue is due, in part, to the increase in the optical absorption coefficient, the reduced scattering coefficient and, therefore, the deposited laser energy fluence in HIFU-treated tissues.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Task-based detectability in CT image reconstruction by filtered backprojection and penalized likelihood estimation

Purpose: Nonstationarity is an important aspect of imaging performance in CT and cone-beam CT (CBCT), especially for systems employing iterative reconstruction. This work presents a theoretical framework for both filtered-backprojection (FBP) and penalized-likelihood (PL) reconstruction that includes explicit descriptions of nonstationary noise, spatial resolution, and task-based detectability index. Potential utility of the model was demonstrated in the optimal selection of regularization parameters in PL reconstruction. Methods: Analytical models for local modulation transfer function (MTF) and noise-power spectrum (NPS) were investigated for both FBP and PL reconstruction, including explicit dependence on the object and spatial location. For FBP, a cascaded systems analysis framework was adapted to account for nonstationarity by separately calculating fluence and system gains for each ray passing through any given voxel. For PL, the point-spread function and covariance were derived using the implicit function theorem and first-order Taylor expansion according toFessler [“Mean and variance of implicitly defined biased estimators (such as penalized maximum likelihood): Applications to tomography,” IEEE Trans. Image Process. 5(3), 493–506 (1996)]. Detectability index was calculated for a variety of simple tasks. The model for PL was used in selecting the regularization strength parameter to optimize task-based performance, with both a constant and a spatially varying regularization map. Results: Theoretical models of FBP and PL were validated in 2D simulated fan-beam data and found to yield accurate predictions of local MTF and NPS as a function of the object and the spatial location. The NPS for both FBP and PL exhibit similar anisotropic nature depending on the pathlength (and therefore, the object and spatial location within the object) traversed by each ray, with the PL NPS experiencing greater smoothing along directions with higher noise. The MTF of FBP is isotropic and independent of location to a first order approximation, whereas the MTF of PL is anisotropic in a manner complementary to the NPS. Task-based detectability demonstrates dependence on the task, object, spatial location, and smoothing parameters. A spatially varying regularization “map” designed from locally optimal regularization can improve overall detectability beyond that achievable with the commonly used constant regularization parameter. Conclusions: Analytical models for task-based FBP and PL reconstruction are predictive of nonstationary noise and resolution characteristics, providing a valuable framework for understanding and optimizing system performance in CT and CBCT.

62 RADIOLOGY AND NUCLEAR MEDICINE↗

SU-F-18C-01: Minimum Detectability Analysis for Comprehensive Sized Based Optimization of Image Quality and Radiation Dose Across CT Protocols

Purpose: This work involved a comprehensive modeling of task-based performance of CT across a wide range of protocols. The approach was used for optimization and consistency of dose and image quality within a large multi-vendor clinical facility. Methods: 150 adult protocols from the Duke University Medical Center were grouped into sub-protocols with similar acquisition characteristics. A size based image quality phantom (Duke Mercury Phantom) was imaged using these sub-protocols for a range of clinically relevant doses on two CT manufacturer platforms (Siemens, GE). The images were analyzed to extract task-based image quality metrics such as the Task Transfer Function (TTF), Noise Power Spectrum, and Az based on designer nodule task functions. The data were analyzed in terms of the detectability of a lesion size/contrast as a function of dose, patient size, and protocol. A graphical user interface (GUI) was developed to predict image quality and dose to achieve a minimum level of detectability. Results: Image quality trends with variations in dose, patient size, and lesion contrast/size were evaluated and calculated data behaved as predicted. The GUI proved effective to predict the Az values representing radiologist confidence for a targeted lesion, patient size, and dose. As an example, an abdomen pelvis exam for the GE scanner, with a task size/contrast of 5-mm/50-HU, and an Az of 0.9 requires a dose of 4.0, 8.9, and 16.9 mGy for patient diameters of 25, 30, and 35 cm, respectively. For a constant patient diameter of 30 cm, the minimum detected lesion size at those dose levels would be 8.4, 5, and 3.9 mm, respectively. Conclusion: The designed CT protocol optimization platform can be used to evaluate minimum detectability across dose levels and patient diameters. The method can be used to improve individual protocols as well as to improve protocol consistency across CT scanners.

60 APPLIED LIFE SCIENCES↗

TH-C-17A-01: Imaging Sensor Comparison for Real-Time Cherenkov Signal Detection From Tissue for Treatment Verification

Purpose: To identify the optimum imaging sensor for a clinical system that would provide real-time imaging of the surface beam profile on patients as novel visual information to radiation therapy technologists, and more rapidly collect clinical data for large-scale studies of Cherenkov applications in radiotherapy. Methods: Four camera types, CMOS, CCD, ICCD and EMICCD, were tested to determine proficiency in the detection of Cherenkov signal in the clinical radiotherapy setting, and subsequent maximum supportable frame rate. Where possible, time-gating between the trigger signal from the LINAC and the intensifiers was implemented to detect signal with room lighting conditions comparable to patient treatment scenarios. A solid water phantom was imaged by the EM-ICCD and ICCD to evaluate the minimum number of accumulations-on-chip required for adequate Cherenkov detection, defined as >200% electron counts per pixel over background signal. Additionally, an ICCD and EM-ICCD were used clinically to image patients undergoing whole-breast radiation therapy, to understand the impact of the resolution limitation of the EM-ICCD. Results: The intensifier-coupled cameras performed best at imaging Cherenkov signal, even with room lights on, which is essential for patient comfort. The tested EM-ICCD was able to support single-shot imaging and frame rates of 30 fps, however, the current maximum resolution of 512 × 512 pixels was restricting. The ICCD used in current clinical trials was limited to 4.7 fps at a 1024 × 1024 resolution. An intensifier with higher quantum efficiency at the entrance photocathode in the red wavelengths (30% QE vs current 7%) promises 16 fps at the same resolution at lower cost than the EM-ICCD. Conclusion: The ICCD with the better red wavelength QE intensifier was determined to be the best suited commercial-off-the-shelf camera to detect real-time Cherenkov signal and provide the best potential for real-time display of radiation dose on the skin during treatment. Funding is from grants from the NIH numbers R01CA109558 and R21EB017559.

60 APPLIED LIFE SCIENCES↗

Pulmonary nodule detection in CT images based on shape constraint CV model

Purpose: Accurate detection of pulmonary nodules remains a technical challenge in computer-aided diagnosis systems because some nodules may adhere to the blood vessels or the lung wall, which have low contrast compared to the surrounding tissues. In this paper, the analysis of typical shape features of candidate nodules based on a shape constraint Chan–Vese (CV) model combined with calculation of the number of blood branches adhered to nodule candidates is proposed to reduce false positive (FP) nodules from candidate nodules. Methods: The proposed scheme consists of three major stages: (1) Segmentation of lung parenchyma from computed tomography images. (2) Extraction of candidate nodules. (3) Reduction of FP nodules. A gray level enhancement combined with a spherical shape enhancement filter is introduced to extract the candidate nodules and their sphere-like contour regions. FPs are removed by analysis of the typical shape features of nodule candidates based on the CV model using spherical constraint and by investigating the number of blood branches adhered to the candidate nodules. The constrained shapes of CV model are automatically achieved from the extracted candidate nodules. Results: The detection performance was evaluated on 127 nodules of 103 cases including three types of challenging nodules, which are juxta-pleural nodules, juxta-vascular nodules, and ground glass opacity nodules. The free-receiver operating characteristic (FROC) curve shows that the proposed method is able to detect 88% of all the nodules in the data set with 4 FPs per case. Conclusions: Evaluation shows that the authors’ method is feasible and effective for detection of three types of nodules in this study.

60 APPLIED LIFE SCIENCES↗

SU-D-BRD-07: Evaluation of the Effectiveness of Statistical Process Control Methods to Detect Systematic Errors For Routine Electron Energy Verification

Purpose: To evaluate the ability of statistical process control methods to detect systematic errors when using a two dimensional (2D) detector array for routine electron beam energy verification. Methods: Electron beam energy constancy was measured using an aluminum wedge and a 2D diode array on four linear accelerators. Process control limits were established. Measurements were recorded in control charts and compared with both calculated process control limits and TG-142 recommended specification limits. The data was tested for normality, process capability and process acceptability. Additional measurements were recorded while systematic errors were intentionally introduced. Systematic errors included shifts in the alignment of the wedge, incorrect orientation of the wedge, and incorrect array calibration. Results: Control limits calculated for each beam were smaller than the recommended specification limits. Process capability and process acceptability ratios were greater than one in all cases. All data was normally distributed. Shifts in the alignment of the wedge were most apparent for low energies. The smallest shift (0.5 mm) was detectable using process control limits in some cases, while the largest shift (2 mm) was detectable using specification limits in only one case. The wedge orientation tested did not affect the measurements as this did not affect the thickness of aluminum over the detectors of interest. Array calibration dependence varied with energy and selected array calibration. 6 MeV was the least sensitive to array calibration selection while 16 MeV was the most sensitive. Conclusion: Statistical process control methods demonstrated that the data distribution was normally distributed, the process was capable of meeting specifications, and that the process was centered within the specification limits. Though not all systematic errors were distinguishable from random errors, process control limits increased the ability to detect systematic errors using routine measurement of electron beam energy constancy.

07 ISOTOPE AND RADIATION SOURCES↗

SU-E-T-392: Evaluation of Ion Chamber/film and Log File Based QA to Detect Delivery Errors

Purpose: Ion chamber and film (ICAF) is a method used to verify patient dose prior to treatment. More recently, log file based QA has been shown as an alternative for measurement based QA. In this study, we delivered VMAT plans with and without errors to determine if ICAF and/or log file based QA was able to detect the errors. Methods: Using two VMAT patients, the original treatment plan plus 7 additional plans with delivery errors introduced were generated and delivered. The erroneous plans had gantry, collimator, MLC, gantry and collimator, collimator and MLC, MLC and gantry, and gantry, collimator, and MLC errors. The gantry and collimator errors were off by 4{sup 0} for one of the two arcs. The MLC error introduced was one in which the opening aperture didn’t move throughout the delivery of the field. For each delivery, an ICAF measurement was made as well as a dose comparison based upon log files. Passing criteria to evaluate the plans were ion chamber less and 5% and film 90% of pixels pass the 3mm/3% gamma analysis(GA). For log file analysis 90% of voxels pass the 3mm/3% 3D GA and beam parameters match what was in the plan. Results: Two original plans were delivered and passed both ICAF and log file base QA. Both ICAF and log file QA met the dosimetry criteria on 4 of the 12 erroneous cases analyzed (2 cases were not analyzed). For the log file analysis, all 12 erroneous plans alerted a mismatch in delivery versus what was planned. The 8 plans that didn’t meet criteria all had MLC errors. Conclusion: Our study demonstrates that log file based pre-treatment QA was able to detect small errors that may not be detected using an ICAF and both methods of were able to detect larger delivery errors.

60 APPLIED LIFE SCIENCES↗

WE-EF-207-03: Design and Optimization of a CBCT Head Scanner for Detection of Acute Intracranial Hemorrhage

Purpose: To design a dedicated x-ray cone-beam CT (CBCT) system suitable to deployment at the point-of-care and offering reliable detection of acute intracranial hemorrhage (ICH), traumatic brain injury (TBI), stroke, and other head and neck injuries. Methods: A comprehensive task-based image quality model was developed to guide system design and optimization of a prototype head scanner suitable to imaging of acute TBI and ICH. Previously reported models were expanded to include the effects of x-ray scatter correction necessary for detection of low contrast ICH and the contribution of bit depth (digitization noise) to imaging performance. Task-based detectablity index provided the objective function for optimization of system geometry, x-ray source, detector type, anti-scatter grid, and technique at 10–25 mGy dose. Optimal characteristics were experimentally validated using a custom head phantom with 50 HU contrast ICH inserts imaged on a CBCT imaging bench allowing variation of system geometry, focal spot size, detector, grid selection, and x-ray technique. Results: The model guided selection of system geometry with a nominal source-detector distance 1100 mm and optimal magnification of 1.50. Focal spot size ∼0.6 mm was sufficient for spatial resolution requirements in ICH detection. Imaging at 90 kVp yielded the best tradeoff between noise and contrast. The model provided quantitation of tradeoffs between flat-panel and CMOS detectors with respect to electronic noise, field of view, and readout speed required for imaging of ICH. An anti-scatter grid was shown to provide modest benefit in conjunction with post-acquisition scatter correction. Images of the head phantom demonstrate visualization of millimeter-scale simulated ICH. Conclusions: Performance consistent with acute TBI and ICH detection is feasible with model-based system design and robust artifact correction in a dedicated head CBCT system. Further improvements can be achieved with incorporation of model-based iterative reconstruction techniques also within the scope of the task-based optimization framework. David Foos and Xiaohui Wang are employees of Carestream Health.

60 APPLIED LIFE SCIENCES↗

Theoretical detection threshold of the proton-acoustic range verification technique

Purpose: Range verification in proton therapy using the proton-acoustic signal induced in the Bragg peak was investigated for typical clinical scenarios. The signal generation and detection processes were simulated in order to determine the signal-to-noise limits. Methods: An analytical model was used to calculate the dose distribution and local pressure rise (per proton) for beams of different energy (100 and 160 MeV) and spot widths (1, 5, and 10 mm) in a water phantom. In this method, the acoustic waves propagating from the Bragg peak were generated by the general 3D pressure wave equation implemented using a finite element method. Various beam pulse widths (0.1–10 μs) were simulated by convolving the acoustic waves with Gaussian kernels. A realistic PZT ultrasound transducer (5 cm diameter) was simulated with a Butterworth bandpass filter with consideration of random noise based on a model of thermal noise in the transducer. The signal-to-noise ratio on a per-proton basis was calculated, determining the minimum number of protons required to generate a detectable pulse. The maximum spatial resolution of the proton-acoustic imaging modality was also estimated from the signal spectrum. Results: The calculated noise in the transducer was 12–28 mPa, depending on the transducer central frequency (70–380 kHz). The minimum number of protons detectable by the technique was on the order of 3–30 × 10{sup 6} per pulse, with 30–800 mGy dose per pulse at the Bragg peak. Wider pulses produced signal with lower acoustic frequencies, with 10 μs pulses producing signals with frequency less than 100 kHz. Conclusions: The proton-acoustic process was simulated using a realistic model and the minimal detection limit was established for proton-acoustic range validation. These limits correspond to a best case scenario with a single large detector with no losses and detector thermal noise as the sensitivity limiting factor. Our study indicated practical proton-acoustic range verification may be feasible with approximately 5 × 10{sup 6} protons/pulse and beam current.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Automated detection of vessel lumen and stent struts in intravascular optical coherence tomography to evaluate stent apposition and neointimal coverage

Purpose: Intravascular optical coherence tomography (IV-OCT) is a high-resolution imaging method used to visualize the microstructure of arterial walls in vivo. IV-OCT enables the clinician to clearly observe and accurately measure stent apposition and neointimal coverage of coronary stents, which are associated with side effects such as in-stent thrombosis. In this study, the authors present an algorithm for quantifying stent apposition and neointimal coverage by automatically detecting lumen contours and stent struts in IV-OCT images. Methods: The algorithm utilizes OCT intensity images and their first and second gradient images along the axial direction to detect lumen contours and stent strut candidates. These stent strut candidates are classified into true and false stent struts based on their features, using an artificial neural network with one hidden layer and ten nodes. After segmentation, either the protrusion distance (PD) or neointimal thickness (NT) for each strut is measured automatically. In randomly selected image sets covering a large variety of clinical scenarios, the results of the algorithm were compared to those of manual segmentation by IV-OCT readers. Results: Stent strut detection showed a 96.5% positive predictive value and a 92.9% true positive rate. In addition, case-by-case validation also showed comparable accuracy for most cases. High correlation coefficients (R > 0.99) were observed for PD and NT between the algorithmic and the manual results, showing little bias (0.20 and 0.46 μm, respectively) and a narrow range of limits of agreement (36 and 54 μm, respectively). In addition, the algorithm worked well in various clinical scenarios and even in cases with a low level of stent malapposition and neointimal coverage. Conclusions: The presented automatic algorithm enables robust and fast detection of lumen contours and stent struts and provides quantitative measurements of PD and NT. In addition, the algorithm was validated using various clinical cases to demonstrate its reliability. Therefore, this technique can be effectively utilized for clinical trials on stent-related side effects, including in-stent thrombosis and in-stent restenosis.

60 APPLIED LIFE SCIENCES↗

Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications

Purpose: In the past decades, computer-aided detection (CADe) systems have been developed to aid screening radiologists in the detection of malignant microcalcifications. These systems are useful to avoid perceptual oversights and can increase the radiologists’ detection rate. However, due to the high number of false positives marked by these CADe systems, they are not yet suitable as an independent reader. Breast arterial calcifications (BACs) are one of the most frequent false positives marked by CADe systems. In this study, a method is proposed for the elimination of BACs as positive findings. Removal of these false positives will increase the performance of the CADe system in finding malignant microcalcifications. Methods: A multistage method is proposed for the removal of BAC findings. The first stage consists of a microcalcification candidate selection, segmentation and grouping of the microcalcifications, and classification to remove obvious false positives. In the second stage, a case-based selection is applied where cases are selected which contain BACs. In the final stage, BACs are removed from the selected cases. The BACs removal stage consists of a GentleBoost classifier trained on microcalcification features describing their shape, topology, and texture. Additionally, novel features are introduced to discriminate BACs from other positive findings. Results: The CADe system was evaluated with and without BACs removal. Here, both systems were applied on a validation set containing 1088 cases of which 95 cases contained malignant microcalcifications. After bootstrapping, free-response receiver operating characteristics and receiver operating characteristics analyses were carried out. Performance between the two systems was compared at 0.98 and 0.95 specificity. At a specificity of 0.98, the sensitivity increased from 37% to 52% and the sensitivity increased from 62% up to 76% at a specificity of 0.95. Partial areas under the curve in the specificity range of 0.8–1.0 were significantly different between the system without BACs removal and the system with BACs removal, 0.129 ± 0.009 versus 0.144 ± 0.008 (p<0.05), respectively. Additionally, the sensitivity at one false positive per 50 cases and one false positive per 25 cases increased as well, 37% versus 51% (p<0.05) and 58% versus 67% (p<0.05) sensitivity, respectively. Additionally, the CADe system with BACs removal reduces the number of false positives per case by 29% on average. The same sensitivity at one false positive per 50 cases in the CADe system without BACs removal can be achieved at one false positive per 80 cases in the CADe system with BACs removal. Conclusions: By using dedicated algorithms to detect and remove breast arterial calcifications, the performance of CADe systems can be improved, in particular, at false positive rates representative for operating points used in screening.

60 APPLIED LIFE SCIENCES↗

SU-F-T-310: Does a Head-Mounted Ionization Chamber Detect IMRT Errors?

Purpose: The conventional plan verification strategy is delivering a plan to a QA-phantom before the first treatment. Monitoring each fraction of the patient treatment in real-time would improve patient safety. We evaluated how well a new detector, the IQM (iRT Systems, Germany), is capable of detecting errors we induced into IMRT plans of three different treatment regions. Results were compared to an established phantom. Methods: Clinical plans of a brain, prostate and head-and-neck patient were modified in the Pinnacle planning system, such that they resulted in either several percent lower prescribed doses to the target volume or several percent higher doses to relevant organs at risk. Unaltered plans were measured on three days, modified plans once, each with the IQM at an Elekta Synergy with an Agility MLC. All plans were also measured with the ArcCHECK with the cavity plug and a PTW semiflex 31010 ionization chamber inserted. Measurements were evaluated with SNC patient software. Results: Repeated IQM measurements of the original plans were reproducible, such that a 1% deviation from the mean as warning and 3% as action level as suggested by the manufacturer seemed reasonable. The IQM detected most of the simulated errors including wrong energy, a faulty leaf, wrong trial exported and a 2 mm shift of one leaf bank. Detection limits were reached for two plans - a 2 mm field position error and a leaf bank offset combined with an MU change. ArcCHECK evaluation according to our current standards also left undetected errors. Ionization chamber evaluation alone would leave most errors undetected. Conclusion: The IQM detected most errors and performed as well as currently established phantoms with the advantage that it can be used throughout the whole treatment. Drawback is that it does not indicate the source of the error.

60 APPLIED LIFE SCIENCES↗

SU-G-BRB-11: On the Sensitivity of An EPID-Based 3D Dose Verification System to Detect Delivery Errors in VMAT Treatments

Purpose: To investigate the sensitivity of an EPID-based 3D dose verification system to detect delivery errors in VMAT treatments. Methods: For this study 41 EPID-reconstructed 3D in vivo dose distributions of 15 different VMAT plans (H&N, lung, prostate and rectum) were selected. To simulate the effect of delivery errors, their TPS plans were modified by: 1) scaling of the monitor units by ±3% and ±6% and 2) systematic shifting of leaf bank positions by ±1mm, ±2mm and ±5mm. The 3D in vivo dose distributions where then compared to the unmodified and modified treatment plans. To determine the detectability of the various delivery errors, we made use of a receiver operator characteristic (ROC) methodology. True positive and false positive rates were calculated as a function of the γ-parameters γmean, γ1% (near-maximum γ) and the PTV dose parameter ΔD{sub 50} (i.e. D{sub 50}(EPID)-D{sub 50}(TPS)). The ROC curve is constructed by plotting the true positive rate vs. the false positive rate. The area under the ROC curve (AUC) then serves as a measure of the performance of the EPID dosimetry system in detecting a particular error; an ideal system has AUC=1. Results: The AUC ranges for the machine output errors and systematic leaf position errors were [0.64 – 0.93] and [0.48 – 0.92] respectively using γmean, [0.57 – 0.79] and [0.46 – 0.85] using γ1% and [0.61 – 0.77] and [ 0.48 – 0.62] using ΔD{sub 50}. Conclusion: For the verification of VMAT deliveries, the parameter γmean is the best discriminator for the detection of systematic leaf position errors and monitor unit scaling errors. Compared to γmean and γ1%, the parameter ΔD{sub 50} performs worse as a discriminator in all cases.

60 APPLIED LIFE SCIENCES↗

TU-FG-209-11: Validation of a Channelized Hotelling Observer to Optimize Chest Radiography Image Processing for Nodule Detection: A Human Observer Study

Purpose: To validate the use of a Channelized Hotelling Observer (CHO) model for guiding image processing parameter selection and enable improved nodule detection in digital chest radiography. Methods: In a previous study, an anthropomorphic chest phantom was imaged with and without PMMA simulated nodules using a GE Discovery XR656 digital radiography system. The impact of image processing parameters was then explored using a CHO with 10 Laguerre-Gauss channels. In this work, we validate the CHO’s trend in nodule detectability as a function of two processing parameters by conducting a signal-known-exactly, multi-reader-multi-case (MRMC) ROC observer study. Five naive readers scored confidence of nodule visualization in 384 images with 50% nodule prevalence. The image backgrounds were regions-of-interest extracted from 6 normal patient scans, and the digitally inserted simulated nodules were obtained from phantom data in previous work. Each patient image was processed with both a near-optimal and a worst-case parameter combination, as determined by the CHO for nodule detection. The same 192 ROIs were used for each image processing method, with 32 randomly selected lung ROIs per patient image. Finally, the MRMC data was analyzed using the freely available iMRMC software of Gallas et al. Results: The image processing parameters which were optimized for the CHO led to a statistically significant improvement (p=0.049) in human observer AUC from 0.78 to 0.86, relative to the image processing implementation which produced the lowest CHO performance. Conclusion: Differences in user-selectable image processing methods on a commercially available digital radiography system were shown to have a marked impact on performance of human observers in the task of lung nodule detection. Further, the effect of processing on humans was similar to the effect on CHO performance. Future work will expand this study to include a wider range of detection/classification tasks and more observers, including experienced chest radiologists.

60 APPLIED LIFE SCIENCES↗

Spin-filter tunneling detection of antiferromagnetic resonance with electrically tunable damping

Antiferromagnetic spintronics offers the potential for higher-frequency operations and improved insensitivity to magnetic fields compared to ferromagnetic spintronics. However, previous electrical techniques to detect antiferromagnetic dynamics have utilized large, millimeter-scale bulk crystals. In this work, we demonstrate direct electrical detection of antiferromagnetic resonance in structures on the few-micrometer scale using spin-filter tunneling in platinum ditelluride (PtTe 2 )/bilayer chromium sulfide bromide (CrSBr)/graphite junctions in which the tunnel barrier is the van der Waals antiferromagnet CrSBr. This sample geometry allows not only efficient detection but also electrical control of the antiferromagnetic resonance through spin-orbit torque from the PtTe 2 electrode. The ability to efficiently detect and control antiferromagnetic resonance enables detailed studies of the physics governing these high-frequency dynamics.

Cham, Thow Min Jerald [Cornell University, Ithaca,↗

When Is a Microbial Culture “Pure”? Persistent Cryptic Contaminant Escapes Detection Even with Deep Genome Sequencing

Geobacter sulfurreducens strain KN400 was recovered in previous studies in which a culture of the DL1 strain of G. sulfurreducens served as the inoculum in investigations of microbial current production at low anode potentials (-400 mV versus Ag/AgCl). Differences in the genome sequences of KN400 and DL1 were too great to have arisen from adaptive evolution during growth on the anode. Previous deep sequencing (80-fold coverage) of the DL1 culture failed to detect sequences specific to KN400, suggesting that KN400 was an external contaminant inadvertently introduced into the anode culturing system. In order to evaluate this further, a portion of the gene for OmcS, a c -type cytochrome that both KN400 and DL1 possess, was amplified from the DL1 culture. HiSeq-2000 Illumina sequencing of the PCR product detected the KN400 sequence, which differs from the DL1 sequence at 14 bp, at a frequency of ca. 1 in 10 5 copies of the DL1 sequence. A similar low frequency of KN400 was detected with quantitative PCR of a KN400-specific gene. KN400 persisted at this frequency after intensive restreaking of isolated colonies from the DL1 culture. However, a culture in which KN400 could no longer be detected was obtained by serial dilution to extinction in liquid medium. The KN400-free culture could not grow on an anode poised at -400 mV. Thus, KN400 cryptically persisted in the culture dominated by DL1 for more than a decade, undetected by even deep whole-genome sequencing, and was only fortuitously uncovered by the unnatural selection pressure of growth on a low-potential electrode. IMPORTANCE: Repeated streaking of isolated colonies on solidified medium remains a common strategy for obtaining pure cultures, especially of difficult-to-cultivate microorganisms such as strict anaerobes. The results presented here demonstrate that verifying the purity of cultures obtained in this manner may be difficult because extremely rare variants can persist, undetectable with even deep genomic DNA sequencing. The only way to ensure that a culture is pure is to cultivate it from an initial single cell, which may be technically difficult for many environmentally significant microbes.

59 BASIC BIOLOGICAL SCIENCES↗

Testing of the method for water microleakage detection from OH hydroxyl spectral lines at the L-2M stellarator

Results are presented from L-2M stellarator experiments on testing a possible method for detection of water microleakages in the cooling system of the first wall and vacuum chamber of ITER. The method consists in the spectroscopic detection of spectral lines of the OH hydroxyl, which forms via the dissociation of water molecules in plasma. Emission in the spectral band of 305-310 nm can be detected even at water leakage rates less than 10{sup -4} Pa m{sup 3}/s. Chemical reactions between water and boron compounds on the vacuum chamber wall delay the detection of leakages up to {approx}2000 s. A similar phenomenon can be expected when a leakage will occur in ITER, where the materials suggested for the first wall (Be, Li) can also chemically react with water.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Results From Invoking Artificial Neural Networks to Measure Insider Threat Detection & Mitigation

Advances on differentiating between malicious intent and natural “organizational evolution” to explain observed anomalies in operational workplace patterns suggest benefit from evaluating collective behaviors observed in the facilities to improve insider threat detection and mitigation (ITDM). Advances in artificial neural networks (ANN) provide more robust pathways for capturing, analyzing, and collating disparate data signals into quantitative descriptions of operational workplace patterns. In response, a joint study by Sandia National Laboratories and the University of Texas at Austin explored the effectiveness of commercial artificial neural network (ANN) software to improve ITDM. Overall, this research demonstrates the benefit of learning patterns of organizational behaviors, detecting off-normal (or anomalous) deviations from these patterns, and alerting when certain types, frequencies, or quantities of deviations emerge for improving ITDM. Evaluating nearly 33,000 access control data points and over 1,600 intrusion sensor data points collected over a nearly twelve-month period, this study's results demonstrated the ANN could recognize operational patterns at the Nuclear Engineering Teaching Laboratory (NETL) and detect off-normal behaviors—suggesting that ANNs can be used to support a data-analytic approach to ITDM. Several representative experiments were conducted to further evaluate these conclusions, with the resultant insights supporting collective behavior-based analytical approaches to quantitatively describe insider threat detection and mitigation.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗