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Bolus use during postmastectomy radiation therapy doubles the risk of grade 2 and 3 skin toxicity. Despite its unknown benefit, bolus is often prescribed during postmastectomy radiation therapy for patients without skin involvement.
No abstract prepared.
The poor response of breast cancer to immune checkpoint blockade might result from low immunogenicity and the immune-suppressive tumor microenvironment. We hypothesized that in situ tumor vaccination via radiation therapy (RT) and suppression of immune tolerance via phosphoinositide 3-kinase δ (PI3Kδ) inhibition would enhance the efficacy of immune checkpoint blockade.
Prone position for whole breast irradiation (WBI) results in lower rates of toxicity and reduced ipsilateral mean lung and heart doses. No randomized trials comparing toxicity and cosmesis at 5 years with prone and supine positioning are available.
To report the long-term efficacy and toxicity of proton therapy for pediatric ependymoma.
Cardiac radioablation is a novel treatment option for therapy-refractory ventricular tachycardia (VT) ineligible for catheter ablation. Three-dimensional clinical target volume (CTV) definition is a key step, and this complex interdisciplinary procedure includes VT-substrate identification based on electroanatomical mapping (EAM) and its transfer to the planning computed tomography (PCT). Benchmarking of this process is necessary for multicenter clinical studies such as the RAVENTA trial.
No abstract prepared.
Nurses in the radiation oncology (RO) clinic have a critical role in the management of patients receiving radiation therapy. However, limited data exist regarding the exposure of nurses to RO during training and the current educational needs of practicing RO nurses. This study assesses nurses’ prior RO education, participation in national training efforts, and perceived educational needs.
Two phase 3 randomized controlled trials (OTT-0101, RTOG-9413) and a meta-analysis have shown an impact of sequencing of androgen deprivation therapy (ADT) and radiation therapy on oncologic outcomes in prostate cancer (PCa). However, the impact of sequencing strategy on health-related quality of life (HR-QoL) is unclear. Here, we present the patient-reported HR-QoL outcomes from the OTT-0101 study.
It is well known that physicians underascertain chemotherapy-related toxicity compared with patient self-report. However, symptom underascertainment in radiation therapy and characterization of patient groups at increased risk for underascertainment have not been examined.
Decreased peripheral lymphocyte counts are associated with survival after radiation therapy (RT) in several solid tumors, although they appear late during or after the radiation course and often correlate with other clinical factors. Here we investigate if absolute lymphocyte counts (ALCs) are independently associated with recurrence in pediatric medulloblastoma early during RT.
Reirradiation for locally recurrent nasopharyngeal carcinoma (NPC) is challenging because prior radiation dose delivered in the first course is often close to the tolerance limit of surrounding normal structures. A delicate balance between achieving local salvage and minimizing treatment toxicities is needed. However, high-level evidence is lacking because available reports are mostly retrospective studies on small series of patients. Pragmatic consensus guidelines, based on an extensive literature search and the pooling of opinions by leading specialists, will provide a useful reference to assist decision-making for these difficult decisions.
Novel actuarial deep learning neural network (ADNN) architectures are proposed for joint prediction of radiation therapy outcomes—radiation pneumonitis (RP) and local control (LC)—in stage III non-small cell lung cancer (NSCLC) patients. Unlike normal tissue complication probability/tumor control probability models that use dosimetric information solely, our proposed models consider complex interactions among multiomics information including positron emission tomography (PET) radiomics, cytokines, and miRNAs. Additional time-to-event information is also used in the actuarial prediction.
Data comparing moderately hypofractionated intensity modulated radiation therapy (IMRT) and proton beam therapy (PBT) are lacking. We aim to compare late toxicity profiles of patients with early-stage prostate cancer treated with moderately hypofractionated PBT and IMRT.
Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.
Advances in germline genetic testing have led to a surge in identification of ataxia-telangiectasia mutated (ATM) variant carriers among breast cancer patients, raising numerous questions regarding use of breast radiation therapy (RT) in this population.
Radiation-induced gastrointestinal syndrome (RIGS) is currently the main cause of death for people exposed to a high dose of irradiation during nuclear incidents, and there is currently no approved effective therapy. Here, we found that CBP/P300 inhibitors, with high efficacy and low toxicity, might be promising radiation mitigators that can cure RIGS.
Autoimmune connective tissue disease (CTD) has historically represented a relative contraindication to breast conservation (BC) among patients with early-stage breast cancer. Controversy exists regarding the use of hypofractionated radiation therapy (RT) among patients with CTDs. We evaluated acute and late toxicity in patients with breast cancer and CTD treated with BC.