Stephen R. Bowen, PhD

Uncertainty-aware multimodal biomarker-guided treatment response prediction in metastatic NSCLC remains a critical unmet need to support robust therapy selection and adaptation over time. We developed a multimodal framework integrating FDG-PET, T-cell recepto...

Total body, marrow, and lymphoid irradiation represent some of the most complex and technically demanding areas in modern radiation therapy. Total body irradiation, in particular, plays a crucial role in the management of certain leukemias and lymphomas, serv...

Lung cancer is a leading global malignancy with high mortality. Radiotherapy is a critical treatment; however, current planning often suffers from subjective dose settings and side effects. This study aims to use a Conditional Generative Adversarial Network (...

Proton radiation therapy (PRT) is an effective modality for ocular cancers. Substantial evidence indicates that proton relative biological effectiveness (RBE) increases with linear energy transfer (LET). In vitro DNA double-strand break (DSB) and cell surviva...

To determine optimal scan and reconstruction parameters of a novel dual-energy CT (DECT) scanner for radiotherapy treatment planning across different patient scenarios.

Multiscale treatment response prediction in advanced NSCLC enables spatially informed dose painting, yet prediction point estimates alone do not convey the uncertainty required for adaptive therapy decision support. We developed a multiscale conformal predict...

Patients receiving radiotherapy (RT) for liver cancer have limited liver function reserves, which increases risk of radiation-induced liver injury, but tools to evaluate functional response post-RT are lacking. We modeled liver function changes on 99mTc sulfu...

ESTRO–AAPM Joint Program in Trial Design for Medical Physicists: Moving Past QA into Clinical Trials for Oncologic Outcomes and Biomarker Applications puts physicists at the center of evidence generation. This panel‑workshop reframes the physicist’s role from...

The recent clinical trials to evaluate novel dose and fractionations, including for non-malignant conditions, may change the clinical role and scope of RT practice. Clinical trials are ongoing to evaluate the use of RT to treat non-malignant conditions such a...

Stereotactic arrhythmia radioablation (STAR), a non-invasive treatment option for refractory ventricular tachycardia (VT), faces challenges from combined respiratory and cardiac motion, necessitating large target margins or motion mitigation. Respiratory gati...

Focused on the "fringes" of Medical Physics - in line with AAPM strategic plan - expanding beyond the current boundaries of Medical Physics. Collecting non-traditional science that belongs/should belong to medical physics. Fun, stimulating, and thought-provok...

Accurate assessment of early radiotherapy response in tumors provides crucial guidance for optimizing radiotherapy protocols. We developed a 3D deep learning model termed Attention Med3D based on transfer learning and attention mechanisms for predicting mid-t...

Accurate identification of high-risk and low-risk tumor subregions enables radiographers to customize radiation dose distributions for biologically adaptive therapies. This study proposes a 3DUNET-GMM model that integrates 3D-UNet feature extracting with Gaus...

Accurate prediction of tumor response during chemoradiotherapy is essential for treatment optimization but remains challenging. We developed a deep learning model based on a Dual Path Network (DPN), which is a hybrid architecture combining elements of ResNet...