Wilko F.A.R. Verbakel

Implementing a fully computed tomography-free online adaptive palliative radiotherapy: a one-visit workflow

Ashaya Tanisha Jaglal, Koen J. Nelissen, Angelique R.W. van Vlaenderen, Amy L. de la Fuente et autres

Background and purpose: Same-day palliative radiotherapy requires rapid workflows, but conventional computed tomography (CT)-based workflows cause delays and strain resources. Advances in cone-beam CT (CBCT) enabled accurate dose calculation and planning without a planning CT. This study evaluated the feasibility and efficiency …

nl, us (code pays fourni par la source)

Cone beam computed tomography-guided online adaptive radiation therapy: Clinical implementation in breast and axillary target volumes

Angelique R.W. van Vlaenderen, Judith G. Middelburg-van Rijn, Koen J. Nelissen, Karin Goudschaal et autres

Background and purpose: Daily differences in breast contour and arm positioning can result in frequent re-positioning and offline re-planning in postoperative breast radiotherapy (RT). Online adaptive radiotherapy (oART) enables daily adaptation of the radiotherapy treatment plan. This study aimed to implement oART …

nl, us (code pays fourni par la source)

COMBINING SPREAD-OUT BRAGG PEAK BEAMS WITH TRANSMISSION BEAMS TO SHORTEN HNC FIELD DELIVERY TIMES WHILE MAINTAINING PLAN QUALITY

Roni Hytönen, Reynald Vanderstraeten, Wilko F.A.R. Verbakel

be, nl (code pays fourni par la source)

Interpreting convolutional neural network explainability for head-and-neck cancer radiotherapy organ-at-risk segmentation

Victor I. J. Strijbis, Oliver J. Gurney‐Champion, Dragoș Grama, Ben J. Slotman et autres

Background Convolutional neural networks (CNNs) have emerged to reduce clinical resources and standardize auto-contouring of organs-at-risk (OARs). Although CNNs perform adequately for most patients, understanding when the CNN might fail is critical for effective and safe clinical deployment. However, the limitations of …

nl (code pays fourni par la source)

Interpreting convolutional neural network explainability for head-and-neck cancer radiotherapy organ-at-risk segmentation

Victor I. J. Strijbis, Oliver J. Gurney‐Champion, Dragoș Grama, Ben J. Slotman et autres

Abstract Background Convolutional neural networks (CNNs) have emerged to reduce clinical resources and standardize auto-contouring of organs-at-risk (OARs). Although CNNs perform adequately for most patients, understanding when the CNN might fail is critical for effective and safe clinical deployment. However, the limitations …

nl, ch (code pays fourni par la source)

Explainable AI for raising confidence in deep learning‐based tumor tracking models

Dragoș Grama, Max Dahele, Ben J. Slotman, Wilko F.A.R. Verbakel

Abstract Background Recently, tumor position monitoring using fluoroscopic images acquired during volumetric modulated arc therapy (VMAT) delivery has become available in a research setting. Accurate tracking during stereotactic body radiotherapy (SBRT), using VMAT, for lung tumors can help to ensure that the …

us, nl (code pays fourni par la source)

Hybrid proton planning combining spread-out Bragg peak beams with transmission beams to shorten field delivery times while maintaining plan quality

Roni Hytönen, Reynald Vanderstraeten, Wilko F.A.R. Verbakel

Background and purpose: Delivery times of Bragg-peak-based intensity-modulated proton therapy fields play an important role in patient throughput and comfort. Despite the associated exit dose, single-layer proton transmission beams benefit from sharper penumbras and are extremely fast to deliver. In this study, …

us, be, nl (code pays fourni par la source)

3572 Delivery of online adaptive palliative radiotherapy without pre-treatment CT imaging

Koen J. Nelissen, Angelique R.W. van Vlaenderen, Ashaya Tanisha Jaglal, Sandy Loopeker et autres

3455 Online adaptive radiotherapy in breast cancer patients – a prospective trial, BREAST-ART NL2021.

Angelique R.W. van Vlaenderen, Judith G. Middelburg-van Rijn, Koen J. Nelissen, Karin Goudschaal et autres

3091 Interpreting convolutional neural network explainability for head-and-neck cancer radiotherapy organ-atrisk segmentation

Victor I. J. Strijbis, Oliver J. Gurney‐Champion, Dragoș Grama, Wilko F.A.R. Verbakel

2503 3D markerless kV tracking of the spine using different kV-based techniques

Martijn J. Simons, D. Hoffmans, Anna M. Dinkla, Max Dahele et autres

Routine Use of Single Visit Online Adaptive Cone Beam Computed Tomography Guided Sim-Free Palliative Radiation Therapy

Koen J. Nelissen, Wilko F.A.R. Verbakel, Prof Ben J Slotman, J. Visser et autres

PURPOSE: Recent developments in cone beam computed tomography guided online adaptive radiation therapy (RT) enabled new fast workflows for palliative RT. Our previous work showed improvements in departmental logistics and patient satisfaction with the use of online adaptive RT compared with regular …

nl (code pays fourni par la source)