Knowledge-based automatic optimization of adaptive early-regression-guided VMAT for rectal cancer

Published on Jan 23, 2020in Physica Medica2.485
· DOI :10.1016/J.EJMP.2020.01.016
Roberta Castriconi6
Estimated H-index: 6
Claudio Fiorino54
Estimated H-index: 54
+ 4 AuthorsRiccardo Calandrino32
Estimated H-index: 32
Abstract Purpose To implement a knowledge-based (KB) optimization strategy to our adaptive (ART) early-regression guided boosting technique in neo-adjuvant radio-chemotherapy for rectal cancer. Material and methods The protocol consists of a first phase delivering 27.6 Gy to tumor/lymph-nodes (2.3 Gy/fr-PTV1), followed by the ART phase concomitantly delivering 18.6 Gy (3.1 Gy/fr) and 13.8 Gy (2.3 Gy/fr) to the residual tumor (PTVART) and to PTV1 respectively. PTVART is obtained by expanding the residual GTV, as visible on MRI at fraction 9. Forty plans were used to generate a KB-model for the first phase using the RapidPlan tool. Instead of building a new model, a robust strategy scaling the KB-model to the ART phase was applied. Both internal and external validation were performed for both phases: all automatic plans (RP) were compared in terms of OARs/PTVs parameters against the original plans (RA). Results The resulting automatic plans were generally better than or equivalent to clinical plans. Of note, V30Gy and V40Gy were significantly improved in RP plans for bladder and bowel; gEUD analysis showed improvement for KB-modality for all OARs, up to 3 Gy for the bowel. Conclusions The KB-model generated for the first phase was robust and it was also efficiently adapted to the ART phase. The performance of automatically generated plans were slightly better than the corresponding manual plans for both phases.
📖 Papers frequently viewed together
48 Citations
13 Citations
6 Citations
Abstract Background and purpose An early tumor regression index (ERI TCP ) was previously introduced and found to predict pathological response after neo-adjuvant radio-chemotherapy of rectal cancer. ERI TCP was tested as a potential biomarker in predicting long-term disease-free survival. Materials and methods Data of 65 patients treated with an early regression-guided adaptive boosting technique (ART) were available. Overall, loco-regional relapse-free and distant metastasis-free survival (OS,...
6 CitationsSource
#1Kevin L. Moore (UCSD: University of California, San Diego)H-Index: 44
The “treatment planning” component of managing a radiotherapy patient currently consumes hours, even days, of human effort. The time and workforce demands of the current planning paradigm can expose patients to delays and potentially substandard treatments, all while standing as seemingly insurmountable roadblocks to adaptive radiotherapy. Automating the treatment planning process is not a new idea, but recent advances have shown that automated planning might finally be turning the corner from n...
23 CitationsSource
#1Tiziana RancatiH-Index: 27
#2C. FiorinoH-Index: 7
The treatment of a patient with radiation therapy is planned to find the optimal way to treat a tumour while minimizing the dose received by the surrounding normal tissues. In order to better exploit the possibilities of this process, the availability of accurate and quantitative knowledge of the peculiar responses of the different tissues is of paramount importance. This book provides an invaluable tutorial for radiation oncologists, medical physicists, and dosimetrists involved in the planning...
5 CitationsSource
#1Yaorong Ge (UNCC: University of North Carolina at Charlotte)H-Index: 21
#2Q. Jackie Wu (Duke University)H-Index: 25
PURPOSE: Intensity-Modulated Radiation Therapy (IMRT), including its variations (including IMRT, Volumetric Arc Therapy (VMAT), and Tomotherapy), is a widely used and critically important technology for cancer treatment. It is a knowledge-intensive technology due not only to its own technical complexity, but also to the inherently conflicting nature of maximizing tumor control while minimizing normal organ damage. As IMRT experience and especially the carefully designed clinical plan data are ac...
56 CitationsSource
#1Roberta CastriconiH-Index: 6
#2Claudio FiorinoH-Index: 54
Last. Giovanni Mauro CattaneoH-Index: 29
view all 7 authors...
Abstract Purpose To develop and apply a stepping approach for the validation of Knowledge-based (KB) models for planning optimization: the method was applied to the case of concomitant irradiation of pelvic nodes and prostate + seminal−vesicles bed irradiation in post-prostatectomy patients. Methods The clinical VMAT plans of 52 patients optimized by two reference planners were selected to generate a KB-model (RapidPlan, v.13.5 Varian). A stepping-validation approach was followed by comparing KB...
14 CitationsSource
#1Elisabetta Cagni (Cardiff University)H-Index: 12
#2Andrea BottiH-Index: 10
Last. Ben J.M. Heijmen (EUR: Erasmus University Rotterdam)H-Index: 64
view all 6 authors...
Abstract Purpose Treatment plans manually generated in clinical routine may suffer from variations and inconsistencies in quality. Using such plans for validating a DVH prediction algorithm might obscure its intrinsic prediction accuracy. In this study we used a recently published large database of Pareto-optimal prostate cancer plans to assess the prediction accuracy of a commercial knowledge-based DVH prediction algorithm, RapidPlan. The database plans were consistently generated with automate...
11 CitationsSource
#1A. ScaggionH-Index: 9
#2M. FusellaH-Index: 7
Last. Marta PaiuscoH-Index: 12
view all 8 authors...
Abstract Purpose This study measured to which extent RapidPlan can drive a reduction of the human-caused variability in prostate cancer treatment planning. Methods Seventy clinical prostate plans were used to train a RapidPlan model. Seven planners, with different levels of planning experience, were asked to plan a VMAT treatment for fifteen prostate cancer patients with and without RapidPlan assistance. The plans were compared on the basis of target coverage, conformance and OAR sparing. Inter-...
25 CitationsSource
#1Claudio FiorinoH-Index: 54
#1C. FiorinoH-Index: 7
Last. Nadia Di MuzioH-Index: 31
view all 16 authors...
Abstract Purpose Introducing a radiobiological index based on early tumor regression during neo-adjuvant radio-chemotherapy (RCT, including oxaliplatin) of rectal adenocarcinoma and testing its discriminative power in predicting the tumor response. Methods Seventy-four patients were treated with Helical Tomotherapy following an adaptive (ART) protocol (41.4 Gy/18 fr, 2.3 Gy/fr) delivering a simultaneous integrated boost on the residual tumor in the last 6 fractions up to 45.6 Gy. T2-weighted MRI...
12 CitationsSource
#1Jorge E. Alpuche Aviles (UM: University of Manitoba)H-Index: 4
#2Maria Isabel Cordero Marcos (Varian Medical Systems)H-Index: 1
Last. Esa Kuusela (Varian Medical Systems)H-Index: 2
view all 6 authors...
: Knowledge-based planning (KBP) can be used to estimate dose-volume histograms (DVHs) of organs at risk (OAR) using models. The task of model creation, however, can result in estimates with differing accuracy; particularly when outlier plans are not properly addressed. This work used RapidPlan™ to create models for the prostate and head and neck intended for large-scale distribution. Potential outlier plans were identified by means of regression analysis scatter plots, Cook's distance, coeffici...
14 CitationsSource
#1Yoshihiro UedaH-Index: 12
#2Junichi Fukunaga (Kyushu University)H-Index: 4
Last. Hajime Monzen (Kindai University)H-Index: 13
view all 6 authors...
The aim of this study was to evaluate the performance of a commercial knowledge-based planning system, in volumetric modulated arc therapy for prostate cancer at multiple radiation therapy departments. In each institute, > 20 cases were assessed. For the knowledge-based planning, the estimated dose (ED) based on geometric and dosimetric information of plans was generated in the model. Lower and upper limits of estimated dose were saved as dose volume histograms for each organ at risk. To verify ...
30 CitationsSource
Cited By9
#1Roberta CastriconiH-Index: 6
Last. Lucia PernaH-Index: 17
view all 0 authors...
#1Hideaki Hirashima (Kyoto University)H-Index: 6
#2Mitsuhiro Nakamura (Kyoto University)H-Index: 20
Last. Takashi Mizowaki (Kyoto University)H-Index: 32
view all 10 authors...
PURPOSE This study aimed to assess dosimetric indices of RapidPlan model-based plans for different energies (6, 8, 10, and 15 MV; 6- and 10-MV flattening filter-free), multileaf collimator (MLC) types (Millennium 120, High Definition 120, dual-layer MLC), and disease sites (head and neck, pancreatic, and rectal cancer) and compare these parameters with those of clinical plans. METHODS RapidPlan models in the Eclipse version 15.6 were used with the data of 28, 42, and 20 patients with head and ne...
#1Elisabetta CagniH-Index: 12
#2Andrea BottiH-Index: 10
Last. Emiliano Spezi (Cardiff University)H-Index: 28
view all 5 authors...
This study aimed to investigate if a commercial, knowledge-based tool for radiotherapy planning could be used to estimate potential organs at risk (OARs), which would spare the re-planning strategy for adaptive radiotherapy (ART). Sixty-four head and neck (HN) VMAT Pareto plans from our institute's database were used to train a knowledge-based planning (KBP) model. An evaluation set of 10 HN patients was randomly selected. For each patient in the evaluation set, the planning computed tomography ...
#1Davide CusumanoH-Index: 11
#2Luca BoldriniH-Index: 16
Last. Luca IndovinaH-Index: 9
view all 20 authors...
Abstract Over the last years, technological innovation in Radiotherapy (RT) led to the introduction of Magnetic Resonance-guided RT (MRgRT) systems. Due to the higher soft tissue contrast compared to on-board CT-based systems, MRgRT is expected to significantly improve the treatment in many situations. MRgRT systems may extend the management of inter- and intra-fraction anatomical changes, offering the possibility of online adaptation of the dose distribution according to daily patient anatomy a...
1 CitationsSource
#2Huikuan Gu (SYSU: Sun Yat-sen University)
Last. Zhen-Yu Qi (SYSU: Sun Yat-sen University)H-Index: 5
view all 6 authors...
BACKGROUND AND PURPOSE To explore whether a highly refined dose volume histograms (DVH) prediction model can improve the accuracy and reliability of knowledge-based volumetric modulated arc therapy (VMAT) planning for cervical cancer. METHODS AND MATERIALS The proposed model underwent repeated refining through progressive training until the training samples increased from initial 25 prior plans up to 100 cases. The estimated DVHs derived from the prediction models of different runs of training w...
Abstract Purpose To implement knowledge-based (KB) automatic planning for helical TomoTherapy (HTT). The focus of the first clinical implementation was the case of high-risk prostate cancer, including pelvic node irradiation. Methods and Materials One hundred two HTT clinical plans were selected to train a KB model using the RapidPlan tool incorporated in the Eclipse system (v13.6, Varian Inc). The individually optimized KB-based templates were converted into HTT-like templates and sent automati...
1 CitationsSource
#1Johanna Austrheim Hundvin (Haukeland University Hospital)H-Index: 1
#2Kristine Fjellanger (Haukeland University Hospital)H-Index: 1
Last. L.B. Hysing (University of Bergen)H-Index: 12
view all 8 authors...
BACKGROUND Manual volumetric modulated arc therapy (VMAT) treatment planning for high-risk prostate cancer receiving whole pelvic radiotherapy (WPRT) with four integrated dose levels is complex and time consuming. We have investigated if the radiotherapy planning process and plan quality can be improved using a well-tuned model developed through a commercial system for knowledge-based planning (KBP). MATERIAL AND METHODS Treatment plans from 69 patients treated for high-risk prostate cancer with...
2 CitationsSource
#1Jiang Hu (SYSU: Sun Yat-sen University)H-Index: 6
#2Boji Liu (SYSU: Sun Yat-sen University)H-Index: 1
Last. Zhen-Yu Qi (SYSU: Sun Yat-sen University)H-Index: 5
view all 9 authors...
Background and purpose:To validate the feasibility and efficiency of a fully automatic knowledge-based planning (KBP)method for nasopharyngeal carcinoma(NPC) cases, with special attention to the possible way that can improve the success rate of auto-planning. Methods and Materials: A knowledge-based dose volume histogram (DVH) prediction model was developed based on 99 formerly treated NPC patients, by means of which the optimization objectives and the corresponding priorities for intensity modu...
Abstract Background and purpose Radiotherapy centers frequently lack simple tools for periodic treatment plan verification and feedback on current plan quality. It is difficult to measure treatment quality over different years or during the planning process. Here, we implemented plan quality assurance (QA) by developing a database of dose-volume histogram (DVH) metrics and a prediction model. These tools were used to assess automatically optimized treatment plans for rectal cancer patients, base...
#1Pier Giorgio Esposito (UniSR: Vita-Salute San Raffaele University)H-Index: 1
#2Roberta Castriconi (UniSR: Vita-Salute San Raffaele University)
Last. C. Fiorino (UniSR: Vita-Salute San Raffaele University)H-Index: 7
view all 8 authors...
Abstract Purpose To test the performances of a volumetric arc technique named ViTAT (Virtual Tangential-fields Arc Therapy) mimicking tangential field irradiation for whole breast radiotherapy. Methods ViTAT plans consisted in 4 arcs whose starting/ending position were established based on gantry angle distribution of clinical plans for right and left-breast. The arcs were completely blocked excluding the first and last 20°. Different virtual bolus densities and thicknesses were preliminarily ev...