Moderate hypofractionation for prostate cancer: A user's guide

Pryor, David; Turner, Sandra; Tai, Keen Hun; Tang, Colin; Sasso, Giuseppe; Dreosti, Marcus; Woo, Henry H.; Wilton, Lee; Martin, Jarad

doi:10.1111/1754-9485.12703

Cited by 13 publications

(14 citation statements)

References 48 publications

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“…To facilitate plan comparisons for each patient, optimized dose distributions were superimposed onto the clinical bladder, and rectum contours and clinically relevant dose-volume metrics were calculated. 26 For rectum, the highest doses received by at least 15% (D 15% ), 20% (D 20% ), 35% (D 35% ), and 50% (D 50% ) were recorded in Gy. For bladder, the highest doses received by at least 5% (D 5% ), 30% (D 30% ), 40% (D 40% ), and 50% (D 50% ) were recorded in Gy.…”

Section: Dosimetric Comparison Of Ro-edited Contoursmentioning

confidence: 91%

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

Zabel

Conway

Gladwish

et al. 2021

Practical Radiation Oncology

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Auto-contouring may reduce workload, interobserver variation, and time associated with manual contouring of organs at risk. Manual contouring remains the standard due in part to uncertainty around the time and workload savings after accounting for the review and editing of auto-contours. This preliminary study compares a standard manual contouring workflow with 2 auto-contouring workflows (atlas and deep learning) for contouring the bladder and rectum in patients with prostate cancer. Methods and Materials: Three contouring workflows were defined based on the initial contour-generation method including manual (MAN), atlas-based auto-contour (ATLAS), and deep-learning auto-contour (DEEP). For each workflow, initial contour generation was retrospectively performed on 15 patients with prostate cancer. Then, radiation oncologists (ROs) edited each contour while blinded to the manner in which the initial contour was generated. Workflows were compared by time (both in initial contour generation and in RO editing), contour similarity, and dosimetric evaluation. Results: Mean durations for initial contour generation were 10.9 min, 1.4 min, and 1.2 min for MAN, DEEP, and ATLAS, respectively. Initial DEEP contours were more geometrically similar to initial MAN contours. Mean durations of the RO editing steps for MAN, DEEP, and ATLAS contours were 4.1 min, 4.7 min, and 10.2 min, respectively. The geometric extent of RO edits was consistently larger for ATLAS contours compared with MAN and DEEP. No differences in clinically relevant dose-volume metrics were observed between workflows. Conclusion: Auto-contouring software affords time savings for initial contour generation; however, it is important to also quantify workload changes at the RO editing step. Using deep-learning auto-contouring for bladder and rectum contour generation reduced contouring time without negatively affecting RO editing times, contour geometry, or clinically relevant doseevolume metrics.

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Section: Dosimetric Comparison Of Ro-edited Contoursmentioning

confidence: 91%

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

Zabel

Conway

Gladwish

et al. 2021

Practical Radiation Oncology

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“…These constraints were taken from the literature. [15][16][17][18][19][20] TABLE II. The model parameters used for estimating the organ equivalent dose and the excess absolute risk for developing secondary bladder or rectal malignancies as derived from the literature.…”

Section: D Second Cancer Risk Assessmentsmentioning

confidence: 99%

Secondary bladder and rectal cancer risk estimates following standard fractionated and moderately hypofractionated VMAT for prostate carcinoma

2020

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Purpose: To estimate the risk for bladder and rectal cancer induction due to standard fractionated (SF) and moderately hypofractionated (HF) volumetric modulated arc therapy (VMAT) for prostate carcinoma. Methods: Twelve patients with low or intermediate-risk of prostate cancer referred for external-beam radiotherapy were included in this study. Three computed tomography-based VMAT plans were created for each study participant. The first plan was generated by assuming patient's irradiation with SF-VMAT (78 Gy in 39 fractions). The second and third plans were created on the basis of two different HF schedules (HF-VMAT 1 : 70 Gy in 30 fractions, HF:VMAT 2 : 60 Gy in 20 fractions). Data from differential dose-volume histograms obtained by the above treatment plans were employed to calculate the organ equivalent dose (OED) of the bladder and rectum with the aid of a nonlinear model accounting for fractionation and proliferation effects. The calculated OED values were used to estimate the average lifetime attributable risk (LAR av ) for the appearance of radiotherapy-induced secondary bladder and rectal malignancies. The lifetime risk of radiation carcinogenesis was compared with the respective organ-, and age-dependent lifetime intrinsic risk (LIR) of cancer development for unexposed males. Results: The average OED of the rectum from SF-VMAT, HF-VMAT 1 and HF-VMAT 2 for prostate cancer was 972.0, 900.2, and 815.7 cGy, respectively. The corresponding values for bladder were 73.4, 72.3, and 71.0 cGy. The LAR av for rectal cancer induction varied from 0.06% to 0.4% by the fractionation schedule used for irradiation and by the age of the patient at the time of treatment. The corresponding risk range related to the development of secondary bladder malignancies was 0.06-0.33%. The SF-VMAT, HF-VMAT 1 and HF-VMAT 2 led to an increase of the lifetime rectal cancer risk with respect to LIR by 2.2-9.8%, 2.0-9.1% and 1.8-8.2%, respectively, depending upon the patient's age. The corresponding elevation for bladder cancer induction was up to 8.0%, 7.9% and 7.7%. Conclusions: The use of VMAT for prostate carcinoma leads to a noteworthy increase of the lifetime risk for bladder and rectal cancer induction compared to that of unexposed people irrespective of the patient's age at the time of treatment and the applied fractionation scheme. The cancer risk data presented in this study may be taken into account by radiation oncologists and medical physicists in the selection of the optimal radiation therapy plan.

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“…First, despite our earlier studies on the a/b for rectal toxicity [10], we did not attempt to express the dose at 2 Gy fraction but we reported nominal doses. Since the 20-fraction schedule is the one with the most robust evidence base to date [2,3,6], and is currently recommended by treatment guidelines, systematic reviews and cooperative groups [27,30,31] this approach would help to implement dose volume objectives without the inherent approximations and uncertainties of the linear quadratic transformation [32,33]. Second, this is the largest single-Institution series on MHRT which allowed us to analyze dosimetric predictors of LRC after correcting for clinical potential confounders in order to refine/validate dose volume objectives [29,34].…”

Section: Discussionmentioning

confidence: 99%

Refinement & validation of rectal wall dose volume objectives for prostate hypofractionation in 20 fractions

Sanguineti

Faiella

Farneti

et al. 2020

Clinical and Translational Radiation Oncology

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a b s t r a c tBackground and purpose: Dose-volume objectives for the rectum have been proposed to limit long term toxicity after moderately hypofractionated radiotherapy (MHRT) for localized prostate cancer. The purpose of the present study is to validate and possibly refine dose volume objective for the rectal wall after 20-fraction MHRT. Materials and methods: All patients treated by 20-fraction MHRT at a single Institution were identified and relative rectal wall (%RW) DVH retrieved. The endpoint of the study is the development of grade 2 + late rectal bleeding (LRB) according to a modified RTOG scale. Clinical and dosimetric predictors of LRB were investigated at both uni-and multi-variable analysis. Results: 293 patients were identified and analyzed. Of them, 35 (12%) developed the endpoint. At univariable analysis, antithrombotic drug usage (yes vs no), technique (3DCRT vs IMRT/VMAT) and several %RW DVH cut-points were significantly correlated with LRB. However, within patients treated by 3DCRT (N = 106), a bi-variable model including anti-thrombotic drug usage and selected %RW dose/volume metrics failed to identify independent dosimetric predictors of LRB. Conversely, within patients treated with intensity modulation (N = 187), the same model showed a progressively higher impact of the percent of RW receiving doses above 40 Gy. Based on this model, we were able to confirm (V32), refine (V60) and identify a novel (V50) cut-point for the %RW. Conclusion: We recommend the following dose volume objectives for the %RW in order to minimize the risk of LRB after 20-fraction MHRT: V32 50%; V50 25.8% and V60 10%.

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Moderate hypofractionation for prostate cancer: A user's guide

Cited by 13 publications

References 48 publications

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

Secondary bladder and rectal cancer risk estimates following standard fractionated and moderately hypofractionated VMAT for prostate carcinoma

Refinement & validation of rectal wall dose volume objectives for prostate hypofractionation in 20 fractions

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