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Development and Validation of a Comprehensive Multivariate Dosimetric Model for Predicting Late Genitourinary Toxicity Following Prostate Cancer Stereotactic Body Radiotherapy.

ABSTRACT: Purpose: Dosimetric predictors of toxicity after Stereotactic Body Radiation Therapy (SBRT) are not well-established. We sought to develop a multivariate model that predicts Common Terminology Criteria for Adverse Events (CTCAE) late grade 2 or greater genitourinary (GU) toxicity by interrogating the entire dose-volume histogram (DVH) from a large cohort of prostate cancer patients treated with SBRT on prospective trials. Methods: Three hundred and thirty-nine patients with late CTCAE toxicity data treated with prostate SBRT were identified and analyzed. All patients received 40 Gy in five fractions, every other day, using volumetric modulated arc therapy. For each patient, we examined 910 candidate dosimetric features including maximum dose, volumes of each organ [CTV, organs at risk (OARs)], V100%, and other granular volumetric/dosimetric indices at varying volumetric/dosimetric values from the entire DVH as well as ADT use to model and predict toxicity from SBRT. Training and validation subsets were generated with 90 and 10% of the patients in our cohort, respectively. Predictive accuracy was assessed by calculating the area under the receiver operating curve (AROC). Univariate analysis with student t-test was first performed on each candidate DVH feature. We subsequently performed advanced machine-learning multivariate analyses including classification and regression tree (CART), random forest, boosted tree, and multilayer neural network. Results: Median follow-up time was 32.3 months (range 3-98.9 months). Late grade ?2 GU toxicity occurred in 20.1% of patients in our series. No single dosimetric parameter had an AROC for predicting late grade ?2 GU toxicity on univariate analysis that exceeded 0.599. Optimized CART modestly improved prediction accuracy, with an AROC of 0.601, whereas other machine learning approaches did not improve upon univariate analyses. Conclusions: CART-based machine learning multivariate analyses drawing from 910 dosimetric features and ADT use modestly improves upon clinical prediction of late GU toxicity alone, yielding an AROC of 0.601. Biologic predictors may enhance predictive models for identifying patients at risk for late toxicity after SBRT.

SUBMITTER: Valle LF

PROVIDER: S-EPMC7251156 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

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Development and Validation of a Comprehensive Multivariate Dosimetric Model for Predicting Late Genitourinary Toxicity Following Prostate Cancer Stereotactic Body Radiotherapy.

Valle Luca F LF Ruan Dan D Dang Audrey A Levin-Epstein Rebecca G RG Patel Ankur P AP Weidhaas Joanne B JB Nickols Nicholas G NG Lee Percy P PP Low Daniel A DA Qi X Sharon XS King Christopher R CR Steinberg Michael L ML Kupelian Patrick A PA Cao Minsong M Kishan Amar U AU

Frontiers in oncology 20200520

<b>Purpose:</b> Dosimetric predictors of toxicity after Stereotactic Body Radiation Therapy (SBRT) are not well-established. We sought to develop a multivariate model that predicts Common Terminology Criteria for Adverse Events (CTCAE) late grade 2 or greater genitourinary (GU) toxicity by interrogating the entire dose-volume histogram (DVH) from a large cohort of prostate cancer patients treated with SBRT on prospective trials. <b>Methods:</b> Three hundred and thirty-nine patients with late CT ...[more]

PMID: 32509582

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Project description:BackgroundProstate cancer rates have been steadily increasing in recent years. As high-precision radiation therapy methods, stereotactic body radiation therapy (SBRT) and carbon-ion radiation therapy (CIRT) have unique advantages. Analyzing the dosimetric differences between SBRT and CIRT in the treatment of localized prostate cancer can help provide patients with more accurate, individualized treatment plans.MethodsWe selected computed tomography positioning images and the contours of target volumes of 16 patients with localized prostate cancer who received radiotherapy. We delineated the organs at risk (OARs) on the CyberKnife (CK) treatment planning system (TPS) MultiPlan4.0, which were imported into the CIRT uniform scanning TPS HIMM-1 ci-Plan. Two treatment plans, SBRT and CIRT, were designed for the same patient, and we used SPSS 22.0 for the statistical analysis of data.ResultsBoth SBRT and CIRT plans met the prescribed dose requirements. In terms of target volume exposure dose, D2 (P<0.001), D5 (P<0.001), D50 (P<0.001), D90 (P=0.029), D95 (P<0.001), D98 (P<0.001), and Dmean (P<0.001) under SBRT were significantly higher than those under CIRT; the conformity index (CI) under SBRT was significantly better than that under CIRT (P<0.001); the target volume coverage rate (V95%) and dose homogeneity index (HI) under CIRT were significantly better than those under SBRT (P<0.001). In terms of OAR exposure dosage, the Dmax of the bladder and rectum under SBRT was significantly lower than that under CIRT (P<0.001), but Dmean was in the other direction; the exposure dose of the intestinal tract under CIRT was significantly lower than that under SBRT (P<0.05); Dmax of the femoral head under CIRT was significantly lower than that under SBRT (P<0.05), and there was no statistical difference between them at other doses.ConclusionsIn this study, we found that when CIRT was used for treating localized prostate cancer, the dose distribution in target volume was more homogeneous and the coverage rate was higher; the average dose of OARs was lower. SBRT had a better CI and higher dose in target volume; the dose hotspot was lower in OARs. It is important to comprehensively consider the dose relationship between local tumor and surrounding tissues when selecting treatment plans.

Project description:BackgroundMetal artifacts due to spinal implants may affect the accuracy of dose calculation for radiotherapy. However, the dosimetric impact of metal artifact reduction (MAR) for spinal implants in stereotactic body radiotherapy (SBRT) plans has not been well studied. The objective of this study was to evaluate the dosimetric impact of MAR in spinal SBRT planning with three clinically common dose calculation algorithms.MethodsGammex phantom and 10 patients' computed tomography (CT) images were studied to investigate the effects of titanium implants. A commercial orthopedic MAR algorithm was employed to reduce artifacts. Dose calculations for SBRT were conducted on both artifact-corrected and uncorrected images using three commercial algorithms [analytical anisotropic algorithm (AAA), Acuros XB (AXB), and Monte Carlo (MC)]. Dose discrepancies between artifact-corrected and uncorrected cases were appraised using a dose-volume histogram (DVH) and 3-dimensional (3D) gamma analysis with different distance to agreement (DTA) and dose difference criteria. The gamma agreement index (GAI) was denoted as G(∆D, DTA). Statistical analysis of t-test was utilized to evaluate the dose differences of different algorithms.ResultsThe phantom study demonstrated that titanium metal artifacts can be effectively reduced. The patient cases study showed that dose differences between the artifact-corrected and uncorrected datasets were small evaluated by gamma index and DVH. Gamma analysis found that even the strict criterion local G(1,1) had average values ≥93.9% for the three algorithms. For all DVH metrics, average differences did not exceed 0.7% in planning target volume (PTV) and 2.1% in planning risk volume of spinal cord (PRV-SC). Statistical analysis showed that the observed dose differences of MC method were significantly larger than those of AAA (P<0.01 for D98% of PTV and P<0.001 for D0.1cc of spinal cord) and AXB methods (P<0.001 for D98% and P<0.0001 for D0.1cc).ConclusionsDosimetric impact of artifacts caused by titanium implants is not significant in spinal SBRT planning, which indicates that dose calculation algorithms might not be very sensitive to CT number variation caused by titanium inserts.

Project description:Purpose/objectivesRetrospective analysis suggests that dose escalation to a biologically effective dose of more than 70 Gy may improve overall survival in patients with pancreatic ductal adenocarcinoma (PDAC), but such treatments in practice are limited by proximity of organs at risk (OARs). We hypothesized that CT-guided online adaptive radiotherapy (OART) can account for interfraction movement of OARs and allow for safe delivery of ablative doses.Materials/methodsThis is a single institution retrospective analysis of patients with PDAC treated with OART on the Ethos platform (Varian Medical Systems, a Siemens Healthineers Company, Palo Alto). All patients were treated to 40 Gy in 5 fractions. PTV overlapping with a 5 mm planning risk volume expansion on the stomach, duodenum and bowel received 25 Gy. Initial treatment plans were created conventionally. For each fraction, PTV and OAR volumes were recontoured with AI assistance after initial cone beam CT (CBCT). The adapted plan was calculated, underwent QA, and then compared to the scheduled plan. A second CBCT was obtained prior to delivery of the selected plan. Total treatment time (first CBCT to end of radiation delivery) and active physician time (first to second CBCT) were recorded. PTV_4000 V95 %, PTV_2500 V9 5%, and D0.03 cc to stomach, duodenum and bowel were reported for scheduled (S) and adapted (A) plans. CTCAEv5.0 toxicities were recorded. Statistical analysis was performed using a two-sided T test and α of 0.05.Results21 patients with unresectable or locally-recurrent PDAC were analyzed, with a total of 105 fractions. Average total time was 29 min and 16 s (16:36-49:40) and average active physician time was 19:41 min (9:25-39:34). All fractions were treated with adapted plans. 97 % of adapted plans met PTV_4000 V95.0 % >95.0 % coverage goal and 100 % of adapted plans met OAR dose constraints. Median follow up was 6.6 months. Only 1 patient experienced acute grade 3+ toxicity directly attributable to radiation. Only 1 patient experienced late grade 3+ toxicity directly attributable to radiation.ConclusionsDaily CT-based OART was associated with significantly reduced dose OARs while achieving superior PTV coverage. Given the relatively quick total treatment time, radiation delivery was generally well tolerated and easily incorporated into the clinic workflow. Our initial clinical experience demonstrates OART allows for safe dose escalation in the treatment of PDAC.

Dataset Information

Development and Validation of a Comprehensive Multivariate Dosimetric Model for Predicting Late Genitourinary Toxicity Following Prostate Cancer Stereotactic Body Radiotherapy.

Publications

Development and Validation of a Comprehensive Multivariate Dosimetric Model for Predicting Late Genitourinary Toxicity Following Prostate Cancer Stereotactic Body Radiotherapy.

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