Treatment planning and outcomes effects of reducing the preferred mean esophagus dose for conventionally fractionated non-small cell lung cancer radiotherapy.

Based on an analysis of published literature, our department recently lowered the preferred mean esophagus dose (MED) constraint for conventionally fractionated (2 Gy/fraction in approximately 30 fractions) treatment of locally advanced non-small cell lung cancer (LA-NSCLC) with the goal of reducing the incidence of symptomatic acute esophagitis (AE). The goal of the change was to encourage treatment planners to achieve a MED close to 21 Gy while still permitting MED to go up to the previous guideline of 34 Gy in difficult cases. We compared all our suitable LA-NSCLC patients treated with plans from one year before through one year after the constraint change. The primary endpoint for this study was achievability of the new constraint by the planners; the secondary endpoint was reduction in symptomatic AE. Planners were able to achieve the new constraint in statistically significantly more cases during the year following its explicit implementation than in the year before (P = 0.0025). Furthermore, 38% of patients treated after the new constraint developed symptomatic AE during their treatment as opposed to 48% of the patients treated before. This is a clinically desirable endpoint although the observed difference was not statistically significant. A subsequent power calculation suggests that this is due to the relatively small number of patients in the study.

Spatial rectal dose/volume metrics predict patient-reported gastro-intestinal symptoms after radiotherapy for prostate cancer.

BACKGROUND: Gastro-intestinal (GI) toxicity after radiotherapy (RT) for prostate cancer reduces patient's quality of life. In this study, we explored associations between spatial rectal dose/volume metrics and patient-reported GI symptoms after RT for localized prostate cancer, and compared these with those of dose-surface/volume histogram (DSH/DVH) metrics. MATERIAL AND METHODS: Dose distributions and six GI symptoms (defecation urgency/emptying difficulties/fecal leakage, ≥Grade 2, median follow-up: 3.6 y) were extracted for 200 patients treated with image-guided RT in 2005-2007. Three hundred and nine metrics assessed from 2D rectal dose maps or DSHs/DVHs were subject to 50-times iterated five-fold cross-validated univariate and multivariate logistic regression analysis (UVA, MVA). Performance of the most frequently selected MVA models was evaluated by the area under the receiving-operating characteristics curve (AUC). RESULTS: The AUC increased for dose-map compared to DSH/DVH-based models (mean SD: 0.64 ± 0.03 vs. 0.61 ± 0.01), and significant relations were found for six versus four symptoms. Defecation urgency and faecal leakage were explained by high doses at the central/upper and central areas, respectively; while emptying difficulties were explained by longitudinal extensions of intermediate doses. CONCLUSIONS: Predictability of patient-reported GI toxicity increased using spatial metrics compared to DSH/DVH metrics. Novel associations were particularly identified for emptying difficulties using both approaches in which intermediate doses were emphasized.

Associations between volume changes and spatial dose metrics for the urinary bladder during local versus pelvic irradiation for prostate cancer.

BACKGROUND: Inter-fractional variation in urinary bladder volumes during the course of radiotherapy (RT) for prostate cancer causes deviations between planned and delivered doses. This study compared planned versus daily cone-beam CT (CBCT)-based spatial bladder dose distributions, for prostate cancer patients receiving local prostate treatment (local treatment) versus prostate including pelvic lymph node irradiation (pelvic treatment). MATERIAL AND METHODS: Twenty-seven patients (N = 15 local treatment; N = 12 pelvic treatment) were treated using daily image-guided RT (1.8 Gy@43-45 fx), adhering to a full bladder/empty rectum protocol. For each patient, 9-10 CBCTs were registered to the planning CT, using the clinically applied translations. The urinary bladder was manually segmented on each CBCT, 3 mm inner shells were generated, and semi and quadrant sectors were created using axial/coronal cuts. Planned and delivered DVH metrics were compared across patients and between the two groups of treatment (t-test, p < .05; Holm-Bonferroni correction). Associations between bladder volume variations and the dose-volume histograms (DVH) of the bladder and its sectors were evaluated (Spearman's rank correlation coefficient, rs). RESULTS: Bladder volumes varied considerably during RT (coefficient of variation: 16-58%). The population-averaged planned and delivered DVH metrics were not significantly different at any dose level. Larger treatment bladder volumes resulted in increased absolute volume of the posterior/inferior bladder sector receiving intermediate-high doses, in both groups. The superior bladder sector received less dose with larger bladder volumes for local treatments (rs ± SD: -0.47 ± 0.32), but larger doses for pelvic treatments (rs ± SD: 0.74 ± 0.24). CONCLUSIONS: Substantial bladder volume changes during the treatment course occurred even though patients were treated under a full bladder/daily image-guided protocol. Larger bladder volumes resulted in less bladder wall spared at the posterior-inferior sector, regardless the treatment received. Contrary, larger bladder volumes meant larger delivered doses to the superior bladder sector for pelvic RT but smaller doses for local treatments.

Radiation Dose to the Penile Structures and Patient-Reported Sexual Dysfunction in Long-Term Prostate Cancer Survivors.

AIM: The involvement of various penile structures in radiotherapy (RT)-induced sexual dysfunction among prostate cancer survivors remains unclear and domains beyond erectile dysfunction such as orgasm, and pain have typically not been considered. The purpose of this study was to investigate sexual dysfunction post-RT for localized prostate cancer and to examine whether radiation dose to different penile structures can explain these symptoms. METHODS: We investigated sexual dysfunction in two treated prostate cancer cohorts and in one non-pelvic-irradiated cohort, 328 sexually active men part of an unselected, population-based study conducted in 2008. The treated subjects were prescribed primary/salvage external-beam RT to 70 Gy@2.0 Gy/fraction. Absorbed RT doses (Dmean and Dmax ) of the corpora cavernosa (CC), the penile bulb (PB), and the total penile structure (CC + PB) were related to 13 patient-reported symptoms on sexual dysfunction by means of factor analysis (FA) and logistic regression. RESULTS: Three distinct symptom domains were identified across all cohorts: "erectile dysfunction" (ED, two to five symptoms), "orgasmic dysfunction" (OD, two to four symptoms), and "pain" (two to three symptoms). The strongest predictor for ED symptoms was CC + PB Dmax (P = 0.001-0.03), CC and PB Dmean predicted OD symptoms equally well (P = 0.03 and 0.02-0.05, respectively), and the strongest predictor for pain symptoms was CC + PB Dmean (P = 0.02-0.03). CONCLUSION: Sexual dysfunction following RT was separated into three main domains with symptoms related to erectile dysfunction, orgasmic dysfunction, and pain. Chances for intact sexual functionality may be increased if dose to the total penile structure can be restricted for these domains in the planning of RT .

An image-based method to quantify biomechanical properties of the rectum in radiotherapy of prostate cancer.

BACKGROUND: Gastrointestinal morbidity after radiotherapy (RT) for prostate cancer may be related to the biomechanical properties of the rectum. In this study we present a magnetic resonance imaging (MRI)-based method to quantitate the thickness and elasticity of the rectal wall in prostate cancer patients treated with RT. MATERIAL AND METHODS: Four patients previously treated with RT for prostate cancer underwent an MRI session with stepwise rectal bag deflation (from a maximum tolerable volume to 0 ml, in 50 ml steps), with a probe inserted inside the bag to monitor the internal rectal pressure. MRIs were acquired using Dixon sequences (4 mm axial slice thickness) at each deflation step. Rectal walls were defined from the recto-sigmoid junction to 3 cm above the anal canal as the space between the inner and outer wall surfaces. The wall thickness was determined and biomechanical properties (strain and stress) were calculated from the pressure measurements and the MRI-segmented rectal walls. RESULTS: The integral rectal pressure varied for the maximum tolerable volume (range 150-250 ml) across patients and ranged from 1.3 to 4.0 kPa (SD = 1.2 kPa). Wall thickness was found to vary between patients and also across different rectum segments, with a mean (SD) thickness for the different segments at the 50 ml distension volume of 1.8-4.0 (0.6) mm. Stress showed larger variation than strain, with mean (SD) values for the different segments ranging between 1.5 and 7.0 (1.5) kPa. CONCLUSION: We have developed a method to quantify biomechanical properties of the rectal wall. The resulting rectal wall thickness, strain and stress differed between patients, as well as across different rectal wall sections. These findings could provide guidance in future predictive outcome modelling in order to better understand the rectal dose-volume response relationship.

Relationships between dose to the gastro-intestinal tract and patient-reported symptom domains after radiotherapy for localized prostate cancer.

BACKGROUND: Gastrointestinal (GI) morbidity after radiotherapy (RT) for prostate cancer is typically addressed by studying specific single symptoms. The aim of this study was to explore the interplay between domains of patient- reported outcomes (PROs) on GI morbidity, and to what extent these are explained by RT dose to the GI tract. MATERIAL AND METHODS: The study included men from two Scandinavian studies (N = 211/277) who had undergone primary external beam radiotherapy (EBRT) for localized prostate cancer to 70-78 Gy (2 Gy/fraction). Factor analysis was applied to previously identified PRO-based symptom domains from two study-specific questionnaires. Number of questions: 43; median time to follow-up: 3.6-6.4 years) and dose-response outcome variables were defined from these domains. Dose/volume parameters of the anal sphincter (AS) or the rectum were tested as predictors for each outcome variable using logistic regression with 10-fold cross-validation. Performance was assessed using area under the receiver operating characteristic curve (Az) and model frequency. RESULTS: Outcome variables from Defecation urgency (number of symptoms: 2-3), Fecal leakage (4-6), Mucous (4), and Pain (3-6) were defined. In both cohorts, intermediate rectal doses predicted Defecation urgency (mean Az: 0.53-0.54; Frequency: 70-75%), and near minimum and low AS doses predicted Fecal leakage (mean Az: 0.63-0.67; Frequency: 83-99%). In one cohort, high AS doses predicted Mucous (mean Az: 0.54; Frequency: 96%), whereas in the other, low AS doses and intermediate rectal doses predicted Pain (mean Az: 0.69; Frequency: 28-82%). CONCLUSION: We have demonstrated that Defecation urgency, Fecal leakage, Mucous, and Pain following primary EBRT for localized prostate cancer primarily are predicted by intermediate rectal doses, low AS doses, high AS doses, or a combination of low AS and intermediate rectal doses, respectively. This suggests that there is a domain-specific dose-response for the GI tract. To reduce risk of GI morbidity, dose distributions of both the AS region and the rectum should, therefore, be considered when prescribing prostate cancer RT.

Evaluation of an application for intensity-based deformable image registration and dose accumulation in radiotherapy.

BACKGROUND: Methods to accurately accumulate doses in radiotherapy (RT) are important for tumour and normal tissues being influenced by geometric uncertainties. The purpose of this study was to investigate a pre-release deformable image registration (DIR)-based dose accumulation application, in the setting of prostate RT. MATERIAL AND METHODS: Initially accumulated bladder and prostate doses were assessed (based on 8-9 repeat CT scans/patient) for nine prostate cancer patients using an intensity-based DIR and dose accumulation algorithm as provided by the Dynamic Adaptive Radiation Therapy (DART) software. The accumulated bladder and prostate dose-volume histograms (DVHs) were compared on a range of parameters (paired Wilcoxon signed-rank test, 5% significance level) to DVHs derived using an in-house developed dose accumulation method based on biomechanical, contour-driven DIR (SurfaceRegistration). Finally, both these accumulated dose distributions were compared to the 'static' DVH, assessed from the planning CT. RESULTS: Over the population, doses accumulated with DART were overall lower than those from SurfaceRegistration (p < 0.05: D2%, gEUD and NTCP (bladder); Dmin (prostate)). The magnitude of these differences peaked for the bladder gEUD with a population median of 47 Gy for DART versus 57 Gy for SurfaceRegistration. Across the ten bladder dose/volume parameters investigated, the most pronounced individual differences were observed between the 'accumulated' DVHs and the 'static' DVHs, with deviations in mean dose up to 22 Gy. CONCLUSION: Substantial and significant differences were observed in the dose distributions between the two investigated DIR-based dose accumulation applications. The most pronounced individual differences were seen for the bladder and relative to the planned dose distribution, encouraging the use of repeat imaging data in RT planning and evaluation for this organ.

Artificial intelligence-based automated segmentation and radiotherapy dose mapping for thoracic normal tissues.

Background and purpose: Objective assessment of delivered radiotherapy (RT) to thoracic organs requires fast and accurate deformable dose mapping. The aim of this study was to implement and evaluate an artificial intelligence (AI) deformable image registration (DIR) and organ segmentation-based AI dose mapping (AIDA) applied to the esophagus and the heart. Materials and methods: AIDA metrics were calculated for 72 locally advanced non-small cell lung cancer patients treated with concurrent chemo-RT to 60 Gy in 2 Gy fractions in an automated pipeline. The pipeline steps were: (i) automated rigid alignment and cropping of planning CT to week 1 and week 2 cone-beam CT (CBCT) field-of-views, (ii) AI segmentation on CBCTs, and (iii) AI-DIR-based dose mapping to compute dose metrics. AIDA dose metrics were compared to the planned dose and manual contour dose mapping (manual DA). Results: AIDA required âˆ¼2 min/patient. Esophagus and heart segmentations were generated with a mean Dice similarity coefficient (DSC) of 0.80±0.15 and 0.94±0.05, a Hausdorff distance at 95th percentile (HD95) of 3.9±3.4 mm and 14.1±8.3 mm, respectively. AIDA heart dose was significantly lower than the planned heart dose (p = 0.04). Larger dose deviations (>=1Gy) were more frequently observed between AIDA and the planned dose (N = 26) than with manual DA (N = 6). Conclusions: Rapid estimation of RT dose to thoracic tissues from CBCT is feasible with AIDA. AIDA-derived metrics and segmentations were similar to manual DA, thus motivating the use of AIDA for RT applications.

A Phase II Study Evaluating the Effect of Intensity Modulated Postmastectomy Radiation Therapy on Implant Failure Rates in Breast Cancer Patients With Immediate, 2-Stage Implant Reconstruction With an MRI Imaging Correlative Substudy.

PURPOSE: Postmastectomy radiation therapy is a mainstay in the adjuvant treatment of node-positive breast cancer, but it poses risks for women with breast reconstruction. Multibeam intensity-modulated radiation therapy improves dose conformality and homogeneity, potentially reducing complications in breast cancer patients with implant-based reconstruction. To investigate this hypothesis, we conducted a single-arm phase 2 clinical trial of breast cancer patients who underwent mastectomy/axillary dissection and prosthesis-based reconstruction. METHODS AND MATERIALS: The primary endpoint was the rate of implant failure (IF) within 24 months of permanent implant placement, which would be considered an improvement over historical controls if below 16%. IF was defined as removal leading to a flat chest wall or replacement with another reconstruction. Patients were analyzed in 2 cohorts. Cohort 1 (RT-PI) received radiation therapy to the permanent implant. Cohort 2 (RT-TE) received radiation therapy to the TE. IF rates, adverse events, and quality of life were analyzed. Follow-up/postradiation therapy assessments were compared with the baseline/preradiation therapy assessments at 3 to 10 weeks after exchange surgery. A subgroup underwent serial magnetic resonance imaging (MRI) sessions to explore the association between MRI-detected changes and capsular contracture, a known adverse effect of radiation therapy. RESULTS: Between June 2014 and March 2017, 119 women were enrolled. Cohort 1 included 45 patients, and cohort 2 had 74 patients. Among 100 evaluable participants, 25 experienced IF during the study period. IF occurred in 8/42 (19%) and 17/58 (29%) in cohorts 1 and 2, respectively. Among the IFs, the majority were due to capsular contracture (13), infection (7), exposure (3), and other reasons (2). Morphologic shape features observed in longitudinal MRI images were associated with the development of Baker grade 3 to 4 contractures. CONCLUSIONS: The rate of IF in reconstructed breast cancer patients treated with intensity-modulated radiation therapy was similar to, but not improved over, that observed with conventional, 3-dimensional-conformal methods. MRI features show promise for predicting capsular contracture but require validation in larger studies.

An 18F-FDG PET/CT and Mean Lung Dose Model to Predict Early Radiation Pneumonitis in Stage III Non-Small Cell Lung Cancer Patients Treated with Chemoradiation and Immunotherapy.

Radiation pneumonitis (RP) that develops early (i.e., within 3 mo) (RPEarly) after completion of concurrent chemoradiation (cCRT) leads to treatment discontinuation and poorer survival for patients with stage III non-small cell lung cancer. Since no RPEarly risk model exists, we explored whether published RP models and pretreatment 18F-FDG PET/CT-derived features predict RPEarly Methods: One hundred sixty patients with stage III non-small cell lung cancer treated with cCRT and consolidative immunotherapy were analyzed for RPEarly Three published RP models that included the mean lung dose (MLD) and patient characteristics were examined. Pretreatment 18F-FDG PET/CT normal-lung SUV featured included the following: 10th percentile of SUV (SUVP10), 90th percentile of SUV (SUVP90), SUVmax, SUVmean, minimum SUV, and SD. Associations between models/features and RPEarly were assessed using area under the receiver-operating characteristic curve (AUC), P values, and the Hosmer-Lemeshow test (pHL). The cohort was randomly split, with similar RPEarly rates, into a 70%/30% derivation/internal validation subset. Results: Twenty (13%) patients developed RPEarly Predictors for RPEarly were MLD alone (AUC, 0.72; P = 0.02; pHL, 0.87), SUVP10, SUVP90, and SUVmean (AUC, 0.70-0.74; P = 0.003-0.006; pHL, 0.67-0.70). The combined MLD and SUVP90 model generalized in the validation subset and was deemed the final RPEarly model (RPEarly risk = 1/[1+e(- x )]; x = -6.08 + [0.17 × MLD] + [1.63 × SUVP90]). The final model refitted in the 160 patients indicated improvement over the published MLD-alone model (AUC, 0.77 vs. 0.72; P = 0.0001 vs. 0.02; pHL, 0.65 vs. 0.87). Conclusion: Patients at risk for RPEarly can be detected with high certainty by combining the normal lung's MLD and pretreatment 18F-FDG PET/CT SUVP90 This refined model can be used to identify patients at an elevated risk for premature immunotherapy discontinuation due to RPEarly and could allow for interventions to improve treatment outcomes.

Exploring published and novel pre-treatment CT and PET radiomics to stratify risk of progression among early-stage non-small cell lung cancer patients treated with stereotactic radiation.

PURPOSE: Disease progression after definitive stereotactic body radiation therapy (SBRT) for early-stage non-small cell lung cancer (NSCLC) occurs in 20-40% of patients. Here, we explored published and novel pre-treatment CT and PET radiomics features to identify patients at risk of progression. MATERIALS/METHODS: Published CT and PET features were identified and explored along with 15 other CT and PET features in 408 consecutively treated early-stage NSCLC patients having CT and PET < 3 months pre-SBRT (training/set-aside validation subsets: n = 286/122). Features were associated with progression-free survival (PFS) using bootstrapped Cox regression (Bonferroni-corrected univariate predictor: p ≤ 0.002) and only non-strongly correlated predictors were retained (|Rs|<0.70) in forward-stepwise multivariate analysis. RESULTS: Tumor diameter and SUVmax were the two most frequently reported features associated with progression/survival (in 6/20 and 10/20 identified studies). These two features and 12 of the 15 additional features (CT: 6; PET: 6) were candidate PFS predictors. A re-fitted model including diameter and SUVmax presented with the best performance (c-index: 0.78; log-rank p-value < 0.0001). A model built with the two best additional features (CTspiculation1 and SUVentropy) had a c-index of 0.75 (log-rank p-value < 0.0001). CONCLUSIONS: A re-fitted pre-treatment model using the two most frequently published features - tumor diameter and SUVmax - successfully stratified early-stage NSCLC patients by PFS after receiving SBRT.

Statistical simulations to estimate motion-inclusive dose-volume histograms for prediction of rectal morbidity following radiotherapy.

BACKGROUND AND PURPOSE: Internal organ motion over a course of radiotherapy (RT) leads to uncertainties in the actual delivered dose distributions. In studies predicting RT morbidity, the single estimate of the delivered dose provided by the treatment planning computed tomography (pCT) is typically assumed to be representative of the dose distribution throughout the course of RT. In this paper, a simple model for describing organ motion is introduced, and is associated to late rectal morbidity data, with the aim of improving morbidity prediction. MATERIAL AND METHODS: Organ motion was described by normally distributed translational motion, with its magnitude characterised by the standard deviation (SD) of this distribution. Simulations of both isotropic and anisotropic (anterior-posterior only) motion patterns were performed, as were random, systematic or combined random and systematic motion. The associations between late rectal morbidity and motion-inclusive delivered dose-volume histograms (dDVHs) were quantified using Spearman's rank correlation coefficient (Rs) in a series of 232 prostate cancer patients, and were compared to the associations obtained with the static/planned DVH (pDVH). RESULTS: For both isotropic and anisotropic motion, different associations with rectal morbidity were seen with the dDVHs relative to the pDVHs. The differences were most pronounced in the mid-dose region (40-60 Gy). The associations were dependent on the applied motion patterns, with the strongest association with morbidity obtained by applying random motion with an SD in the range 0.2-0.8 cm. CONCLUSION: In this study we have introduced a simple model for describing organ motion occurring during RT. Differing and, for some cases, stronger dose-volume dependencies were found between the motion-inclusive dose distributions and rectal morbidity as compared to the associations with the planned dose distributions. This indicates that rectal organ motion during RT influences the efforts to model the risk of morbidity using planning distributions alone.

Dose/volume-based evaluation of the accuracy of deformable image registration for the rectum and bladder.

BACKGROUND AND PURPOSE: Deformable image registration (DIR) is a key component of image-guided and adaptive strategies in radiotherapy. DIR based on image intensities alone is promising for online applications, but is challenged in regions with low intensity gradients. In this study we have investigated the performance of intensity- based DIR applied to contour propagation of the rectum and bladder, focusing on the consequences in terms of dose/volume parameters. MATERIAL AND METHODS: The rectum and bladder volumes were delineated in the planning computed tomography (pCT) scan and in 8-9 repeat CTs (Vmanual) for nine prostate cancer patients. The volumes from the pCT were propagated onto the repeat CTs using intensity-based DIR (Vprop). Dose/volume parameters for Vmanual and Vprop were derived by dose re-calculations following rigid registration on prostate fiducials. Linear regression was used to identify qualitative and quantitative volumetric measures of the DIR performance being associated with the differences in dose/volume parameters. RESULTS: The median differences in dose/volume parameters assessed for Vprop and Vmanual were modest, but individual differences ~7 Gy were seen. The observed differences in dose/volume parameters showed strong correlations to the measures of the DIR performance as well as with the volume variations, most pronounced for the rectum (R(2) = 0.63-0.85; p ≤ 0.05). CONCLUSION: Limitations in the intensity-based DIR algorithm resulted in large individual differences in dose/volume parameters between propagated and manually segmented volumes, which were correlated with volumetric measures of the DIR performance.

Predicting cancer relapse following lung stereotactic radiotherapy: an external validation study using real-world evidence.

Purpose: For patients receiving lung stereotactic ablative radiotherapy (SABR), evidence suggests that high peritumor density predicts an increased risk of microscopic disease (MDE) and local-regional failure, but only if there is low or heterogenous incidental dose surrounding the tumor (GTV). A data-mining method (Cox-per-radius) has been developed to investigate this dose-density interaction. We apply the method to predict local relapse (LR) and regional failure (RF) in patients with non-small cell lung cancer. Methods: 199 patients treated in a routine setting were collated from a single institution for training, and 76 patients from an external institution for validation. Three density metrics (mean, 90th percentile, standard deviation (SD)) were studied in 1mm annuli between 0.5cm inside and 2cm outside the GTV boundary. Dose SD and fraction of volume receiving less than 30Gy were studied in annuli 0.5-2cm outside the GTV to describe incidental MDE dosage. Heat-maps were created that correlate with changes in LR and RF rates due to the interaction between dose heterogeneity and density at each distance combination. Regions of significant improvement were studied in Cox proportional hazards models, and explored with and without re-fitting in external data. Correlations between the dose component of the interaction and common dose metrics were reported. Results: Local relapse occurred at a rate of 6.5% in the training cohort, and 18% in the validation cohort, which included larger and more centrally located tumors. High peritumor density in combination with high dose variability (0.5 - 1.6cm) predicts LR. No interactions predicted RF. The LR interaction improved the predictive ability compared to using clinical variables alone (optimism-adjusted C-index; 0.82 vs 0.76). Re-fitting model coefficients in external data confirmed the importance of this interaction (C-index; 0.86 vs 0.76). Dose variability in the 0.5-1.6 cm annular region strongly correlates with heterogeneity inside the target volume (SD; ρ = 0.53 training, ρ = 0.65 validation). Conclusion: In these real-world cohorts, the combination of relatively high peritumor density and high dose variability predicts increase in LR, but not RF, following lung SABR. This external validation justifies potential use of the model to increase low-dose CTV margins for high-risk patients.

Simulating the Potential of Model-Based Individualized Prescriptions for Ultracentral Lung Tumors.

Purpose: The use of stereotactic body radiation therapy for ultracentral lung tumors is limited by increased toxicity. We hypothesized that using published normal tissue complication probability (NTCP) and tumor control probability (TCP) models could improve the therapeutic ratio between tumor control and toxicity. A proposed model-based approach was applied to virtually replan early-stage non-small cell lung cancer (NSCLC) tumors. Methods and Materials: The analysis included 63 patients with ultracentral NSCLC tumors treated at our center between 2008 and 2017. Along with current clinical constraints, additional NTCP model-based criteria, including for grade 3+ radiation pneumonitis (RP3+) and grade 2+ esophagitis, were implemented using 4 different fractionation schemes. Scaled dose distributions resulting in the highest TCP without violating constraints were selected (optimal plan [Planopt]). Planopt predictions were compared with the observed local control and toxicities. Results: The observed 2-year local control rate was 72% (95% CI, 57%-88%) compared with 87% (range, 6%-93%) for Planopt TCP. Thirty-nine patients had Planopt with TCP > 80%, and 14 patients had Planopt TCP < 50%. The Planopt NTCPs for RP3+ were reduced by nearly half compared with patients' observed RP3+. The RP3+ NTCP was the most frequent reason for TCP of Planopt < 80% (14/24 patients), followed by grade 2+ esophagitis NTCP (5/24 patients) due to larger tumors (>40 cc vs ≤40 cc; P = .002) or a shorter tumor to esophagus distance (≥5 cm vs <5 cm; P < .001). Conclusions: We demonstrated the potential for model-based prescriptions to yield higher TCP while respecting NTCP for patients with ultracentral NSCLC. Individualizing treatments based on NTCP- and TCP-driven simulations halved the predicted relative to the observed rates of RP3+. Our simulations also identified patients whose TCP could not be improved without violating NTCP due to larger tumors or a near tumor to esophagus proximity.

Predicting the germline dependence of hematuria risk in prostate cancer radiotherapy patients.

BACKGROUND AND PURPOSE: Late radiation-induced hematuria can develop in prostate cancer patients undergoing radiotherapy and can negatively impact the quality-of-life of survivors. If a genetic component of risk could be modeled, this could potentially be the basis for modifying treatment for high-risk patients. We therefore investigated whether a previously developed machine learning-based modeling method using genome-wide common single nucleotide polymorphisms (SNPs) can stratify patients in terms of the risk of radiation-induced hematuria. MATERIALS AND METHODS: We applied a two-step machine learning algorithm that we previously developed for genome-wide association studies called pre-conditioned random forest regression (PRFR). PRFR includes a pre-conditioning step, producing adjusted outcomes, followed by random forest regression modeling. Data was from germline genome-wide SNPs for 668 prostate cancer patients treated with radiotherapy. The cohort was stratified only once, at the outset of the modeling process, into two groups: a training set (2/3 of samples) for modeling and a validation set (1/3 of samples). Post-modeling bioinformatics analysis was conducted to identify biological correlates plausibly associated with the risk of hematuria. RESULTS: The PRFR method achieved significantly better predictive performance compared to other alternative methods (all p < 0.05). The odds ratio between the high and low risk groups, each of which consisted of 1/3 of samples in the validation set, was 2.87 (p = 0.029), implying a clinically useful level of discrimination. Bioinformatics analysis identified six key proteins encoded by CTNND2, GSK3B, KCNQ2, NEDD4L, PRKAA1, and TXNL1 genes as well as four statistically significant biological process networks previously shown to be associated with the bladder and urinary tract. CONCLUSION: The risk of hematuria is significantly dependent on common genetic variants. The PRFR algorithm resulted in a stratification of prostate cancer patients at differential risk levels of post-radiotherapy hematuria. Bioinformatics analysis identified important biological processes involved in radiation-induced hematuria.

Lesion Dosimetry for [177Lu]Lu-PSMA-617 Radiopharmaceutical Therapy Combined with Stereotactic Body Radiotherapy in Patients with Oligometastatic Castration-Sensitive Prostate Cancer.

A single-institution prospective pilot clinical trial was performed to demonstrate the feasibility of combining [177Lu]Lu-PSMA-617 radiopharmaceutical therapy (RPT) with stereotactic body radiotherapy (SBRT) for the treatment of oligometastatic castration-sensitive prostate cancer. Methods: Six patients with 9 prostate-specific membrane antigen (PSMA)-positive oligometastases received 2 cycles of [177Lu]Lu-PSMA-617 RPT followed by SBRT. After the first intravenous infusion of [177Lu]Lu-PSMA-617 (7.46 ± 0.15 GBq), patients underwent SPECT/CT at 3.2 ± 0.5, 23.9 ± 0.4, and 87.4 ± 12.0 h. Voxel-based dosimetry was performed with calibration factors (11.7 counts per second/MBq) and recovery coefficients derived from in-house phantom experiments. Lesions were segmented on baseline PSMA PET/CT (50% SUVmax). After a second cycle of [177Lu]Lu-PSMA-617 (44 ± 3 d; 7.50 ± 0.10 GBq) and an interim PSMA PET/CT scan, SBRT (27 Gy in 3 fractions) was delivered to all PSMA-avid oligometastatic sites, followed by post-PSMA PET/CT. RPT and SBRT voxelwise dose maps were scaled (α/ß = 3 Gy; repair half-time, 1.5 h) to calculate the biologically effective dose (BED). Results: All patients completed the combination therapy without complications. No grade 3+ toxicities were noted. The median of the lesion SUVmax as measured on PSMA PET was 16.8 (interquartile range [IQR], 11.6) (baseline), 6.2 (IQR, 2.7) (interim), and 2.9 (IQR, 1.4) (post). PET-derived lesion volumes were 0.4-1.7 cm3 The median lesion-absorbed dose (AD) from the first cycle of [177Lu]Lu-PSMA-617 RPT (ADRPT) was 27.7 Gy (range, 8.3-58.2 Gy; corresponding to 3.7 Gy/GBq, range, 1.1-7.7 Gy/GBq), whereas the median lesion AD from SBRT was 28.1 Gy (range, 26.7-28.8 Gy). Spearman rank correlation, ρ, was 0.90 between the baseline lesion PET SUVmax and SPECT SUVmax (P = 0.005), 0.74 (P = 0.046) between the baseline PET SUVmax and the lesion ADRPT, and -0.81 (P = 0.022) between the lesion ADRPT and the percent change in PET SUVmax (baseline to interim). The median for the lesion BED from RPT and SBRT was 159 Gy (range, 124-219 Gy). ρ between the BED from RPT and SBRT and the percent change in PET SUVmax (baseline to post) was -0.88 (P = 0.007). Two cycles of [177Lu]Lu-PSMA-617 RPT contributed approximately 40% to the maximum BED from RPT and SBRT. Conclusion: Lesional dosimetry in patients with oligometastatic castration-sensitive prostate cancer undergoing [177Lu]Lu-PSMA-617 RPT followed by SBRT is feasible. Combined RPT and SBRT may provide an efficient method to maximize the delivery of meaningful doses to oligometastatic disease while addressing potential microscopic disease reservoirs and limiting the dose exposure to normal tissues.

External validation of pulmonary radiotherapy toxicity models for ultracentral lung tumors.

Introduction: Pulmonary toxicity is dose-limiting in stereotactic body radiation therapy (SBRT) for tumors that abut the proximal bronchial tree (PBT), esophagus, or other mediastinal structures. In this work we explored published models of pulmonary toxicity following SBRT for such ultracentral tumors in an independent cohort of patients. Methods: The PubMed database was searched for pulmonary toxicity models. Identified models were tested in a cohort of patients with ultracentral lung tumors treated between 2008 and 2017 at one large center (N = 88). This cohort included 60 % primary and 40 % metastatic tumors treated to 45 Gy in 5 fractions (fx), 50 Gy in 5 fx, 60 Gy in 8 fx, or 60 Gy in 15 fx prescribed as 100 % dose to PTV. Results: Seven published NTCP models from two studies were identified. The NTCP models utilized PBT max point dose (Dmax), D0.2 cm3, V65, V100, and V130. Within the independent cohort, the ≥ grade 3 toxicity and grade 5 toxicity rates were 18 % and 7-10 %, respectively, and the Dmax models best described pulmonary toxicity. The Dmax to 0.1 cm3 model was better calibrated and had increased steepness compared to the Dmax model. A re-planning study minimizing PBT 0.1 cm3 to below 122 Gy in EQD23 (for a 10 % ≥grade 3 pulmonary toxicity) was demonstrated to be completely feasible in 4/6 patients, and dose to PBT 0.1 cm3 was considerably lowered in all six patients. Conclusions: Pulmonary toxicity models were identified from two studies and explored within an independent ultracentral lung tumor cohort. A modified Dmax to 0.1 cm3 PBT model displayed the best performance. This model could be utilized as a starting point for rationally constructed airways constraints in ultracentral patients treated with SBRT or hypofractionation.

ROE (Radiotherapy Outcomes Estimator): An open-source tool for optimizing radiotherapy prescriptions.

BACKGROUND AND OBJECTIVES: Radiotherapy prescriptions currently derive from population-wide guidelines established through large clinical trials. We provide an open-source software tool for patient-specific prescription determination using personalized dose-response curves. METHODS: We developed ROE, a plugin to the Computational Environment for Radiotherapy Research to visualize predicted tumor control and normal tissue complication simultaneously, as a function of prescription dose. ROE can be used natively with MATLAB and is additionally made accessible in GNU Octave and Python, eliminating the need for commercial licenses. It provides a curated library of published and validated predictive models and incorporates clinical restrictions on normal tissue outcomes. ROE additionally provides batch-mode tools to evaluate and select among different fractionation schemes and analyze radiotherapy outcomes across patient cohorts. CONCLUSION: ROE is an open-source, GPL-copyrighted tool for interactive exploration of the dose-response relationship to aid in radiotherapy planning. We demonstrate its potential clinical relevance in (1) improving patient awareness by quantifying the risks and benefits of a given treatment protocol (2) assessing the potential for dose escalation across patient cohorts and (3) estimating accrual rates of new protocols.