Lisanne V. van Dijk

Validation and Modification of a Prediction Model for Acute Cardiac Events in Patients With Breast Cancer Treated With Radiotherapy Based on Three-Dimensional Dose Distributions to Cardiac Substructures

Purpose A relationship between mean heart dose (MHD) and acute coronary event (ACE) rate was reported in a study of patients with breast cancer (BC). The main objective of our cohort study was to validate this relationship and investigate if other dose-distribution parameters are better predictors for ACEs than MHD. Patients and Methods The cohort consisted of 910 consecutive female patients with BC treated with radiotherapy (RT) after breast-conserving surgery. The primary end point was cumulative incidence of ACEs within 9 years of follow-up. Both MHD and various dose-distribution parameters of the cardiac substructures were collected from three-dimensional computed tomography planning data. Results The median MHD was 2.37 Gy (range, 0.51 to 15.25 Gy). The median follow-up time was 7.6 years (range, 0.1 to 10.1 years), during which 30 patients experienced an ACE. The cumulative incidence of ACE increased by 16.5% per Gy (95% CI, 0.6 to 35.0; P = .042). Analysis showed that the volume of the left ventricle receiving 5 Gy (LV-V5) was the most important prognostic dose-volume parameter. The most optimal multivariable normal tissue complication probability model for ACEs consisted of LV-V5, age, and weighted ACE risk score per patient (c-statistic, 0.83; 95% CI, 0.75 to 0.91). Conclusion A significant dose-effect relationship was found for ACEs within 9 years after RT. Using MHD, the relative increase per Gy was similar to that reported in the previous study. In addition, LV-V5 seemed to be a better predictor for ACEs than MHD. This study confirms the importance of reducing exposure of the heart to radiation to avoid excess risk of ACEs after radiotherapy for BC.

Normal tissue complication probability (NTCP) models for late rectal bleeding, stool frequency and fecal incontinence after radiotherapy in prostate cancer patients.

BACKGROUND AND PURPOSE Curative radiotherapy for prostate cancer may lead to anorectal side effects, including rectal bleeding, fecal incontinence, increased stool frequency and rectal pain. The main objective of this study was to develop multivariable NTCP models for these side effects. MATERIAL AND METHODS The study sample was composed of 262 patients with localized or locally advanced prostate cancer (stage T1-3). Anorectal toxicity was prospectively assessed using a standardized follow-up program. Different anatomical subregions within and around the anorectum were delineated. A LASSO logistic regression analysis was used to analyze dose volume effects on toxicity. RESULTS In the univariable analysis, rectal bleeding, increase in stool frequency and fecal incontinence were significantly associated with a large number of dosimetric parameters. The collinearity between these predictors was high (VIF>5). In the multivariable model, rectal bleeding was associated with the anorectum (V70) and anticoagulant use, fecal incontinence was associated with the external sphincter (V15) and the iliococcygeal muscle (V55). Finally, increase in stool frequency was associated with the iliococcygeal muscle (V45) and the levator ani (V40). No significant associations were found for rectal pain. CONCLUSIONS Different anorectal side effects are associated with different anatomical substructures within and around the anorectum. The dosimetric variables associated with these side effects can be used to optimize radiotherapy treatment planning aiming at prevention of specific side effects and to estimate the benefit of new radiation technologies.

Predicting response to neoadjuvant chemoradiotherapy in esophageal cancer with textural features derived from pre-treatment 18F-FDG PET/CT imaging

Adequate prediction of tumor response to neoadjuvant chemoradiotherapy (nCRT) in esophageal cancer (EC) patients is important in a more personalized treatment. The current best clinical method to predict pathologic complete response is SUVmax in 18F-FDG PET/CT imaging. To improve the prediction of response, we constructed a model to predict complete response to nCRT in EC based on pretreatment clinical parameters and 18F-FDG PET/CT–derived textural features. Methods: From a prospectively maintained single-institution database, we reviewed 97 consecutive patients with locally advanced EC and a pretreatment 18F-FDG PET/CT scan between 2009 and 2015. All patients were treated with nCRT (carboplatin/paclitaxel/41.4 Gy) followed by esophagectomy. We analyzed clinical, geometric, and pretreatment textural features extracted from both 18F-FDG PET and CT. The current most accurate prediction model with SUVmax as a predictor variable was compared with 6 different response prediction models constructed using least absolute shrinkage and selection operator regularized logistic regression. Internal validation was performed to estimate the model’s performances. Pathologic response was defined as complete versus incomplete response (Mandard tumor regression grade system 1 vs. 2–5). Results: Pathologic examination revealed 19 (19.6%) complete and 78 (80.4%) incomplete responders. Least absolute shrinkage and selection operator regularization selected the clinical parameters: histologic type and clinical T stage, the 18F-FDG PET–derived textural feature long run low gray level emphasis, and the CT-derived textural feature run percentage. Introducing these variables to a logistic regression analysis showed areas under the receiver-operating-characteristic curve (AUCs) of 0.78 compared with 0.58 in the SUVmax model. The discrimination slopes were 0.17 compared with 0.01, respectively. After internal validation, the AUCs decreased to 0.74 and 0.54, respectively. Conclusion: The predictive values of the constructed models were superior to the standard method (SUVmax). These results can be considered as an initial step in predicting tumor response to nCRT in locally advanced EC. Further research in refining the predictive value of these models is needed to justify omission of surgery.

Selection of head and neck cancer patients for adaptive radiotherapy to decrease xerostomia

BACKGROUND AND PURPOSE The aim of this study was to develop and validate a method to select head and neck cancer patients for adaptive radiotherapy (ART) pre-treatment. Potential pre-treatment selection criteria presented in recent literature were included in the analysis. MATERIALS AND METHODS Deviations from the planned parotid gland mean dose (PG ΔDmean) were estimated for 113 head and neck cancer patients by re-calculating plans on repeat CT scans. Uni- and multivariable linear regression analyses were performed to select pre-treatment parameters, and ROC curve analysis was used to determine cut off values, for selecting patients with a PG dose deviation larger than 3Gy. The patient selection method was validated in a second patient cohort of 43 patients. RESULTS After multivariable analysis, the planned PG Dmean remained the only significant parameter for PG ΔDmean. A sensitivity of 91% and 80% could be obtained using a threshold of PG Dmean of 22.2Gy, for the development and validation cohorts, respectively. This would spare 38% (development cohort) and 24% (validation cohort) of patients from the labour-intensive ART procedure. CONCLUSIONS The presented method to select patients for ART pre-treatment reduces the labour of ART, contributing to a more effective allocation of the department resources.

Robust Intensity Modulated Proton Therapy (IMPT) Increases Estimated Clinical Benefit in Head and Neck Cancer Patients.

Purpose To compare the clinical benefit of robust optimized Intensity Modulated Proton Therapy (minimax IMPT) with current photon Intensity Modulated Radiation Therapy (IMRT) and PTV-based IMPT for head and neck cancer (HNC) patients. The clinical benefit is quantified in terms of both Normal Tissue Complication Probability (NTCP) and target coverage in the case of setup and range errors. Methods and Materials For 10 HNC patients, PTV-based IMRT (7 fields), minimax and PTV-based IMPT (2, 3, 4, 5 and 7 fields) plans were tested on robustness. Robust optimized plans differed from PTV-based plans in that they target the CTV and penalize possible error scenarios, instead of using the static isotropic CTV-PTV margin. Perturbed dose distributions of all plans were acquired by simulating in total 8060 setup (±3.5 mm) and range error (±3%) combinations. NTCP models for xerostomia and dysphagia were used to predict the clinical benefit of IMPT versus IMRT. Results The robustness criterion was met in the IMRT and minimax IMPT plans in all error scenarios, but this was only the case in 1 of 40 PTV-based IMPT plans. Seven (out of 10) patients had relatively large NTCP reductions in minimax IMPT plans compared to IMRT. For these patients, xerostomia and dysphagia NTCP values were reduced by 17.0% (95% CI; 13.0–21.1) and 8.1% (95% CI; 4.9–11.2) on average with minimax IMPT. Increasing the number of fields did not contribute to plan robustness, but improved organ sparing. Conclusions The estimated clinical benefit in terms of NTCP of robust optimized (minimax) IMPT is greater than that of IMRT and PTV-based IMPT in HNC patients. Furthermore, the target coverage of minimax IMPT plans in the presence of errors was comparable to IMRT plans.

(18)F-FDG PET image biomarkers improve prediction of late radiation-induced xerostomia

BACKGROUND AND PURPOSE Current prediction of radiation-induced xerostomia 12months after radiotherapy (Xer12m) is based on mean parotid gland dose and baseline xerostomia (Xerbaseline) scores. The hypothesis of this study was that prediction of Xer12m is improved with patient-specific characteristics extracted from 18F-FDG PET images, quantified in PET image biomarkers (PET-IBMs). PATIENTS AND METHODS Intensity and textural PET-IBMs of the parotid gland were collected from pre-treatment 18F-FDG PET images of 161 head and neck cancer patients. Patient-rated toxicity was prospectively collected. Multivariable logistic regression models resulting from step-wise forward selection and Lasso regularisation were internally validated by bootstrapping. The reference model with parotid gland dose and Xerbaseline was compared with the resulting PET-IBM models. RESULTS High values of the intensity PET-IBM (90th percentile (P90)) and textural PET-IBM (Long Run High Grey-level Emphasis 3 (LRHG3E)) were significantly associated with lower risk of Xer12m. Both PET-IBMs significantly added in the prediction of Xer12m to the reference model. The AUC increased from 0.73 (0.65-0.81) (reference model) to 0.77 (0.70-0.84) (P90) and 0.77 (0.69-0.84) (LRHG3E). CONCLUSION Prediction of Xer12m was significantly improved with pre-treatment PET-IBMs, indicating that high metabolic parotid gland activity is associated with lower risk of developing late xerostomia. This study highlights the potential of incorporating patient-specific PET-derived functional characteristics into NTCP model development.

Improving the prediction of overall survival for head and neck cancer patients using image biomarkers in combination with clinical parameters

PURPOSE To develop and validate prediction models of overall survival (OS) for head and neck cancer (HNC) patients based on image biomarkers (IBMs) of the primary tumor and positive lymph nodes (Ln) in combination with clinical parameters. MATERIAL AND METHODS The study cohort was composed of 289 nasopharyngeal cancer (NPC) patients from China and 298 HNC patients from the Netherlands. Multivariable Cox-regression analysis was performed to select clinical parameters from the NPC and HNC datasets, and IBMs from the NPC dataset. Final prediction models were based on both IBMs and clinical parameters. RESULTS Multivariable Cox-regression analysis identified three independent IBMs (tumor Volume-density, Run Length Non-uniformity and Ln Major-axis-length). This IBM model showed a concordance(c)-index of 0.72 (95%CI: 0.65-0.79) for the NPC dataset, which performed reasonably with a c-index of 0.67 (95%CI: 0.62-0.72) in the external validation HNC dataset. When IBMs were added in clinical models, the c-index of the NPC and HNC datasets improved to 0.75 (95%CI: 0.68-0.82; p=0.019) and 0.75 (95%CI: 0.70-0.81; p<0.001), respectively. CONCLUSION The addition of IBMs from the primary tumor and Ln improved the prognostic performance of the models containing clinical factors only. These combined models may improve pre-treatment individualized prediction of OS for HNC patients.

Parotid gland fat related Magnetic Resonance image biomarkers improve prediction of late radiation-induced xerostomia

PURPOSE This study investigated whether Magnetic Resonance image biomarkers (MR-IBMs) were associated with xerostomia 12 months after radiotherapy (Xer12m) and to test the hypothesis that the ratio of fat-to-functional parotid tissue is related to Xer12m. Additionally, improvement of the reference Xer12m model based on parotid gland dose and baseline xerostomia, with MR-IBMs was explored. METHODS Parotid gland MR-IBMs of 68 head and neck cancer patients were extracted from pre-treatment T1-weighted MR images, which were normalized to fat tissue, quantifying 21 intensity and 43 texture image characteristics. The performance of the resulting multivariable logistic regression models after bootstrapped forward selection was compared with that of the logistic regression reference model. Validity was tested in a small external cohort of 25 head and neck cancer patients. RESULTS High intensity MR-IBM P90 (the 90th intensity percentile) values were significantly associated with a higher risk of Xer12m. High P90 values were related to high fat concentration in the parotid glands. The MR-IBM P90 significantly improved model performance in predicting Xer12m (likelihood-ratio-test; p = 0.002), with an increase in internally validated AUC from 0.78 (reference model) to 0.83 (P90). The MR-IBM P90 model also outperformed the reference model (AUC = 0.65) on the external validation cohort (AUC = 0.83). CONCLUSION Pre-treatment MR-IBMs were associated to radiation-induced xerostomia, which supported the hypothesis that the amount of predisposed fat within the parotid glands is associated with Xer12m. In addition, xerostomia prediction was improved with MR-IBMs compared to the reference model.

Development of a prediction model for late urinary incontinence, hematuria, pain and voiding frequency among irradiated prostate cancer patients

Background and purpose Incontinence, hematuria, voiding frequency and pain during voiding are possible side effects of radiotherapy among patients treated for prostate cancer. The objective of this study was to develop multivariable NTCP models for these side effects. Material and methods This prospective cohort study was composed of 243 patients with localized or locally advanced prostate cancer (stage T1-3). Genito-urinary (GU) toxicity was assessed using a standardized follow-up program. The GU toxicity endpoints were scored using the Common Terminology Criteria for Adverse Events version 3.0 (CTCAE 3.0) scoring system. The full bladder and different anatomical subregions within the bladder were delineated. A least absolute shrinkage and selection operator (LASSO) logistic regression analysis was used to analyze dose volume effects on the four individual endpoints. Results In the univariable analysis, urinary incontinence was significantly associated with dose distributions in the trigone (V55-V75, mean). Hematuria was significantly associated with the bladder wall dose (V40-V75, mean), bladder dose (V70-V75), cardiovascular disease and anticoagulants use. Pain during urinating was associated with the dose to the trigone (V50-V75, mean) and with trans transurethral resection of the prostate (TURP). In the final multivariable model urinary incontinence was associated with the mean dose of the trigone. Hematuria was associated with bladder wall dose (V75) and cardiovascular disease, while pain during urinating was associated with trigone dose (V75) and TURP. No significant associations were found for increase in voiding frequency. Conclusions Radiation-induced urinary side effects are associated with dose distributions to different organs as risk. Given the dose effect relationships found, decreasing the dose to the trigone and bladder wall may reduce the incidence of incontinence, pain during voiding and hematuria, respectively.