Dataset Information

Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.

ABSTRACT: PURPOSE:To determine whether serial cone beam computed tomography (CBCT) images taken during head and neck radiation therapy (HNR) can improve chronic xerostomia prediction. METHODS AND MATERIALS:In a retrospective analysis, parotid glands (PGs) were delineated on daily kV CBCT images using deformable image registration for 119 HNR patients (60 or 70 Gy in 2 Gy fractions over 6 or 7 weeks). Deformable image registration accuracy for a subset of deformed contours was quantified using the Dice similarity coefficient and mean distance to agreement in comparison with manually drawn contours. Average weekly changes in CBCT-measured mean Hounsfield unit intensity and volume were calculated for each PG relative to week 1. Dose-volume histogram statistics were extracted from each plan, and interactions among dose, volume, and intensity were investigated. Univariable analysis and penalized logistic regression were used to analyze association with observer-rated xerostomia at 1 year after HNR. Models including CBCT delta imaging features were compared with clinical and dose-volume histogram-only models using area under the receiver operating characteristic curve (AUC) for grade ?1 and grade ?2 xerostomia prediction. RESULTS:All patients experienced end-treatment PG volume reduction with mean (range) ipsilateral and contralateral PG shrinkage of 19.6% (0.9%-58.4%) and 17.7% (4.4%-56.3%), respectively. Midtreatment volume change was highly correlated with mean PG dose (r = -0.318, P < 1e-6). Incidence of grade ?1 and grade ?2 xerostomia was 65% and 16%, respectively. For grade ?1 xerostomia prediction, the delta-imaging model had an AUC of 0.719 (95% confidence interval [CI], 0.603-0.830), compared with 0.709 (95% CI, 0.603-0.815) for the dose/clinical model. For grade ?2 xerostomia prediction, the dose/clinical model had an AUC of 0.692 (95% CI, 0.615-0.770), and the addition of contralateral PG changes modestly improved predictive performance, with an AUC of 0.776 (0.643-0.912). CONCLUSIONS:The rate of CBCT-measured PG image feature changes improves prediction over dose alone for chronic xerostomia prediction. Analysis of CBCT images acquired for treatment positioning may provide an inexpensive monitoring system to support toxicity-reducing adaptive radiation therapy.

SUBMITTER: Rosen BS

PROVIDER: S-EPMC6411287 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

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Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.

Rosen Benjamin S BS Hawkins Peter G PG Polan Daniel F DF Balter James M JM Brock Kristy K KK Kamp Justin D JD Lockhart Christina M CM Eisbruch Avraham A Mierzwa Michelle L ML Ten Haken Randall K RK El Naqa Issam I

International journal of radiation oncology, biology, physics 20180710 4

<h4>Purpose</h4>To determine whether serial cone beam computed tomography (CBCT) images taken during head and neck radiation therapy (HNR) can improve chronic xerostomia prediction.<h4>Methods and materials</h4>In a retrospective analysis, parotid glands (PGs) were delineated on daily kV CBCT images using deformable image registration for 119 HNR patients (60 or 70 Gy in 2 Gy fractions over 6 or 7 weeks). Deformable image registration accuracy for a subset of deformed contours was quantified usi ...[more]

PMID: 30003997

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Project description:PurposeTo analyze baseline CT/MR-based image features of salivary glands to predict radiation-induced xerostomia 3-months after head-and-neck cancer (HNC) radiotherapy.MethodsA retrospective analysis was performed on 266 HNC patients who were treated using radiotherapy at our institution between 2009 and 2018. CT and T1 post-contrast MR images along with NCI-CTCAE xerostomia grade (3-month follow-up) were prospectively collected at our institution. CT and MR images were registered on which parotid/submandibular glands were contoured. Image features were extracted for ipsilateral/contralateral parotid and submandibular glands relative to the location of the primary tumor. Dose-volume-histogram (DVH) parameters were also acquired. Features were pre-selected based on Spearman correlation before modelling by examining the correlation with xerostomia (p < 0.05). A shrinkage regression analysis of the pre-selected features was performed using LASSO. The internal validity of the variable selection was estimated by repeating the entire variable selection procedure using a leave-one-out-cross-validation. The most frequently selected variables were considered in the final model. A generalized linear regression with repeated ten-fold cross-validation was developed to predict radiation-induced xerostomia at 3-months after radiotherapy. This model was tested in an independent dataset (n = 50) of patients who were treated at the same institution in 2017-2018. We compared the prediction performances under eight conditions (DVH-only, CT-only, MR-only, CT + MR, DVH + CT, DVH + CT + MR, Clinical+CT + MR, and Clinical+DVH + CT + MR) using the area under the receiver operating characteristic curve (ROC-AUC).ResultsAmong extracted features, 7 CT, 5 MR, and 2 DVH features were selected. The internal cohort (n = 216) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.73 ± 0.01, 0.69 ± 0.01, 0.70 ± 0.01, and 0.79 ± 0.01, respectively. The validation cohort (n = 50) ROC-AUC values for DVH, CT, MR, and Clinical+DVH + CT + MR features were 0.63, 0.57, 0.66, and 0.68, respectively. The DVH-ROC was not significantly different than the CT-ROC (p = 0.8) or MR-ROC (p = 0.4). However, the CT + MR-ROC was significantly different than the CT-ROC (p = 0.03), but not the Clinical+DVH + CT + MR model (p = 0.5).ConclusionOur results suggest that baseline CT and MR image features may reflect baseline salivary gland function and potential risk for radiation injury. The integration of baseline image features into prediction models has the potential to improve xerostomia risk stratification with the ultimate goal of truly personalized HNC radiotherapy.

Project description:To assess whether, in addition to sparing the parotid glands (PGs), xerostomia after chemotherapy plus intensity-modulated radiotherapy (chemo-IMRT) for head-and-neck cancer is affected by reducing the dose to the other salivary glands.In a prospective study, 78 patients with Stage III-IV oropharynx/nasopharynx cancer underwent chemo-IMRT, with the aim of sparing the parts of the bilateral PGs, oral cavity (OC) containing the minor salivary glands, and contralateral submandibular gland (SMG) outside the target (when contralateral level I was not a target). Before therapy and periodically for 24 months, validated patient-reported xerostomia questionnaire (XQ) scores and observer-graded xerostomia scores were recorded. Also, the stimulated and unstimulated saliva was measured selectively from each of the PGs and SMGs. The mean OC doses served as surrogates of minor salivary gland dysfunction. Regression models assessed the XQ and observer-graded xerostomia predictors.Statistically significant predictors of the XQ score on univariate analysis included the OC, PG, and SMG mean doses and the baseline XQ score, time since RT, and both stimulated and unstimulated PG saliva flow rates. Similar factors were statistically significant predictors of observer-graded xerostomia. The OC, PG, and SMG mean doses were moderately intercorrelated (r = 0.47-0.55). On multivariate analyses, after adjusting for the PG and SMG doses, the OC mean dose (p < .0001), interval from RT (p < .0001), and stimulated PG saliva (p < .0025) were significant predictors of the XQ scores and the OC mean dose and time for observer-graded xerostomia. Although scatter plots showed no thresholds, an OC mean dose of <40 Gy and contralateral SMG mean dose of <50 Gy were each associated with low patient-reported and observer-rated xerostomia at almost all post-therapy points.The PG, SMG, and OC mean doses were significant predictors of both patient-reported and observer-rated xerostomia after chemo-IMRT, with OC doses remaining significant after adjusting for the PG and SMG doses. These results support efforts to spare all the salivary glands by IMRT, beyond the PGs alone.

Project description:PurposeTo develop an automated magnetic resonance imaging (MRI) parotid segmentation method to monitor radiation-induced parotid gland changes in patients after head and neck radiation therapy (RT).Methods and materialsThe proposed method combines the atlas registration method, which captures the global variation of anatomy, with a machine learning technology, which captures the local statistical features, to automatically segment the parotid glands from the MRIs. The segmentation method consists of 3 major steps. First, an atlas (pre-RT MRI and manually contoured parotid gland mask) is built for each patient. A hybrid deformable image registration is used to map the pre-RT MRI to the post-RT MRI, and the transformation is applied to the pre-RT parotid volume. Second, the kernel support vector machine (SVM) is trained with the subject-specific atlas pair consisting of multiple features (intensity, gradient, and others) from the aligned pre-RT MRI and the transformed parotid volume. Third, the well-trained kernel SVM is used to differentiate the parotid from surrounding tissues in the post-RT MRIs by statistically matching multiple texture features. A longitudinal study of 15 patients undergoing head and neck RT was conducted: baseline MRI was acquired prior to RT, and the post-RT MRIs were acquired at 3-, 6-, and 12-month follow-up examinations. The resulting segmentations were compared with the physicians' manual contours.ResultsSuccessful parotid segmentation was achieved for all 15 patients (42 post-RT MRIs). The average percentage of volume differences between the automated segmentations and those of the physicians' manual contours were 7.98% for the left parotid and 8.12% for the right parotid. The average volume overlap was 91.1% ± 1.6% for the left parotid and 90.5% ± 2.4% for the right parotid. The parotid gland volume reduction at follow-up was 25% at 3 months, 27% at 6 months, and 16% at 12 months.ConclusionsWe have validated our automated parotid segmentation algorithm in a longitudinal study. This segmentation method may be useful in future studies to address radiation-induced xerostomia in head and neck radiation therapy.

Project description:ImportanceWhole-brain radiation therapy (WBRT) delivers a substantial radiation dose to the parotid glands, but the parotid glands are not delineated for avoidance and xerostomia has never been reported as an adverse effect. Minimizing the toxic effects in patients receiving palliative treatments, such as WBRT, is crucial.ObjectiveTo assess whether xerostomia is a toxic effect of WBRT.Design, setting, and participantsThis observational cohort study enrolled patients from November 2, 2015, to March 20, 2018, at 1 academic center (University of North Carolina Hospitals) and 2 affiliated community hospitals (High Point Regional Hospital and University of North Carolina Rex Hospital). Adult patients (n = 100) receiving WBRT for the treatment or prophylaxis of brain metastases were enrolled. Patients who had substantial baseline xerostomia or did not complete WBRT or at least 1 postbaseline questionnaire were prospectively excluded from analysis and follow-up. Patients received 3-dimensional WBRT using opposed lateral fields covering the skull and the C1 or C2 vertebra. Per standard practice, the parotid glands were not prospectively delineated.Main outcomes and measuresPatients completed the University of Michigan Xerostomia Questionnaire and a 4-point bother score at baseline, immediately after WBRT, at 1 month, at 3 months, and at 6 months. The primary end point was the 1-month xerostomia score, with a hypothesized worsening score of 10 points from baseline.ResultsOf the 100 patients enrolled, 73 (73%) were eligible for analysis and 55 (55%) were evaluable at 1 month. The 73 patients included 43 women (59%) and 30 men (41%) with a median (range) age of 61 (23-88) years. The median volume of parotid receiving at least 20 Gy (V20Gy) was 47%. The mean xerostomia score was 7 points at baseline and was statistically significantly higher at each assessment period, including 21 points immediately after WBRT (95% CI, 16-26; P < .001), 23 points (95% CI, 16-30; P < .001) at 1 month, 21 points (95% CI, 13-28; P < .001) at 3 months, and 14 points (95% CI, 7-21; P = .03) at 6 months. At 1 month, the xerostomia score increased by 20 points or more in 19 patients (35%). The xerostomia score at 1 month was associated with parotid dose as a continuous variable and was 35 points in patients with parotid V20Gy of 47% or greater, compared with only 9 points in patients with parotid V20Gy less than 47% (P < .001). The proportion of patients who self-reported to be bothered quite a bit or bothered very much by xerostomia at 1 month was 50% in those with parotid V20Gy of 47% or greater, compared with only 4% in those with parotid V20Gy less than 47% (P < .001). At 3 months, this difference was 50% vs 0% (P = .001). Xerostomia was not associated with medication use.Conclusions and relevanceClinically significant xerostomia occurred by the end of WBRT, appeared to be persistent, and appeared to be associated with parotid dose. The findings from this study suggest that the parotid glands should be delineated for avoidance to minimize these toxic effects in patients who undergo WBRT and often do not survive long enough for salivary recovery.

Dataset Information

Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.

Publications

Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.

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