Feasibility and safety of definite volumetric modulated arc therapy with simultaneous integrated boost to the dominant intraprostatic lesion in patients with unfavorable intermediate to high-risk prostate cancer

Background: The most common site of recurrence of prostate cancer after definite radiation therapy is the dominant intraprostatic lesion (DIL). This study aimed to investigate the feasibility and safety of definite volumetric modulated arc therapy (VMAT) with simultaneous integrated boost (SIB) to the DIL in patients with unfavorable intermediate to high-risk prostate cancer. Materials and methods: In this prospective uncontrolled clinical trial, patients were delivered VMAT at a dose of 87.75 Gy in 39 fractions or 70 Gy in 20 fractions to the DIL in combination with androgen deprivation therapy. Genitourinary (GU) and rectal toxicity, International Prostate Symptom Score (IPSS) and IPSS quality of life (IPSS-QOL) score were collected. Results: Forty-five patients with a median follow-up of 20 months were analyzed. The cumulative incidence of acute grade ³ 2 GU and rectal toxicity was 33.1% and 9.5%, respectively. Regarding late toxicity, the cumulative incidence of grade ≥ 2 GU and rectal toxicity was 12.6% and 2.8%, respectively. During treatment, the mean increase of IPSS was +7.4 ± 4.2 and the mean increase of IPSS-QOL was +1.7 ± 1.3. However, both IPSS and IPSS-QOL scores returned to their baseline levels by 3-months post-treatment. No significant correlation between baseline characteristics and grade ³ 2 GU or rectal toxicity was found. Conclusion: Focal SIB to the DIL of ≥ 90 Gy EQD2 in unfavorable intermediate to high-risk prostate cancer patients resulted in tolerable toxicity profiles. The mean IPSS and IPSS-QOL scores both worsened during treatment; however, both scores returned to baseline level by 3 months after treatment

3D Kinect Camera Scheme with Time-Series Deep-Learning Algorithms for Classification and Prediction of Lung Tumor Motility

This paper proposes a time-series deep-learning 3D Kinect camera scheme to classify the respiratory phases with a lung tumor and predict the lung tumor displacement. Specifically, the proposed scheme is driven by two time-series deep-learning algorithmic models: the respiratory-phase classification model and the regression-based prediction model. To assess the performance of the proposed scheme, the classification and prediction models were tested with four categories of datasets: patient-based datasets with regular and irregular breathing patterns; and pseudopatient-based datasets with regular and irregular breathing patterns. In this study, ‘pseudopatients’ refer to a dynamic thorax phantom with a lung tumor programmed with varying breathing patterns and breaths per minute. The total accuracy of the respiratory-phase classification model was 100%, 100%, 100%, and 92.44% for the four dataset categories, with a corresponding mean squared error (MSE), mean absolute error (MAE), and coefficient of determination (R2) of 1.2–1.6%, 0.65–0.8%, and 0.97–0.98, respectively. The results demonstrate that the time-series deep-learning classification and regression-based prediction models can classify the respiratory phases and predict the lung tumor displacement with high accuracy. Essentially, the novelty of this research lies in the use of a low-cost 3D Kinect camera with time-series deep-learning algorithms in the medical field to efficiently classify the respiratory phase and predict the lung tumor displacement

Enhanced Deep-Learning-Based Automatic Left-Femur Segmentation Scheme with Attribute Augmentation

This research proposes augmenting cropped computed tomography (CT) slices with data attributes to enhance the performance of a deep-learning-based automatic left-femur segmentation scheme. The data attribute is the lying position for the left-femur model. In the study, the deep-learning-based automatic left-femur segmentation scheme was trained, validated, and tested using eight categories of CT input datasets for the left femur (F-I–F-VIII). The segmentation performance was assessed by Dice similarity coefficient (DSC) and intersection over union (IoU); and the similarity between the predicted 3D reconstruction images and ground-truth images was determined by spectral angle mapper (SAM) and structural similarity index measure (SSIM). The left-femur segmentation model achieved the highest DSC (88.25%) and IoU (80.85%) under category F-IV (using cropped and augmented CT input datasets with large feature coefficients), with an SAM and SSIM of 0.117–0.215 and 0.701–0.732. The novelty of this research lies in the use of attribute augmentation in medical image preprocessing to enhance the performance of the deep-learning-based automatic left-femur segmentation scheme

Vaginal dose point reporting in cervical cancer patients treated with combined 2D/3D external beam radiotherapy and 2D/3D brachytherapy

Traditionally, vaginal dose points have been defined at the vaginal source level, thus not providing dose information for the entire vagina. Since reliable vaginal dose volume/surface histograms are unavailable, a strategy for comprehensive vaginal dose reporting for combined EBRT and BT was established and investigated. An anatomical vaginal reference point was defined at the level of the Posterior-Inferior Border of Symphysis (PIBS), plus two points ±2 cm (mid/introitus vagina). For BT extra points were selected for the upper vagina at 12/3/6/9 o'clock, at the vaginal surface and 5 mm depth. A vaginal reference length (VRL) was defined from ring centre to PIBS. Fifty-nine patients treated for cervical cancer were included in this retrospective feasibility study. The method was applicable to all patients. Total EQD2 doses at PIBS and ±2 cm were 36.7 Gy (3.1-68.2), 49.6 Gy (32.1-89.6) and 4.3 Gy (1.0-46.6). At the vaginal surface at ring level doses were respectively 266.1 Gy (67.6-814.5)/225.9 Gy (61.5-610.5) at 3/9 o'clock, and 85.1 Gy (55.4-140.3)/72.0 Gy (49.1-108.9) at 12/6 o'clock. Mean VRL on MRI was 5.6 cm (2.0-9.4). With this novel system, a comprehensive reporting of vaginal doses is feasible. The present study has demonstrated large dose variations between patients observed in all parts of the vagina, resulting from different contributions from EBRT and B

The Impact of Active Nutritional Support for Head and Neck Cancer Patients Receiving Concurrent Chemoradiotherapy

Objective: Malnutrition is the most common problem in head and neck cancer (HNC) patients receiving concurrent chemoradiotherapy. The radiation toxicities cause decreased food intake, with resultant severe weight loss and malnutrition. This study sought to determine whether an active nutrition improvement counseling program before and during concurrent chemoradiotherapy for HNC patients could increase the treatment completion rate without the interruptions caused by the side effects of chemoradiotherapy. Methods: The findings of a prospective study of the effects of an active nutrition improvement program before and during concurrent chemoradiotherapy (study, n = 32) was compared with those of a retrospective chart review of HNC patients who had received definite or postoperative concurrent chemoradiotherapy (control, n = 80). The correlations between nutritional status and the number of treatment completions, number of tube feeding insertions during treatment, RTOG toxicity, nutritional status, and quality of life were obtained. Results: There was no statistically significant difference between the concurrent chemoradiotherapy completion rates of both groups (p = 0.121; 95% CI, 0.226-1.188). The major cause of delayed or discontinued chemotherapy was oral mucositis. No significant differences were found in the tube feeding insertion rates and RTOG toxicities of both groups. However, the data showed a clinically significant difference in the concurrent chemoradiotherapy completion rate for the study group (56%), more than 15 percentage points higher than the control group’s rate (40%). Conclusion: An active nutrition improvement program before and during concurrent chemoradiotherapy is clinically beneficial for HNC patients, providing a higher treatment completion rate than otherwise

Multicentre evaluation of a novel vaginal dose reporting method in 153 cervical cancer patients

Recently, a vaginal dose reporting method for combined EBRT and BT in cervical cancer patients was proposed. The current study was to evaluate vaginal doses with this method in a multicentre setting, wherein different applicators, dose rates and protocols were used. In a subset of patients from the EMBRACE study, vaginal doses were evaluated. Doses at the applicator surface left/right and anterior/posterior and at 5mm depth were measured. In addition, the dose at the Posterior-Inferior Border of Symphysis (PIBS) vaginal dose point and PIBS±2cm, corresponding to the mid and lower vagina, was measured. 153 patients from seven institutions were included. Large dose variations expressed in EQD2 with α/β=3Gy were seen between patients, in particular at the top left and right vaginal wall (median 195 (range 61-947)Gy/178 (61-980)Gy, respectively). At 5mm depth, doses were 98 (55-212)Gy/91 (54-227)Gy left/right, and 71 (51-145)Gy/67 (49-189)Gy anterior/posterior, respectively. The dose at PIBS and PIBS±2cm was 41 (3-81)Gy, 54 (32-109)Gy and 5 (1-51)Gy, respectively. At PIBS+2cm (mid vagina) dose variation was coming from BT. The variation at PIBS-2cm (lower vagina) was mainly dependent on EBRT field border location. This novel method for reporting vaginal doses coming from EBRT and BT through well-defined dose points gives a robust representation of the dose along the vaginal axis. In addition, it allows comparison of vaginal dose between patients from different centres. The doses at the PIBS points represent the doses at the mid and lower parts of the vagina. Large variations in dose throughout the vagina were observed between patients and centre