Expert system classifier for adaptive radiation therapy in prostate cancer.

A classifier-based expert system was developed to compare delivered and planned radiation therapy in prostate cancer patients. Its aim is to automatically identify patients that can benefit from an adaptive treatment strategy. The study predominantly addresses dosimetric uncertainties and critical issues caused by motion of hollow organs. 1200 MVCT images of 38 prostate adenocarcinoma cases were analyzed. An automatic daily re-contouring of structures (i.e. rectum, bladder and femoral heads), rigid/deformable registration and dose warping was carried out to simulate dose and volume variations during therapy. Support vector machine, K-means clustering algorithms and similarity index analysis were used to create an unsupervised predictive tool to detect incorrect setup and/or morphological changes as a consequence of inadequate patient preparation due to stochastic physiological changes, supporting clinical decision-making. After training on a dataset that was considered sufficiently dosimetrically stable, the system identified two equally sized macro clusters with distinctly different volumetric and dosimetric baseline properties and defined thresholds for these two clusters. Application to the test cohort resulted in 25% of the patients located outside the two macro clusters thresholds and which were therefore suspected to be dosimetrically unstable. In these patients, over the treatment course, mean volumetric changes of 30 and 40% for rectum and bladder were detected which possibly represents values justifying adjustment of patient preparation, frequent re-planning or a plan-of-the-day strategy. Based on our research, by combining daily IGRT images with rigid/deformable registration and dose warping, it is possible to apply a machine learning approach to the clinical setting obtaining useful information for a decision regarding an individualized adaptive strategy. Especially for treatments influenced by the movement of hollow organs, this could reduce inadequate treatments and possibly reduce toxicity, thereby increasing overall RT efficacy.

SIS epidemiological model for adaptive RT: Forecasting the parotid glands shrinkage during tomotherapy treatment.

PURPOSE: A susceptible-infected-susceptible (SIS) epidemic model was applied to radiation therapy (RT) treatments to predict morphological variations in head and neck (H&N) anatomy. METHODS: 360 daily MVCT images of 12 H&N patients treated by tomotherapy were analyzed in this retrospective study. Deformable image registration (DIR) algorithms, mesh grids, and structure recontouring, implemented in the RayStation treatment planning system (TPS), were applied to assess the daily organ warping. The parotid's warping was evaluated using the epidemiological approach considering each vertex as a single subject and its deformed vector field (DVF) as an infection. Dedicated IronPython scripts were developed to export daily coordinates and displacements of the region of interest (ROI) from the TPS. matlab tools were implemented to simulate the SIS modeling. Finally, the fully trained model was applied to a new patient. RESULTS: A QUASAR phantom was used to validate the model. The patients' validation was obtained setting 0.4 cm of vertex displacement as threshold and splitting susceptible (S) and infectious (I) cases. The correlation between the epidemiological model and the parotids' trend for further optimization of alpha and beta was carried out by Euclidean and dynamic time warping (DTW) distances. The best fit with experimental conditions across all patients (Euclidean distance of 4.09 ± 1.12 and DTW distance of 2.39 ± 0.66) was obtained setting the contact rate at 7.55 ± 0.69 and the recovery rate at 2.45 ± 0.26; birth rate was disregarded in this constant population. CONCLUSIONS: Combining an epidemiological model with adaptive RT (ART), the authors' novel approach could support image-guided radiation therapy (IGRT) to validate daily setup and to forecast anatomical variations. The SIS-ART model developed could support clinical decisions in order to optimize timing of replanning achieving personalized treatments.

A support vector machine tool for adaptive tomotherapy treatments: Prediction of head and neck patients criticalities.

PURPOSE: Adaptive radiation therapy (ART) is an advanced field of radiation oncology. Image-guided radiation therapy (IGRT) methods can support daily setup and assess anatomical variations during therapy, which could prevent incorrect dose distribution and unexpected toxicities. A re-planning to correct these anatomical variations should be done daily/weekly, but to be applicable to a large number of patients, still require time consumption and resources. Using unsupervised machine learning on retrospective data, we have developed a predictive network, to identify patients that would benefit of a re-planning. METHODS: 1200 MVCT of 40 head and neck (H&N) cases were re-contoured, automatically, using deformable hybrid registration and structures mapping. Deformable algorithm and MATLAB(®) homemade machine learning process, developed, allow prediction of criticalities for Tomotherapy treatments. RESULTS: Using retrospective analysis of H&N treatments, we have investigated and predicted tumor shrinkage and organ at risk (OAR) deformations. Support vector machine (SVM) and cluster analysis have identified cases or treatment sessions with potential criticalities, based on dose and volume discrepancies between fractions. During 1st weeks of treatment, 84% of patients shown an output comparable to average standard radiation treatment behavior. Starting from the 4th week, significant morpho-dosimetric changes affect 77% of patients, suggesting need for re-planning. The comparison of treatment delivered and ART simulation was carried out with receiver operating characteristic (ROC) curves, showing monotonous increase of ROC area. CONCLUSIONS: Warping methods, supported by daily image analysis and predictive tools, can improve personalization and monitoring of each treatment, thereby minimizing anatomic and dosimetric divergences from initial constraints.

Transvaginal ultrasound assessment of uterine scar after previous caesarean section: comparison with 3T-magnetic resonance diffusion tensor imaging.

PURPOSE: This study aimed to evaluate 3-T magnetic resonance imaging in the analysis of caesarean scars in women with prior caesarean section (pCS) and investigate the potential added value of diffusion tensor imaging (3T-MR-DTI) with fibre tracking reconstruction, compared with transvaginal ultrasound (TVUS). METHODS: Thirty women who had previously undergone elective CS in a singleton pregnancy at term were examined (19 women with one pCS formed group 1 and 11 women with two pCS formed group 2). Patients underwent TVUS and 3T-MR-DTI within 2 days. Twelve women with prior vaginal delivery served as controls and underwent only 3T-MR. Uterine fibre architecture was depicted by MR-DTI with 3D tractography reconstruction providing quali-quantitative analysis of fibre, described as the reduction of number of longitudinal fibres that run through the uterine scar. RESULTS: Six subjects were excluded. According to 3T-MR morphology, scars were described as linear (n = 12) and retracting (n = 12); disagreement with TVUS was 54 %. The thickness of myometrium at the scar level was found to be significantly greater with 3T-MR compared to TVUS in linear scars (p = 0.01). No difference was found among retracting scars. In controls, according to 3T-MR-DTI, longitudinal myometrial fibres running in the anterior wall were similar to those in the posterior wall at same level -2 %; -27 % + 22 %). In groups 1 and 2 there was significant reduction in anterior fibres compared to posterior ones (-53 %; -77 % - 34 %; p = 0.0001). Among retracting scars, fibre reduction was significantly higher compared to linear scars, p < 0.016. CONCLUSIONS: The added value of 3T-MR with DTI lies in the prompt evaluation of muscle fibre remaining at scar level.

Review of the results of the in vivo dosimetry during total skin electron beam therapy.

This work reviews results of in vivo dosimetry (IVD) for total skin electron beam (TSEB) therapy, focusing on new methods, data emerged within 2012. All quoted data are based on a careful review of the literature reporting IVD results for patients treated by means of TSEB therapy. Many of the reviewed papers refer mainly to now old studies and/or old guidelines and recommendations (by IAEA, AAPM and EORTC), because (due to intrinsic rareness of TSEB-treated pathologies) only a limited number of works and reports with a large set of numerical data and proper statistical analysis is up-to-day available in scientific literature. Nonetheless, a general summary of the results obtained by the now numerous IVD techniques available is reported; innovative devices and methods, together with areas of possible further and possibly multicenter investigations for TSEB therapies are highlighted.

Reduction of scatter radiation during transradial percutaneous coronary angiography: a randomized trial using a lead-free radiation shield.

BACKGROUND: Occupational radiation exposure is a growing problem due to the increasing number and complexity of interventional procedures performed. Radial artery access has reduced the number of complications at the price of longer procedure duration. Radpad® scatter protection is a sterile, disposable bismuth-barium radiation shield drape that should be able to decrease the dose of operator radiation during diagnostic and interventional procedures. Such radiation shield has never been tested in a randomized study in humans. METHODS: Sixty consecutive patients undergoing coronary angiography by radial approach were randomized 1:1 to Radpad use versus no radiation shield protection. The sterile shield was placed around the area of right radial artery sheath insertion and extended medially to the patient trunk. All diagnostic procedures were performed by the same operator to reduce variability in radiation absorption. Radiation exposure was measured blindly using thermoluminescence dosimeters positioned at the operator's chest, left eye, left wrist, and thyroid. RESULTS: Despite similar fluoroscopy time (3.52 ± 2.71 min vs. 3.46 ± 2.77 min, P = 0.898) and total examination dose (50.5 ± 30.7 vs. 45.8 ± 18.0 Gycm(2), P = 0.231), the mean total radiation exposure to the operator was significantly lower when Radpad was utilized (282.8 ± 32.55 µSv vs. 367.8 ± 105.4 µSv, P < 0.0001) corresponding to a 23% total reduction. Moreover, mean radiation exposure was lower with Radpad utilization at all body locations ranging from 13 to 34% reduction. CONCLUSIONS: This first-in-men randomized trial demonstrates that Radpad significantly reduces occupational radiation exposure during coronary angiography performed through right radial artery access.