Clinical validation of an automatic atlas-based segmentation tool for male pelvis CT images.

PURPOSE: This retrospective work aims to evaluate the possible impact on intra- and inter-observer variability, contouring time, and contour accuracy of introducing a pelvis computed tomography (CT) auto-segmentation tool in radiotherapy planning workflow. METHODS: Tests were carried out on five structures (bladder, rectum, pelvic lymph-nodes, and femoral heads) of six previously treated subjects, enrolling five radiation oncologists (ROs) to manually re-contour and edit auto-contours generated with a male pelvis CT atlas created with the commercial software MIM MAESTRO. The ROs first delineated manual contours (M). Then they modified the auto-contours, producing automatic-modified (AM) contours. The procedure was repeated to evaluate intra-observer variability, producing M1, M2, AM1, and AM2 contour sets (each comprising 5 structures × 6 test patients × 5 ROs = 150 contours), for a total of 600 contours. Potential time savings was evaluated by comparing contouring and editing times. Structure contours were compared to a reference standard by means of Dice similarity coefficient (DSC) and mean distance to agreement (MDA), to assess intra- and inter-observer variability. To exclude any automation bias, ROs evaluated both M and AM sets as "clinically acceptable" or "to be corrected" in a blind test. RESULTS: Comparing AM to M sets, a significant reduction of both inter-observer variability (p < 0.001) and contouring time (-45% whole pelvis, p < 0.001) was obtained. Intra-observer variability reduction was significant only for bladder and femoral heads (p < 0.001). The statistical test showed no significant bias. CONCLUSION: Our atlas-based workflow proved to be effective for clinical practice as it can improve contour reproducibility and generate time savings. Based on these findings, institutions are encouraged to implement their auto-segmentation method.

Methodological approach to create an atlas using a commercial auto-contouring software.

PURPOSE: The aim of this work was to establish a methodological approach for creation and optimization of an atlas for auto-contouring, using the commercial software MIM MAESTRO (MIM Software Inc. Cleveland OH). METHODS: A computed tomography (CT) male pelvis atlas was created and optimized to evaluate how different tools and options impact on the accuracy of automatic segmentation. Pelvic lymph nodes (PLN), rectum, bladder, and femurs of 55 subjects were reviewed for consistency by a senior consultant radiation oncologist with 15 yr of experience. Several atlas and workflow options were tuned to optimize the accuracy of auto-contours. The deformable image registration (DIR), the finalization method, the k number of atlas best matching subjects, and several post-processing options were studied. To test our atlas performances, automatic and reference manual contours of 20 test subjects were statistically compared based on dice similarity coefficient (DSC) and mean distance to agreement (MDA) indices. The effect of field of view (FOV) reduction on auto-contouring time was also investigated. RESULTS: With the optimized atlas and workflow, DSC and MDA median values of bladder, rectum, PLN, and femurs were 0.91 and 1.6 mm, 0.85 and 1.6 mm, 0.85 and 1.8 mm, and 0.96 and 0.5 mm, respectively. Auto-contouring time was more than halved by strictly cropping the FOV of the subject to be contoured to the pelvic region. CONCLUSION: A statistically significant improvement of auto-contours accuracy was obtained using our atlas and optimized workflow instead of the MIM Software pelvic atlas.

Robotic stereotactic radiotherapy for liver oligometastases from colorectal cancer: a single-center experience.

PURPOSE: To report on the safety and clinical benefit of robotic stereotactic radiotherapy (SBRT) for liver oligometastatic colorectal cancer (CRC). METHODS: Robotic SBRT was applied to oligometastatic CRC patients, defined as having 1-4 liver metastases and absent or controlled extrahepatic disease. The intended prescription dose was 37.5 Gy in three fractions. Treatment efficacy was estimated by clinical benefit rate (CBR), progression-free survival (PFS) and overall survival (OS). Toxicity was graded according to CTC-AE scale, v. 4.03. Regression analysis was performed to search for the presence of any predictive factors. RESULTS: Between 2012 and 2017, 38 patients (66 lesions) were irradiated. The median delivered biological effective maximum dose (maxBED10) was 142 Gy. At a median follow-up of 11.8 months (range 3.2-58.8), the 1- and 2-year OS were 67.3% and 44.1%, respectively. Actuarial LC rates for all patients at 6 and 12 months were 64.2% and 60.4%, respectively. Local or distant progression occurred in 28 (77.8%) patients, with a 1- and 2-year PFS of 19.3% and 12.2%, respectively. The CBR was 71.4%, with no significant association with maxBED10. At multivariate analysis, the presence of extrahepatic disease had a detrimental impact on PFS (HR 3.98, 95% CI 1.77-8.93; p < 0.001) and OS (HR 3.58, 95% CI 1.06-12.07; p < 0.04). No acute grade 3 gastrointestinal toxicity was observed. CONCLUSIONS: Our analysis underlines the importance of patients' selection to identify the oligometastatic scenario most likely to benefit from SBRT. Prospective studies are needed to further assess its role among locoregional treatment options for liver metastases from CRC.

Local treatment for relapsing glioblastoma: A decision-making tree for choosing between reirradiation and second surgery.

In case of circumscribed recurrent glioblastoma (rec-GBM), a second surgery (Re-S) and reirradiation (Re-RT) are local strategies to consider. The aim is to provide an algorithm to use in the daily clinical practice. The first step is to consider the life expectancy in order to establish whether the patient should be a candidate for active treatment. In case of a relatively good life expectancy (>3 months) and a confirmed circumscribed disease(i.e. without multiple lesions that are in different lobes/hemispheres), the next step is the assessment of the prognostic factors for local treatments. Based on the existing prognostic score systems, patients who should be excluded from local treatments may be identified; based on the validated prognostic factors, one or the other local treatment may be preferred. The last point is the estimation of expected toxicity, considering patient-related, tumor-related and treatment-related factors impacting on side effects. Lastly, patients with very good prognostic factors may be considered for receiving a combined treatment.