RESUMO
Purpose/objectives: Auto-segmentation with artificial intelligence (AI) offers an opportunity to reduce inter- and intra-observer variability in contouring, to improve the quality of contours, as well as to reduce the time taken to conduct this manual task. In this work we benchmark the AI auto-segmentation contours produced by five commercial vendors against a common dataset. Methods and materials: The organ at risk (OAR) contours generated by five commercial AI auto-segmentation solutions (Mirada (Mir), MVision (MV), Radformation (Rad), RayStation (Ray) and TheraPanacea (Ther)) were compared to manually-drawn expert contours from 20 breast, 20 head and neck, 20 lung and 20 prostate patients. Comparisons were made using geometric similarity metrics including volumetric and surface Dice similarity coefficient (vDSC and sDSC), Hausdorff distance (HD) and Added Path Length (APL). To assess the time saved, the time taken to manually draw the expert contours, as well as the time to correct the AI contours, were recorded. Results: There are differences in the number of CT contours offered by each AI auto-segmentation solution at the time of the study (Mir 99; MV 143; Rad 83; Ray 67; Ther 86), with all offering contours of some lymph node levels as well as OARs. Averaged across all structures, the median vDSCs were good for all systems and compared favorably with existing literature: Mir 0.82; MV 0.88; Rad 0.86; Ray 0.87; Ther 0.88. All systems offer substantial time savings, ranging between: breast 14-20 mins; head and neck 74-93 mins; lung 20-26 mins; prostate 35-42 mins. The time saved, averaged across all structures, was similar for all systems: Mir 39.8 mins; MV 43.6 mins; Rad 36.6 min; Ray 43.2 mins; Ther 45.2 mins. Conclusions: All five commercial AI auto-segmentation solutions evaluated in this work offer high quality contours in significantly reduced time compared to manual contouring, and could be used to render the radiotherapy workflow more efficient and standardized.
RESUMO
The optimal management of intrahepatic malignancies involves a multidisciplinary approach. Although surgical resection has been considered the only curative approach, the use of several minimally invasive ablative techniques has dramatically increased the last two decades, mainly due to the fact that they provide similar oncological results with significantly decreased morbidity. Among these modalities, interstitial liver brachytherapy, probably the most flexible liver ablative method, with excellent clinical data on its safety and effectiveness, is frequently not even mentioned as an option in the current peer reviewed literature and guidelines. Brachytherapy is a type of radiotherapy utilizing radionuclides that are directly inserted into the tumor. Compared to external beam radiation therapy, brachytherapy has the potential to deliver an ablative radiation dose over a short period of time, with the advantage of a rapid dose fall-off, that allows for sparing of adjacent healthy tissue. For numerous malignancies such as skin, gynecological, breast, prostate, head and neck, bladder, liver and soft-tissue tumors, brachytherapy as a monotherapy or combined with external beam radiation therapy, has become a standard treatment for many decades. This review article aims to describe the high-dose-rate liver brachytherapy technique, its selection criteria, present its advantages and disadvantages, as well as the available clinical data, in order to help physicians to explore and hopefully introduce liver brachytherapy into their clinical routine.
RESUMO
An innovative template, based on thoracic cage surface reconstructions for breast interstitial brachytherapy was developed. Hybrid-inverse-planning-optimisation-based implantations and brachytherapy plans, using three custom anthropomorphic breast phantoms, were utilised for its validation. A user independent, inverse planning and inverse implanting technique is proposed.
