Repurposing traditional U-Net predictions for sparse SAM prompting in medical image segmentation.

Objective:Automated medical image segmentation (MIS) using deep learning has traditionally relied on models built and trained from scratch, or at least fine-tuned on a target dataset. The Segment Anything Model (SAM) by Meta challenges this paradigm by providing zero-shot generalisation capabilities. This study aims to develop and compare methods for refining traditional U-Net segmentations by repurposing them for automated SAM prompting.Approach:A 2D U-Net with EfficientNet-B4 encoder was trained using 4-fold cross-validation on an in-house brain metastases dataset. Segmentation predictions from each validation set were used for automatic sparse prompt generation via a bounding box prompting method (BBPM) and novel implementations of the point prompting method (PPM). The PPMs frequently produced poor slice predictions (PSPs) that required identification and substitution. A slice was identified as a PSP if it (1) contained multiple predicted regions per lesion or (2) possessed outlier foreground pixel counts relative to the patient's other slices. Each PSP was substituted with a corresponding initial U-Net or SAM BBPM prediction. The patients' mean volumetric dice similarity coefficient (DSC) was used to evaluate and compare the methods' performances.Main results:Relative to the initial U-Net segmentations, the BBPM improved mean patient DSC by 3.93 ± 1.48% to 0.847 ± 0.008 DSC. PSPs constituted 20.01-21.63% of PPMs' predictions and without substitution performance dropped by 82.94 ± 3.17% to 0.139 ± 0.023 DSC. Pairing the two PSP identification techniques yielded a sensitivity to PSPs of 92.95 ± 1.20%. By combining this approach with BBPM prediction substitution, the PPMs achieved segmentation accuracies on par with the BBPM, improving mean patient DSC by up to 4.17 ± 1.40% and reaching 0.849 ± 0.007 DSC.Significance:The proposed PSP identification and substitution techniques bridge the gap between PPM and BBPM performance for MIS. Additionally, the uniformity observed in our experiments' results demonstrates the robustness of SAM to variations in prompting style. These findings can assist in the design of both automatically and manually prompted pipelines.

Simultaneous Truth and Performance Level Estimation Method for Evaluation of Target Contouring in Radiosurgery.

BACKGROUND/AIM: The problem of lack of standardisation in target delineation and herewith the variability of target contours in Gamma Knife radiosurgery is as severe as in linac-based radiotherapy in general. The first aim of this study was to quantify the contouring variability for a group of five radiosurgery targets and estimate their true-volume based on multiple delineations using the Simultaneous Truth and Performance Level Estimation (STAPLE) algorithm. The second aim was to assess the robustness of the STAPLE method for the assessment of the true-volume, with respect to the number of contours available as input. PATIENTS AND METHODS: A multicentre analysis of the variability in contouring of five cases was performed. Twelve contours were provided for each case by experienced planners for Gamma Knife. To assess the robustness of the STAPLE method with respect to the number of contours used as input, sets of contours were randomly selected in the analysis. RESULTS: A high similarity was observed between the STAPLE generated true-volume and the 50%-agreement volume when all 12 available contours were used as input (90-100%). Lower similarity was observed with smaller sets of contours (10-70%). CONCLUSION: If a high number of input contours is available, the STAPLE method provides a valuable tool in the estimation of the true volume of a target based on multiple contours as well as the sensitivity and specificity for each input contour relative to the true volume of that structure. The robustness of the STAPLE method for rendering the true target volume depends on the number of contours provided as input and their variability with respect to shape, size and position.

The role of the concept of biologically effective dose (BED) in treatment planning in radiosurgery.

Radiosurgery (RS) treatment times vary, even for the same prescription dose, due to variations in the collimator size, the number of iso-centres/beams/arcs used and the time gap between each of these exposures. The biologically effective dose (BED) concept, incorporating fast and slow components of repair, was used to show the likely influence of these variables for Gamma Knife patients with Vestibular Schwannomas. Two patients plans were selected, treated with the Model B Gamma Knife, these representing the widest range of treatment variables; iso-centre numbers 3 and 13, overall treatment times 25.4 and 129.6 min, prescription dose 14 Gy. These were compared with 3 cases treated with the Perfexion(®) Gamma Knife. The iso-centre number varied between 11 and 18, treatment time 35.7 - 74.4 min, prescription dose 13 Gy. In the longer Model B Gamma Knife treatment plan the 14 Gy iso-dose was best matched by the 58 Gy2.47 iso-BED line, although higher and lower BED values were associated with regions on the prescription iso-dose. The equivalent value for the shorter treatment was 85 Gy2.47. BED volume histograms showed that a BED of 85 Gy2.47 only covered ∼65% of the target in the plan with the longer overall treatment time. The corresponding BED values for the 3 cases, treated with the Perfexion(®) Gamma Knife, were 59.5, 68.5 and 71.5 Gy2.47. In conclusion BED calculations, taking account of the repair of sublethal damage, may indicate the importance of reporting overall time to reflect the biological effectiveness of the total physical dose applied.

Application of the concept of biologically effective dose (BED) to patients with Vestibular Schwannomas treated by radiosurgery.

In the application of stereotactic radiosurgery, using the Gamma Knife, there are large variations in the overall treatment time for the same prescription dose, given in a single treatment session, for different patients. This is due to not only changes in the activity of the Cobolt-60 sources, but also to variations in the number of iso-centers used, the collimator size for a particular iso-center, and the time gap between the different iso-centers. Although frequently viewed as a single dose treatment the concept of biologically effective dose (BED), incorporating concurrent fast and a slow components of repair of sublethal damage, would imply potential variations in BED because of the influence of these different variables associated with treatment. This was investigated in 26 patients, treated for Vestibular Schwannomas, using the Series B Gamma-Knife, between 1999 and 2005. The iso-center number varied between 2 and 13, and the overall treatment time from 25.4-129.58 min. The prescription doses varied from 10-14 Gy. To obtain physical dose and dose-rates from each iso-center, in a number of locations in the region of interest, a prototype version of the Leksell GammaPlan® was used. For an individual patient, BED values varied by up to 15% for a given physical iso-dose. This was due to variation in the dose prescription at different locations on that iso-dose. Between patients there was a decline in the range of BED values as the overall treatment time increased. This increased treatment time was partly a function of the slow decline in the activity of the sources with time but predominantly due to changes in the number of iso-centers used. Thus, variations in BED values did not correlate with prescription dose but was modified by the overall treatment time.