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BackgroundThe present study aimed to define the optimal number of atlases for automatic multi-atlas-based brachial plexus (BP) segmentation and to compare Simultaneous Truth and Performance Level Estimation (STAPLE) label fusion with Patch label fusion using the ADMIRE® software. The accuracy of the autosegmentations was measured by comparing all of the generated autosegmentations with the anatomically validated gold standard segmentations that were developed using cadavers.Materials and methodsTwelve cadaver computed tomography (CT) atlases were used for automatic multi-atlas-based segmentation. To determine the optimal number of atlases, one atlas was selected as a patient and the 11 remaining atlases were registered onto this patient using a deformable image registration algorithm. Next, label fusion was performed by using every possible combination of 2 to 11 atlases, once using STAPLE and once using Patch. This procedure was repeated for every atlas as a patient.The similarity of the generated automatic BP segmentations and the gold standard segmentation was measured by calculating the average Dice similarity (DSC), Jaccard (JI) and True positive rate (TPR) for each number of atlases. These similarity indices were compared for the different number of atlases using an equivalence trial and for the two label fusion groups using an independent sample-t test.ResultsDSC’s and JI’s were highest when using nine atlases with both STAPLE (average DSC = 0,532; JI = 0,369) and Patch (average DSC = 0,530; JI = 0,370). When comparing both label fusion algorithms using 9 atlases for both, DSC and JI values were not significantly different. However, significantly higher TPR values were achieved in favour of STAPLE (p < 0,001). When fewer than four atlases were used, STAPLE produced significantly lower DSC, JI and TPR values than did Patch (p = 0,0048).ConclusionsUsing 9 atlases with STAPLE label fusion resulted in the most accurate BP autosegmentations (average DSC = 0,532; JI = 0,369 and TPR = 0,760). Only when using fewer than four atlases did the Patch label fusion results in a significantly more accurate autosegmentation than STAPLE.

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In this series, setup accuracy is significantly worse in prone compared to supine position for the LA and LO directions. However, without proper image-guidance, uncertainty margins of about 1 cm are also necessary for supine WBI. For patients with a higher BMI, larger margins are required.

We report on a dosimetrical study comparing supine (S) and prone-crawl (P) position for radiotherapy of whole breast (WB) and loco-regional lymph node regions, including the internal mammary chain (LN_IM). Six left sided breast cancer patients were CT-simulated in S and P positions and four patients only in P position. Treatment plans were made using non-coplanar volumetric modulated arc photon therapy (VMAT) or pencil beam scanning intensity modulated proton therapy (IMPT). Dose prescription was 15*2.67 Gy(GyRBE). The average mean heart doses for S or P VMAT were 5.6 or 4.3 Gy, respectively (p = 0.16) and 1.02 or 1.08 GyRBE, respectively for IMPT (p = 0.8; p < 0.001 for IMPT versus VMAT). The average mean lung doses for S or P VMAT were 5.91 or 2.90 Gy, respectively (p = 0.002) and 1.56 or 1.09 GyRBE, respectively for IMPT (p = 0.016). In high-risk patients, average (range) thirty-year mortality rates from radiotherapy-related cardiac injury and lung cancer were estimated at 6.8(5.4–9.4)% or 3.8(2.8–5.1)% for S or P VMAT (p < 0.001), respectively, and 1.6(1.1–2.0)% or 1.2(0.8–1.6)% for S or P IMPT (p = 0.25), respectively. Radiation-related mortality risk could outweigh the ~8% disease-specific survival benefit of WB + LN_IM radiotherapy for S VMAT but not P VMAT. IMPT carries the lowest radiation-related mortality risks.