Evalutation of two commercial deep learning OAR segmentation models for prostate cancer treatment

Purpose or ObjectiveTo evaluate two commercial, CE labeled deep learning-based models for automatic organs at risk segmentation on planning CT images for prostate cancer radiotherapy. Model evaluation was focused on assessing both geometrical metrics and evaluating a potential time saving.Material and MethodsThe evaluated models consisted of RayStation 10B Deep Learning Segmentation (RaySearch Laboratories AB, Stockholm, Sweden) and MVision AI Segmentation Service (MVision, Helsinki, Finland) and were applied to CT images for a dataset of 54 male pelvis patients. The RaySearch model was re-trained with 44 clinic specific patients (Skåne University Hospital, Lund, Sweden) for the femoral head structures to adjust the model to our specific delineation guidelines. The model was evaluated on 10 patients from the same clinic. Dice similarity coefficient (DSC) and Hausdorff distance (95th percentile) was computed for model evaluation, using an in-house developed Python script. The average time for manual and AI model delineations was recorded.ResultsAverage DSC scores and Hausdorff distances for all patients and both models are presented in Figure 1 and Table 1, respectively. The femoral head segmentations in the re-trained RaySearch model had increased overlap with our clinical data, with a DSC (mean±1 STD) for the right femoral head of 0.55±0.06 (n=53) increasing to 0.91±0.02 (n=10) and mean Hausdorff (mm) decreasing from 55±7 (n=53) to 4±1 (n=10) (similar results for the left femoral head). The deviation in femoral head compared to the RaySearch and MVision original models occurred due to a difference in the femoral head segmentation guideline in the clinic specific data, see Figure 2. Time recording of manual delineation was 13 minutes compared to 0.5 minutes (RaySearch) and 1.4 minutes (MVision) for the AI models, manual correction not included.ConclusionBoth AI models demonstrate good segmentation performance for bladder and rectum. Clinic specific training data (or data that complies to the clinic specific delineation guideline) might be necessary to achieve segmentation results in accordance to the clinical specific standard for some anatomical structures, such as the femoral heads in our case. The time saving was around 90%, not including manual correction

Feasibility of Pencil Beam Scanned Intensity Modulated Proton Therapy in Breath-hold for Locally Advanced Non-Small Cell Lung Cancer.

PURPOSE We evaluated the feasibility of treating patients with locally advanced non-small cell lung cancer (NSCLC) with pencil beam scanned intensity modulated proton therapy (IMPT) in breath-hold. METHODS AND MATERIALS Fifteen NSCLC patients who had previously received 66 Gy in 33 fractions with image guided photon radiation therapy were included in the present simulation study. In addition to a planning breath-hold computed tomography (CT) scan before the treatment start, a median of 6 (range 3-9) breath-hold CT scans per patient were acquired prospectively throughout the radiation therapy course. Three-field IMPT plans were constructed using the planning breath-hold CT scan, and the four-dimensional dose distributions were simulated, with consideration of both patient intra- and interfraction motion, in addition to dynamic treatment delivery. RESULTS The median clinical target volume receiving 95% of the prescribed dose was 99.8% and 99.7% for the planned and simulated dose distributions, respectively. For 3 patients (20%), the dose degradation was >5%, and plan adjustment was needed. Dose degradation correlated significantly with the change in water-equivalent path lengths (P<.01) in terms of the percentage of voxels with 3-mm or more undershoot on repeat CT scans. The dose to the organs at risk was similar for the planned and simulated dose distributions. Three or fewer breath-holds per field would be required for 12 of the 15 patients, which was clinically feasible. CONCLUSIONS For 9 of 15 NSCLC patients, IMPT in breath-hold was both dosimetrically robust and feasible to deliver regarding the treatment time. Three patients would have required plan adaption to meet the dosimetric criteria. The change in water-equivalent path length is an indicator of plan robustness and should be considered for the selection of patients for whom the plan would require adaptation

Daily Adaptive Proton Therapy : Is it Appropriate to Use Analytical Dose Calculations for Plan Adaption?

Purpose: The accuracy of analytical dose calculations (ADC) and dose uncertainties resulting from anatomical changes are both limiting factors in proton therapy. For the latter, rapid plan adaption is necessary; for the former, Monte Carlo (MC) approaches are increasingly recommended. These, however, are inherently slower than analytical approaches, potentially limiting the ability to rapidly adapt plans. Here, we compare the clinical relevance of uncertainties resulting from both. Methods and Materials: Five patients with non-small cell lung cancer with up to 9 computed tomography (CT) scans acquired during treatment and five paranasal (head and neck) patients with 10 simulated anatomical changes (sinus filling) were analyzed. On the initial planning CT scans, treatment plans were optimized and calculated using an ADC and then recalculated with MC. Additionally, all plans were recalculated (non-adapted) and reoptimized (adapted) on each repeated CT using the same ADC as for the initial plan, and the resulting dose distributions were compared. Results: When comparing analytical and MC calculations in the initial treatment plan and averaged over all patients, 94.2% (non-small cell lung cancer) and 98.5% (head and neck) of voxels had differences <±5%, and only minor differences in clinical target volume (CTV) V95 (average <2%) were observed. In contrast, when recalculating nominal plans on the repeat (anatomically changed) CT scans, CTV V95 degraded by up to 34%. Plan adaption, however, restored CTV V95 differences between adapted and nominal plans to <0.5%. Adapted organ-at-risk doses remained the same or improved. Conclusions: Dose degradations caused by anatomic changes are substantially larger than uncertainties introduced by the use of analytical instead of MC dose calculations. Thus, if the use of analytical calculations can enable more rapid and efficient plan adaption than MC approaches, they can and should be used for plan adaption for these patient groups

Impact of beam angle choice on pencil beam scanning breath-hold proton therapy for lung lesions

<p><b>Introduction:</b> The breath-hold technique inter alia has been suggested to mitigate the detrimental effect of motion on pencil beam scanned (PBS) proton therapy dose distributions. The aim of this study was to evaluate the robustness of incident proton beam angles to day-to-day anatomical variations in breath-hold.</p> <p><b>Materials and methods:</b> Single field PBS plans at five degrees increments in the transversal plane were made and water-equivalent path lengths (WEPLs) were derived on the planning breath-hold CT (BHCT) for 30 patients diagnosed with locally-advanced non-small cell lung cancer (NSCLC), early stage NSCLC or lung metastasis. Our treatment planning system was subsequently used to recalculate the plans and derive WEPL on a BHCT scan acquired at the end of the treatment. Changes to the V_95%, D₉₅ and mean target dose were evaluated.</p> <p><b>Results:</b> The difference in WEPL as a function of the beam angle was highly patient specific, with a median of 3.3 mm (range: 0.0–41.1 mm). Slightly larger WEPL differences were located around the lateral or lateral anterior/posterior beam angles. Linear models revealed that changes in dose were associated to the changes in WEPL and the tumor baseline shift (<i>p</i> < 0.05).</p> <p><b>Conclusions:</b> WEPL changes and tumor baseline shift can serve as reasonable surrogates for dosimetric uncertainty of the target coverage and are well-suited for routine evaluation of plan robustness. The two lateral beam angles are not recommended to use for PBS proton therapy of lung cancer patients treated in breath-hold, due to the poor robustness for several of the patients evaluated.</p