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

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Gorgisyan, JennyLund University,Lunds universitet,Medicinsk strålningsfysik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Medical Radiation Physics, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital (author)

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

Article/chapterEnglish2022

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2022

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LIBRIS-ID:oai:lup.lub.lu.se:826ceeaa-cdff-49bd-a661-60033a1ad028
https://lup.lub.lu.se/record/826ceeaa-cdff-49bd-a661-60033a1ad028URI

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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.

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Bengtsson, IdaSkåne University Hospital (author)
Lempart, MichaelLund University,Lunds universitet,Medicinsk strålningsfysik, Malmö,Forskargrupper vid Lunds universitet,Medical Radiation Physics, Malmö,Lund University Research Groups,Skåne University Hospital(Swepub:lu)mi5751le (author)
Lerner, MinnaLund University,Lunds universitet,Medicinsk strålningsfysik, Malmö,Forskargrupper vid Lunds universitet,Medical Radiation Physics, Malmö,Lund University Research Groups,Skåne University Hospital(Swepub:lu)mi7225ah (author)
Wieslander, ElinoreLund University,Lunds universitet,Medicinsk strålningsfysik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Medical Radiation Physics, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Skåne University Hospital(Swepub:lu)radf-ewi (author)
Alkner, SaraLund University,Lunds universitet,Patologi, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Onkologi övergripande,Sektion I,Institutionen för kliniska vetenskaper, Lund,Pathology, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Oncology corporate,Section I,Department of Clinical Sciences, Lund,Skåne University Hospital(Swepub:lu)med-srt (author)
Jamtheim Gustafsson, ChristianLund University,Lunds universitet,Medicinsk strålningsfysik, Lund,Sektion V,Institutionen för kliniska vetenskaper, Lund,Medicinska fakulteten,Medicinsk strålningsfysik, Malmö,Forskargrupper vid Lunds universitet,Radiotherapy Physics,Medical Radiation Physics, Lund,Section V,Department of Clinical Sciences, Lund,Faculty of Medicine,Medical Radiation Physics, Malmö,Lund University Research Groups,Skåne University Hospital(Swepub:lu)med-cgf (author)
Medicinsk strålningsfysik, LundSektion V (creator_code:org_t)

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