Automated and robust organ segmentation for 3D-based internal dose calculation

Abstract Purpose In this work, we address image segmentation in the scope of dosimetry using deep learning and make three main contributions: (a) to extend and optimize the architecture of an existing convolutional neural network (CNN) in order to obtain a fast, robust and accurate computed tomography (CT)-based organ segmentation method for kidneys and livers; (b) to train the CNN with an inhomogeneous set of CT scans and validate the CNN for daily dosimetry; and (c) to evaluate dosimetry results obtained using automated organ segmentation in comparison with manual segmentation done by two independent experts. Methods We adapted a performant deep learning approach using CT-images to delineate organ boundaries with sufficiently high accuracy and adequate processing time. The segmented organs were consequently used as binary masks for further convolution with a point spread function to retrieve the activity values from quantitatively reconstructed SPECT images for “volumetric”/3D dosimetry. The resulting activities were used to perform dosimetry calculations with the kidneys as source organs. Results The computational expense of the algorithm was sufficient for clinical daily routine, required minimum pre-processing and performed with acceptable accuracy a Dice coefficient of $$93\%$$ 93 % for liver segmentation and of $$94\%$$ 94 % for kidney segmentation, respectively. In addition, kidney self-absorbed doses calculated using automated segmentation differed by $$7\%$$ 7 % from dosimetry performed by two medical physicists in 8 patients. Conclusion The proposed approach may accelerate volumetric dosimetry of kidneys in molecular radiotherapy with 177Lu-labelled radiopharmaceuticals such as 177Lu-DOTATOC. However, even though a fully automated segmentation methodology based on CT images accelerates organ segmentation and performs with high accuracy, it does not remove the need for supervision and corrections by experts, mostly due to misalignments in the co-registration between SPECT and CT images. Trial registration EudraCT, 2016-001897-13. Registered 26.04.2016, www.clinicaltrialsregister.eu/ctr-search/search?query=2016-001897-13

Explainable AI to improve acceptance of convolutional neural networks for automatic classification of dopamine transporter SPECT in the diagnosis of clinically uncertain parkinsonian syndromes

Purpose!#!Deep convolutional neural networks (CNN) provide high accuracy for automatic classification of dopamine transporter (DAT) SPECT images. However, CNN are inherently black-box in nature lacking any kind of explanation for their decisions. This limits their acceptance for clinical use. This study tested layer-wise relevance propagation (LRP) to explain CNN-based classification of DAT-SPECT in patients with clinically uncertain parkinsonian syndromes.!##!Methods!#!The study retrospectively included 1296 clinical DAT-SPECT with visual binary interpretation as 'normal' or 'reduced' by two experienced readers as standard-of-truth. A custom-made CNN was trained with 1008 randomly selected DAT-SPECT. The remaining 288 DAT-SPECT were used to assess classification performance of the CNN and to test LRP for explanation of the CNN-based classification.!##!Results!#!Overall accuracy, sensitivity, and specificity of the CNN were 95.8%, 92.8%, and 98.7%, respectively. LRP provided relevance maps that were easy to interpret in each individual DAT-SPECT. In particular, the putamen in the hemisphere most affected by nigrostriatal degeneration was the most relevant brain region for CNN-based classification in all reduced DAT-SPECT. Some misclassified DAT-SPECT showed an 'inconsistent' relevance map more typical for the true class label.!##!Conclusion!#!LRP is useful to provide explanation of CNN-based decisions in individual DAT-SPECT and, therefore, can be recommended to support CNN-based classification of DAT-SPECT in clinical routine. Total computation time of 3 s is compatible with busy clinical workflow. The utility of 'inconsistent' relevance maps to identify misclassified cases requires further investigation

32nd International Austrian Winter Symposium : Zell am See, the Netherlands. 20-23 January 2016.

Table of contentsA1 68Ga-PSMA PET/CT in staging and restaging of Prostate Cancer Patients: comparative study with 18F-Choline PET/CTW Langsteger, A Rezaee, W Loidl, HS Geinitz, F Fitz, M Steinmair, G Broinger, L Pallwien-Prettner, M BeheshtiA2 F18 Choline PET - CT: an accurate diagnostic tool for the detection of parathyroid adenoma?L Imamovic, M Beheshti, G Rendl, D Hackl, O Tsybrovsky, M Steinmair, K Emmanuel, F Moinfar, C Pirich, W LangstegerA3 [18F]Fluoro-DOPA-PET/CT in the primary diagnosis of medullary thyroid carcinomaA Bytyqi, G Karanikas, M Mayerhöfer, O Koperek, B Niederle, M HartenbachA4 Variations of clinical PET/MR operations: An international survey on the clinical utilization of PET/MRIT Beyer, K Herrmann, J CzerninA5 Standard Dixon-based attenuation correction in combined PET/MRI: Reproducibility and the possibility of Lean body mass estimationI Rausch, P Rust, MD DiFranco, M Lassen, A Stadlbauer, ME Mayerhöfer, M Hartenbach, M Hacker, T BeyerA6 High resolution digital FDG PET/MRI imaging for assessment of ACL graft viabilityK Binzel, R Magnussen, W Wei, MU Knopp, DC Flanigan, C Kaeding, MV KnoppA7 Using pre-existing hematotoxicity as predictor for severe side effects and number of treatment cycles of Xofigo therapyA Leisser, M Nejabat, M Hartenbach, G Kramer, M Krainer, M Hacker, A HaugA8 QDOSE - comprehensive software solution for internal dose assessmentWencke Lehnert, Karl Schmidt, Sharok Kimiaei, Marcus Bronzel, Andreas KlugeA9 Clinical impact of Time-of-Flight on next-generation digital PET imaging of Yttrium-90 radioactivity following liver radioembolizationCL Wright, K Binzel, J Zhang, Evan Wuthrick, Piotr Maniawski, MV KnoppA10 Snakes in patients! Lessons learned from programming active contours for automated organ segmentationM Blaickner, E Rados, A Huber, M Dulovits, H Kulkarni, S Wiessalla, C Schuchardt, RP Baum, B Knäusl, D GeorgA11 Influence of a genetic polymorphism on brain uptake of the dual ABCB1/ABCG2 substrate [11C]tariquidarM Bauer, B Wulkersdorfer, W Wadsak, C Philippe, H Haslacher, M Zeitlinger, O LangerA12 Outcome prediction of temporal lobe epilepsy surgery from P-glycoprotein activity. Pooled analysis of (R)-[11C]-verapamil PET data from two European centresM Bauer, M Feldmann, R Karch, W Wadsak, M Zeitlinger, MJ Koepp, M-C Asselin, E Pataraia, O LangerA13 In-vitro and in-vivo characterization of [18F]FE@SNAP and derivatives for the visualization of the melanin concentrating hormone receptor 1M Zeilinger, C Philippe, M Dumanic, F Pichler, J Pilz, M Hacker, W Wadsak, M MitterhauserA14 Reducing time in quality control leads to higher specific radioactivity of short-lived radiotracersL Nics, B Steiner, M Hacker, M Mitterhauser, W WadsakA15 In vitro 11C-erlotinib binding experiments in cancer cell lines with epidermal growth factor receptor mutationsA Traxl, Thomas Wanek, Kushtrim Kryeziu, Severin Mairinger, Johann Stanek, Walter Berger, Claudia Kuntner, Oliver LangerA16 7-[11C]methyl-6-bromopurine, a PET tracer to measure brain Mrp1 function: radiosynthesis and first PET evaluation in miceS Mairinger, T Wanek, A Traxl, M Krohn, J Stanek, T Filip, M Sauberer, C Kuntner, J Pahnke, O LangerA17 18F labeled azidoglucose derivatives as "click" agents for pretargeted PET imagingD Svatunek, C Denk, M Wilkovitsch, T Wanek, T Filip, C Kuntner-Hannes, J Fröhlich, H MikulaA18 Bioorthogonal tools for PET imaging: development of radiolabeled 1,2,4,5-TetrazinesC Denk, D Svatunek, T Wanek, S Mairinger, J Stanek, T Filip, J Fröhlich, H Mikula, C Kuntner-HannesA19 Preclinical evaluation of [18F]FE@SUPPY- a new PET-tracer for oncologyT Balber, J Singer, J Fazekas, C Rami-Mark, N Berroterán-Infante, E Jensen-Jarolim, W Wadsak, M Hacker, H Viernstein, M MitterhauserA20 Investigation of Small [18F]-Fluoroalkylazides for Rapid Radiolabeling and In Vivo Click ChemistryC Denk, D Svatunek, B Sohr, H Mikula, J Fröhlich, T Wanek, C Kuntner-Hannes, T FilipA21 Microfluidic 68Ga-radiolabeling of PSMA-HBED-CC using a flow-through reactorS Pfaff, C Philippe, M Mitterhauser, M Hartenbach, M Hacker, W WadsakA22 Influence of 24-nor-ursodeoxycholic acid on hepatic disposition of [18F]ciprofloxacin measured with positron emission tomographyT Wanek, E Halilbasic, M Visentin, S Mairinger, B Stieger, C Kuntner, M Trauner, O LangerA23 Automated 18F-flumazenil production using chemically resistant disposable cassettesP Lam, M Aistleitner, R Eichinger, C ArtnerA24 Similarities and differences in the synthesis and quality control of 177Lu-DOTA-TATE, 177Lu -HA-DOTA-TATE and 177Lu-DOTA-PSMA (PSMA-617)H Eidherr, C Vraka, A Haug, M Mitterhauser, L Nics, M Hartenbach, M Hacker, W WadsakA25 68Ga- and 177Lu-labelling of PSMA-617H Kvaternik, R Müller, D Hausberger, C Zink, RM AignerA26 Radiolabelling of liposomes with 67Ga and biodistribution studies after administration by an aerosol inhalation systemU Cossío, M Asensio, A Montes, S Akhtar, Y te Welscher, R van Nostrum, V Gómez-Vallejo, J LlopA27 Fully automated quantification of DaTscan SPECT: Integration of age and gender differencesF VandeVyver, T Barclay, N Lippens, M TrochA28 Lesion-to-background ratio in co-registered 18F-FET PET/MR imaging - is it a valuable tool to differentiate between low grade and high grade brain tumor?L Hehenwarter, B Egger, J Holzmannhofer, M Rodrigues-Radischat, C PirichA29 [11C]-methionine PET in gliomas - a retrospective data analysis of 166 patientsN Pötsch, I Rausch, D Wilhelm, M Weber, J Furtner, G Karanikas, A Wöhrer, M Mitterhauser, M Hacker, T Traub-WeidingerA30 18F-Fluorocholine versus 18F-Fluorodeoxyglucose for PET/CT imaging in patients with relapsed or progressive multiple myeloma: a pilot studyT Cassou-Mounat, S Balogova, V Nataf, M Calzada, V Huchet, K Kerrou, J-Y Devaux, M Mohty, L Garderet, J-N TalbotA31 Prognostic benefit of additional SPECT/CT in sentinel lymph node mapping of breast cancer patientsS Stanzel, G Pregartner, T Schwarz, V Bjelic-Radisic, B Liegl-Atzwanger, R AignerA32 Evaluation of diagnostic value of TOF-18F-FDG PET/CT in patients with suspected pancreatic cancerS Stanzel, F Quehenberger, RM AignerA33 New quantification method for diagnosis of primary hyperpatahyroidism lesions and differential diagnosis vs thyropid nodular disease in dynamic scintigraphyA Koljević Marković, Milica Janković, V Miler Jerković, M Paskaš, G Pupić, R Džodić, D PopovićA34 A rare case of diffuse pancreatic involvement in patient with merkel cell carcinoma detected by 18F-FDGMC Fornito, D FamiliariA35 TSH-stimulated 18F-FDG PET/CT in the diagnosis of recurrent/metastatic radioiodine-negative differentiated thyroid carcinomas in patients with various thyroglobuline levelsP Koranda, H Polzerová, I Metelková, L Henzlová, R Formánek, E Buriánková, M KamínekA36 Breast Dose from lactation following I131 treatmentWH Thomson, C LewisA37 A new concept for performing SeHCAT studies with the gamma cameraWH Thomson, J O'Brien, G James, A NotghiA38 Whole body F-18-FDG-PET and tuberculosis: sensitivity compared to x-ray-CTH Huber, I Stelzmüller, R Wunn, M Mandl, F Fellner, B Lamprecht, M GabrielA39 Emerging role 18F-FDG PET-CT in the diagnosis and follow-up of the infection in heartware ventricular assist system (HVAD)MC Fornito, G LeonardiA40 Validation of Poisson resampling softwareWH Thomson, J O'Brien, G JamesA41 Protection of PET nuclear medicine personnel: problems in satisfying dose limit requirementsJ Hudzietzová, J Sabol, M Fülöp