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SU‐E‐J‐186: Automated SPECT‐Based Segmentation for Quality Assurance of CT‐Delineated Tumor Volumes for 131I Tositumomab Therapy of Non‐Hodgkins Lymphoma
Author(s) -
Thorwarth R,
Dewaraja Y,
Wilderman S,
Kaminski M,
Avram A,
Roberson P
Publication year - 2013
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.4814398
Subject(s) - nuclear medicine , imaging phantom , quality assurance , scanner , radioimmunotherapy , calibration , segmentation , volume (thermodynamics) , medicine , mathematics , physics , artificial intelligence , computer science , monoclonal antibody , statistics , pathology , external quality assessment , immunology , quantum mechanics , antibody
Purpose: CT segmentation of tumor volumes suffers from many error sources which can impact the calculation of absorbed dose and 4D bio‐effect modeling. Determination of gross tumor volumes from SPECT scans of anti‐CD20 monoclonal antibody uptake was explored as a quality assurance step. Investigated were two count threshold methods (optimal and constant threshold) and one edge detection method. Methods: Patient data were selected from a dataset of refractory non‐Hodgkins lymphoma studies of 131 I radioimmunotherapy. The calibration phantom geometry consisted of seven (1 mL to 95 mL) spheres in an elliptical tank. The background activity was 5 mCi with sphere activities adjusted for an approximate 6:1 concentration ratio. Phantom scans were repeated with no background activity. The patient and calibration sphere data were collected on a Siemens Symbia TruePoint SPECT/CT scanner and reconstructed with in‐house OS‐EM software. The optimal threshold technique used a calibration of threshold vs volume. The constant threshold method (40% and 60% thresholds explored) used a calibration of volume correction factor vs volume. The edge detection method used the Canny algorithm to map edges and determine an edge correction factor. Results: Challenges included 1) resolving tumor volume from nearby significant uptake objects (organs, vessels or other tumors) and 2) identifying volume for large tumors with significantly non‐uniform activity. A constant threshold of 60% with background and volume correction performed best. The determined volumes from patient data were 0.70–0.73 (>12mL) or 0.44‐0.69 (<12mL) of the CT‐delineated volumes. The lower than unity values were attributed to non‐sharp activity boundaries. A priori volume estimates were required for object radii less than the scanner resolution (i.e. <12mL). Conclusion: The constant threshold method can be used to check the validity of CT‐delineated tumor volumes. An additional volume correction factor is required to account for non‐sharp tumor edges. Dr M Kaminski receives research support from GlaxoSmithKline and royalties from Bexxar.