title: [Automated detection and volumetric segmentation of the spleen in CT scans].
abstract: OBJECTIVE
  To introduce automated detection and volumetric segmentation of the spleen in spiral CT scans with the THESEUS-MEDICO software. The consistency between automated volumetry (aV), estimated volume determination (eV) and manual volume segmentation (mV) was evaluated.
  
  
  METHODS
  Retrospective evaluation of the CAD system based on methods like "marginal space learning" and "boosting algorithms". 3 consecutive spiral CT scans (thoraco-abdominal; portal-venous contrast agent phase; 1 or 5 mm slice thickness) of 15 consecutive lymphoma patients were included. The eV: 30 cm³ + 0.58 (width × length × thickness of the spleen) and the mV as the reference standard were determined by an experienced radiologist.
  
  
  RESULTS
  The aV could be performed in all CT scans within 15.2 (± 2.4) seconds. The average splenic volume measured by aV was 268.21 ± 114.67 cm³ compared to 281.58 ± 130.21 cm³ in mV and 268.93 ± 104.60 cm³ in eV. The correlation coefficient was 0.99 (coefficient of determination (R²) = 0.98) for aV and mV, 0.91 (R² = 0.83) for mV and eV and 0.91 (R² = 0.82) for aV and eV. There was an almost perfect correlation of the changes in splenic volume measured with the new aV and mV (0.92; R² = 0.84), mV and eV (0.95; R² = 0.91) and aV and eV (0.83; R² = 0.69) between two time points.
  
  
  CONCLUSIONS
  The automated detection and volumetric segmentation software rapidly provides an accurate measurement of the splenic volume in CT scans. Knowledge about splenic volume and its change between two examinations provides valuable clinical information without effort for the radiologist.
authors.affiliation: Radiologisches Institut, Universitätsklinikum Erlangen. matthias.hammon@ukerlangen.de
authors.forename: M
authors.initials: M
authors.lastname: Hammon
authors.forename: P
authors.initials: P
authors.lastname: Dankerl
authors.forename: M
authors.initials: M
authors.lastname: Kramer
authors.forename: S
authors.initials: S
authors.lastname: Seifert
authors.forename: A
authors.initials: A
authors.lastname: Tsymbal
authors.forename: M J
authors.initials: MJ
authors.lastname: Costa
authors.forename: R
authors.initials: R
authors.lastname: Janka
authors.forename: M
authors.initials: M
authors.lastname: Uder
authors.forename: A
authors.initials: A
authors.lastname: Cavallaro
mesh_terms: D000328:Adult; D000368:Aged; D003287:Contrast Media; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D005260:Female; D006801:Humans; D021621:Imaging, Three-Dimensional / Q000379:methods*; D008223:Lymphoma / Q000000981:diagnostic imaging* / Q000473:pathology; D008297:Male; D008875:Middle Aged; D009367:Neoplasm Staging; D009929:Organ Size; D010363:Pattern Recognition, Automated; D012189:Retrospective Studies; D012984:Software; D054894:Spiral Cone-Beam Computed Tomography / Q000379:methods*; D013154:Spleen / Q000000981:diagnostic imaging*
chemical_list: D003287:Contrast Media