title: Computer-aided diagnosis in two-phase 201Tl-SPECT of thoracic lesions.
abstract: OBJECTIVE
  The retention index, a traditionally quantitative analysis of two-phase (201)Tl single photon emission computed tomography (SPECT) of the chest, is manually calculated by experienced physicians from comparable 2-D ROI. However, a 3-D ROI would provide more information than a 2-D ROI extracted from a single frame of SPECT. We propose a new diagnostic system, computer-aided diagnosis (CAD), to automatically detect suspicious lesions as 3-D objects on chest (201)Tl-SPECT, and assist the physician in interpreting these images.
  
  
  METHODS
  Seventy patients with thoracic lesions and confirmed diagnoses were enrolled to test this automatic CAD system. The reliability of the CAD system in detecting lesions as 3-D objects was compared to the 2-D ROI of (201)Tl-SPECT found by the manually visualized method. Furthermore, we also proposed a novel index, the retention index using the heart (RIH), to differentiate high retention (slow clearance, increasing target to heart ratio) as a criterion for a malignant lesion, from low retention (faster clearance, small or no increase of the target to heart ratio) for benign lesions.
  
  
  RESULTS
  The CAD system can achieve a detection rate of 100% in automatically searching for thoracic lesions in (201)Tl-SPECT. In diagnostic performance, the CAD system with the RIH of comparable 3-D objects has an area under the ROC curve of 0.86, higher than the 0.78 of the traditional RI method (p=0.198).
  
  
  CONCLUSIONS
  The CAD system of two-phase (201)Tl-SPECT is a promising tool for detecting and diagnosing thoracic lesions with a diagnostic accuracy of 0.81.
authors.affiliation: Department of Internal Medicine, China Medical University Hospital, Taichung, Taiwan.
authors.forename: Y-H
authors.initials: YH
authors.lastname: Yu
authors.forename: R-F
authors.initials: RF
authors.lastname: Chang
authors.forename: W-C
authors.initials: WC
authors.lastname: Shen
authors.forename: D-K
authors.initials: DK
authors.lastname: Lin
authors.forename: S-S
authors.initials: SS
authors.lastname: Sun
authors.forename: C-Y
authors.initials: CY
authors.lastname: Tu
authors.forename: K-L
authors.initials: KL
authors.lastname: Chiu
authors.forename: W-H
authors.initials: WH
authors.lastname: Hsu
mesh_terms: D000230:Adenocarcinoma / Q000000981:diagnostic imaging; D000368:Aged; D000369:Aged, 80 and over; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging; D002294:Carcinoma, Squamous Cell / Q000000981:diagnostic imaging; D003936:Diagnosis, Computer-Assisted; D005260:Female; D006801:Humans; D008171:Lung Diseases / Q000000981:diagnostic imaging / Q000382:microbiology; D008175:Lung Neoplasms / Q000000981:diagnostic imaging*; D008297:Male; D008875:Middle Aged; D009164:Mycobacterium Infections / Q000000981:diagnostic imaging*; D013902:Radiography, Thoracic; D011868:Radioisotopes; D013794:Thallium Radioisotopes; D015899:Tomography, Emission-Computed, Single-Photon; D014376:Tuberculosis / Q000000981:diagnostic imaging*
chemical_list: D011868:Radioisotopes; D013794:Thallium Radioisotopes