title: Implementation and Performance of Automated Software for Computing Right-to-Left Ventricular Diameter Ratio From Computed Tomography Pulmonary Angiography Images.
abstract: OBJECTIVE
  The aim of this study was to prospectively test the performance and potential for clinical integration of software that automatically calculates the right-to-left ventricular (RV/LV) diameter ratio from computed tomography pulmonary angiography images.
  
  
  METHODS
  Using 115 computed tomography pulmonary angiography images that were positive for acute pulmonary embolism, we prospectively evaluated RV/LV ratio measurements that were obtained as follows: (1) completely manual measurement (reference standard), (2) completely automated measurement using the software, and (3 and 4) using a customized software interface that allowed 2 independent radiologists to manually adjust the automatically positioned calipers.
  
  
  RESULTS
  Automated measurements underestimated (P < 0.001) the reference standard (1.09 [0.25] vs1.03 [0.35]). With manual correction of the automatically positioned calipers, the mean ratio became closer to the reference standard (1.06 [0.29] by read 1 and 1.07 [0.30] by read 2), and the correlation improved (r = 0.675 to 0.872 and 0.887). The mean time required for manual adjustment (37 [20] seconds) was significantly less than the time required to perform measurements entirely manually (100 [23] seconds).
  
  
  CONCLUSIONS
  Automated CT RV/LV diameter ratio software shows promise for integration into the clinical workflow for patients with acute pulmonary embolism.
authors.affiliation: From the *Applied Imaging Science Laboratory, Department of Radiology, Brigham and Women's Hospital, Boston, MA; †Department of Radiology, Juntendo University, Tokyo, Japan; ‡Department of Radiology, University of Texas Southwestern Medical Center, Dallas, TX; §Biomedical Image Technologies, Universidad Politécnica de Madrid & CIBER-BBN, Madrid, Spain; ∥Surgical Planning Laboratory, Brigham and Women's Hospital, Boston; and ¶Madrid-MIT M+Visión Consortium, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA; and #Department of Radiology, The Ottawa Hospital and Ottawa University, Ottawa, Ontario, Canada.
authors.forename: Kanako K
authors.initials: KK
authors.lastname: Kumamaru
authors.forename: Elizabeth
authors.initials: E
authors.lastname: George
authors.forename: Ayaz
authors.initials: A
authors.lastname: Aghayev
authors.forename: Sachin S
authors.initials: SS
authors.lastname: Saboo
authors.forename: Ashish
authors.initials: A
authors.lastname: Khandelwal
authors.forename: Sara
authors.initials: S
authors.lastname: Rodríguez-López
authors.forename: Tianrun
authors.initials: T
authors.lastname: Cai
authors.forename: Daniel
authors.initials: D
authors.lastname: Jiménez-Carretero
authors.forename: Raúl San José
authors.initials: RS
authors.lastname: Estépar
authors.forename: Maria J
authors.initials: MJ
authors.lastname: Ledesma-Carbayo
authors.forename: Germán
authors.initials: G
authors.lastname: González
authors.forename: Frank J
authors.initials: FJ
authors.lastname: Rybicki
mesh_terms: D000465:Algorithms; D000072226:Computed Tomography Angiography; D006352:Heart Ventricles / Q000033:anatomy & histology / Q000000981:diagnostic imaging*; D006801:Humans; D000069550:Machine Learning; D008875:Middle Aged; D015588:Observer Variation; D009929:Organ Size; D010363:Pattern Recognition, Automated / Q000379:methods*; D011651:Pulmonary Artery / Q000000981:diagnostic imaging*; D011655:Pulmonary Embolism / Q000000981:diagnostic imaging* / Q000473:pathology; D011856:Radiographic Image Enhancement; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D012984:Software