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The curved planar reformation (CPR) method re-samples the vascular structures along the vessel centerline to generate
longitudinal cross-section views. The CPR technique has been commonly used in coronary CTA workstation to facilitate
radiologists’ visual assessment of coronary diseases, but has not yet been used for pulmonary vessel analysis in CTPA
due to the complicated tree structures and the vast network of pulmonary vasculature. In this study, a new curved planar
reformation and optimal path tracing (CROP) method was developed to facilitate feature extraction and false positive
(FP) reduction and improve our PE detection system. PE candidates are first identified in the segmented pulmonary
vessels at prescreening. Based on Dijkstra’s algorithm, the optimal path (OP) is traced from the pulmonary trunk
bifurcation point to each PE candidate. The traced vessel is then straightened and a reformatted volume is generated
using CPR. Eleven new features that characterize the intensity, gradient, and topology are extracted from the PE
candidate in the CPR volume and combined with the previously developed 9 features to form a new feature space for FP
classification. With IRB approval, CTPA of 59 PE cases were retrospectively collected from our patient files (UM set)
and 69 PE cases from the PIOPED II data set with access permission. 595 and 800 PEs were manually marked by
experienced radiologists as reference standard for the UM and PIOPED set, respectively. At a test sensitivity of 80%, the
average FP rate was improved from 18.9 to 11.9 FPs/case with the new method for the PIOPED set when the UM set
was used for training. The FP rate was improved from 22.6 to 14.2 FPs/case for the UM set when the PIOPED set was
used for training. The improvement in the free response receiver operating characteristic (FROC) curves was statistically
significant (p<0.05) by JAFROC analysis, indicating that the new features extracted from the CROP method are useful
for FP reduction.
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