Variabilities in Reference Standard by Radiologists and Performance Assessment in Detection of Pulmonary Embolism in CT Pulmonary Angiography.

Annotating lesion locations by radiologists' manual marking is a key step to provide reference standard for the training and testing of a computer-aided detection system by supervised machine learning. Inter-reader variability is not uncommon in readings even by expert radiologists. This study evaluated the variability of the radiologist-identified pulmonary emboli (PEs) to demonstrate the importance of improving the reliability of the reference standard by a multi-step process for performance evaluation. In an initial reading of 40 CTPA PE cases, two experienced thoracic radiologists independently marked the PE locations. For markings from the two radiologists that did not agree, each radiologist re-read the cases independently to assess the discordant markings. Finally, for markings that still disagreed after the second reading, the two radiologists read together to reach a consensus. The variability of radiologists was evaluated by analyzing the agreement between two radiologists. For the 40 cases, 475 and 514 PEs were identified by radiologists R1 and R2 in the initial independent readings, respectively. For a total of 545 marks by the two radiologists, 81.5% (444/545) of the marks agreed but 101 marks in 36 cases differed. After consensus, 65 (64.4%) and 36 (35.6%) of the 101 marks were determined to be true PEs and false positives (FPs), respectively. Of these, 48 and 17 were false negatives (FNs) and 14 and 22 were FPs by R1 and R2, respectively. Our study demonstrated that there is substantial variability in reference standards provided by radiologists, which impacts the performance assessment of a lesion detection system. Combination of multiple radiologists' readings and consensus is needed to improve the reliability of a reference standard.

Acute pulmonary embolism.

CT pulmonary angiography has become a first-line imaging test for evaluation of PE because of its high accuracy, ease of use, and ready availability. PIOPED II supports the use of multidetector CT as a first-line test especially in outpatients. Technological advances continue to evolve, and with refinements in technology, we will continue to optimize imaging for PE detection. lonizing radiation remains a concern particularly in the young and in pregnant patients, and methods to decrease these are being advocated. SPECT V/Q may play a bigger role in PE diagnosis in the future and the role of MR is yet to be determined in the PIOPED ll study, with the potential of solving some of the issues regarding radiation in a select group of patients.

Best-Quality Vessel Identification Using Vessel Quality Measure in Multiple-Phase Coronary CT Angiography.

The detection of stenotic plaques strongly depends on the quality of the coronary arterial tree imaged with coronary CT angiography (cCTA). However, it is time consuming for the radiologist to select the best-quality vessels from the multiple-phase cCTA for interpretation in clinical practice. We are developing an automated method for selection of the best-quality vessels from coronary arterial trees in multiple-phase cCTA to facilitate radiologist's reading or computerized analysis. Our automated method consists of vessel segmentation, vessel registration, corresponding vessel branch matching, vessel quality measure (VQM) estimation, and automatic selection of best branches based on VQM. For every branch, the VQM was calculated as the average radial gradient. An observer preference study was conducted to visually compare the quality of the selected vessels. 167 corresponding branch pairs were evaluated by two radiologists. The agreement between the first radiologist and the automated selection was 76% with kappa of 0.49. The agreement between the second radiologist and the automated selection was also 76% with kappa of 0.45. The agreement between the two radiologists was 81% with kappa of 0.57. The observer preference study demonstrated the feasibility of the proposed automated method for the selection of the best-quality vessels from multiple cCTA phases.

Thoracic central venous evaluation: comparison of first-pass direct versus delayed-phase indirect multidetector CT venography.

PURPOSE: The purpose was to compare first-pass and delayed-phase thoracic computed tomography (CT) venography for the evaluation of suspected central thoracic venous pathology. MATERIAL AND METHODS: CT images and medical records of all patients who underwent thoracic CT venography over a 5-year period were retrospectively reviewed. Both first-pass (18s) and delayed-phase (60s) venous images were obtained in all patients. The images were reviewed in random order by three readers using a semiquantitative visual grading scheme for image quality, including artifacts and the uniformity of venous enhancement. In addition, enhancement was quantitatively evaluated. The presence and type of venous pathology, and overall diagnostic confidence were recorded and compared. Reference verification was performed when available. RESULTS: Eighteen patients formed the study group, mean age 49.5years and 28% male. Dual-arm injection was successful in 72% of exams. All readers reported more streak artifacts on first-pass imaging than delayed imaging (72%-94% vs. 27%-44%, respectively; P<.05). First-pass imaging had significantly higher measured enhancement across all central venous segments than delayed imaging (mean HU range 212-906 HU vs. 173-414 HU; P<.05) but also had significantly more heterogeneous enhancement (mean S.D. range 75-1058 HU vs. 67-378 HU; P<.05). For overall diagnosis, reader agreement, accuracy, and confidence levels were higher for delayed-phase images (P<.05). CONCLUSION: Indirect thoracic CT venography using delayed-phase imaging alone may be sufficient for evaluating clinically suspected central venous abnormality.

Coronary CT angiography (cCTA): automated registration of coronary arterial trees from multiple phases.

Coronary computed tomography angiography (cCTA) is a commonly used imaging modality for the evaluation of coronary artery disease. cCTA is generally reconstructed in multiple cardiac phases because different coronary arteries may be better visualized in some phases than in others due to the periodic cardiac motion. We are developing an automated registration method for coronary arterial trees from multiple-phase cCTA that has potential application in building a 'best-quality' tree to facilitate image analysis and detection of stenotic plaques. Given the segmented left or right coronary arterial (LCA or RCA) trees from the multiple phases as input, the adjacent phase pairs, where displacements are relatively small, are registered by a specifically designed method based on a cubic B-spline with fast localized optimization (CBSO). For the phase pairs with large displacements, a global registration using an affine transform with quadratic terms and nonlinear simplex optimization (AQSO) is followed by a local registration using CBSO to refine the AQSO registered volumes. 26 LCA and 26 RCA trees with six cCTA phases from 26 patients were used for registration evaluation. The average distances for the tree pairs between the adjacent phases with small displacements before and after CBSO registration were 0.96  ±  0.79 and 0.76  ±  0.61 mm respectively for LCA, and 0.93  ±  0.97 and 0.64  ±  0.43 mm, respectively for RCA. The average distance differences before and after registration were statistically significant (p < 0.001) for both LCA and RCA trees. The average distances for the distant phases with large displacements before registration, after AQSO registration, and finally after the CBSO registration were 2.85  ±  1.46, 1.62  ±  0.76, and 0.97  ±  0.43 mm, respectively for LCA, and 4.03  ±  2.36, 2.18  ±  1.11, and 0.97  ±  0.44 mm, respectively for RCA. The average distance differences between every two consecutive stages of registration were statistically significant. The corresponding phases of LCA and RCA trees were aligned to an average of less than 1 mm, providing a basis for a best-quality tree construction.

Computerized detection of noncalcified plaques in coronary CT angiography: evaluation of topological soft gradient prescreening method and luminal analysis.

PURPOSE: The buildup of noncalcified plaques (NCPs) that are vulnerable to rupture in coronary arteries is a risk for myocardial infarction. Interpretation of coronary CT angiography (cCTA) to search for NCP is a challenging task for radiologists due to the low CT number of NCP, the large number of coronary arteries, and multiple phase CT acquisition. The authors conducted a preliminary study to develop machine learning method for automated detection of NCPs in cCTA. METHODS: With IRB approval, a data set of 83 ECG-gated contrast enhanced cCTA scans with 120 NCPs was collected retrospectively from patient files. A multiscale coronary artery response and rolling balloon region growing (MSCAR-RBG) method was applied to each cCTA volume to extract the coronary arterial trees. Each extracted vessel was reformatted to a straightened volume composed of cCTA slices perpendicular to the vessel centerline. A topological soft-gradient (TSG) detection method was developed to prescreen for NCP candidates by analyzing the 2D topological features of the radial gradient field surface along the vessel wall. The NCP candidates were then characterized by a luminal analysis that used 3D geometric features to quantify the shape information and gray-level features to evaluate the density of the NCP candidates. With machine learning techniques, useful features were identified and combined into an NCP score to differentiate true NCPs from false positives (FPs). To evaluate the effectiveness of the image analysis methods, the authors performed tenfold cross-validation with the available data set. Receiver operating characteristic (ROC) analysis was used to assess the classification performance of individual features and the NCP score. The overall detection performance was estimated by free response ROC (FROC) analysis. RESULTS: With our TSG prescreening method, a prescreening sensitivity of 92.5% (111/120) was achieved with a total of 1181 FPs (14.2 FPs/scan). On average, six features were selected during the tenfold cross-validation training. The average area under the ROC curve (AUC) value for training was 0.87 ± 0.01 and the AUC value for validation was 0.85 ± 0.01. Using the NCP score, FROC analysis of the validation set showed that the FP rates were reduced to 3.16, 1.90, and 1.39 FPs/scan at sensitivities of 90%, 80%, and 70%, respectively. CONCLUSIONS: The topological soft-gradient prescreening method in combination with the luminal analysis for FP reduction was effective for detection of NCPs in cCTA, including NCPs causing positive or negative vessel remodeling. The accuracy of vessel segmentation, tracking, and centerline identification has a strong impact on NCP detection. Studies are underway to further improve these techniques and reduce the FPs of the CADe system.

Computerized analysis of coronary artery disease: performance evaluation of segmentation and tracking of coronary arteries in CT angiograms.

PURPOSE: The authors are developing a computer-aided detection system to assist radiologists in analysis of coronary artery disease in coronary CT angiograms (cCTA). This study evaluated the accuracy of the authors' coronary artery segmentation and tracking method which are the essential steps to define the search space for the detection of atherosclerotic plaques. METHODS: The heart region in cCTA is segmented and the vascular structures are enhanced using the authors' multiscale coronary artery response (MSCAR) method that performed 3D multiscale filtering and analysis of the eigenvalues of Hessian matrices. Starting from seed points at the origins of the left and right coronary arteries, a 3D rolling balloon region growing (RBG) method that adapts to the local vessel size segmented and tracked each of the coronary arteries and identifies the branches along the tracked vessels. The branches are queued and subsequently tracked until the queue is exhausted. With Institutional Review Board approval, 62 cCTA were collected retrospectively from the authors' patient files. Three experienced cardiothoracic radiologists manually tracked and marked center points of the coronary arteries as reference standard following the 17-segment model that includes clinically significant coronary arteries. Two radiologists visually examined the computer-segmented vessels and marked the mistakenly tracked veins and noisy structures as false positives (FPs). For the 62 cases, the radiologists marked a total of 10191 center points on 865 visible coronary artery segments. RESULTS: The computer-segmented vessels overlapped with 83.6% (8520/10191) of the center points. Relative to the 865 radiologist-marked segments, the sensitivity reached 91.9% (795/865) if a true positive is defined as a computer-segmented vessel that overlapped with at least 10% of the reference center points marked on the segment. When the overlap threshold is increased to 50% and 100%, the sensitivities were 86.2% and 53.4%, respectively. For the 62 test cases, a total of 55 FPs were identified by radiologist in 23 of the cases. CONCLUSIONS: The authors' MSCAR-RBG method achieved high sensitivity for coronary artery segmentation and tracking. Studies are underway to further improve the accuracy for the arterial segments affected by motion artifacts, severe calcified and noncalcified soft plaques, and to reduce the false tracking of the veins and other noisy structures. Methods are also being developed to detect coronary artery disease along the tracked vessels.

Acute pulmonary embolism.

Evolving MDCT technology and high accuracy for pulmonary embolism detection has led to CT pulmonary angiography (CTPA) becoming a first-line imaging test. Rapid and accurate assessment for DVT and PE can be performed with a single test. Concerns remain regarding the radiation exposure incurred with CTPA and CT venography, especially in young patients. There are concerns also regarding radiation exposure in pregnancy and search for the best diagnostic test for PE in pregnancy. The increased detection of subsegmental emboli raises the question as to which emboli are significant and should be treated and which should be left alone. We review the current role of CT in the diagnosis of pulmonary embolism.