OBJECTIVE: The objective of our study was to compare the preoperative diagnostic accuracy of axial, multiplanar, and 3D MDCT images for evaluating congenital lung anomalies in pediatric patients and to assess the potential added diagnostic value of multiplanar and 3D MDCT images in this setting. MATERIALS AND METHODS: We used our hospital information system to identify all consecutive pediatric patients younger than 18 years who had undergone preoperative MDCT angiography and had a pathologically proven congenital lung anomaly between June 2005 and February 2010. Each MDCT examination was reviewed independently by two experienced pediatric radiologists for the types, location, associated mass effect, and associated anomalous vessels of congenital lung anomalies on axial, multiplanar, and 3D MDCT images. The final diagnosis was determined by surgical and pathologic findings. Diagnostic accuracy, confidence level of diagnosis (scale of 1-3: 1 = highest confidence and 3 = lowest), perceived added diagnostic value of multiplanar or 3D MDCT images (scale of 1-5: 5 = highest added diagnostic value and 1 = lowest), and interobserver kappa agreement were evaluated. RESULTS: The final study cohort consisted of 46 pediatric patients (28 males and 18 females; mean age, 5.6 ± 6 [SD] months; range, 1 day-50 months). Histopathologic diagnoses included congenital pulmonary airway malformation (n = 19, 41%), sequestration (n = 15, 33%), congenital lobar emphysema (n = 7, 15%), and bronchogenic cyst (n = 5, 11%). Both independent reviewers correctly diagnosed types, location, associated mass effect, and associated anomalous arteries of all congenital lung anomalies with high accuracy (100%) and confidence level (mean confidence level < 1.2) on each type of image display (axial, multiplanar, and 3D). However, for the detection of anomalous veins, multiplanar and 3D images were associated with greater diagnostic accuracy and higher confidence level than axial images alone. Specifically, diagnostic accuracy for the detection of anomalous veins (n = 15; 33%) was 60% (9/15 cases) for axial MDCT images, 80% (12/15) for multiplanar MDCT images, and 100% (15/15) for 3D MDCT images (Friedman test, p = 0.011). Confidence levels for the detection of anomalous veins were significantly higher with 3D MDCT images (mean level = 1.0) and multiplanar MDCT images (mean level = 1.5) compared with axial MDCT images alone (mean level = 2.6) (Friedman test, p < 0.01). Both multiplanar and 3D MDCT images were found to provide added diagnostic value for accurately detecting anomalous veins associated with congenial lung anomalies (paired Student t tests, p < 0.012). CONCLUSION: Axial MDCT images allow accurate diagnosis of the types, location, associated mass effect, and anomalous arteries of congenital lung anomalies, but supplemental multiplanar and 3D MDCT images add diagnostic value for the evaluation of congenital lung lesions associated with anomalous veins.
OBJECTIVE: The objective of our study was to compare the preoperative diagnostic accuracy of axial, multiplanar, and 3D MDCT images for evaluating congenital lung anomalies in pediatric patients and to assess the potential added diagnostic value of multiplanar and 3D MDCT images in this setting. MATERIALS AND METHODS: We used our hospital information system to identify all consecutive pediatric patients younger than 18 years who had undergone preoperative MDCT angiography and had a pathologically proven congenital lung anomaly between June 2005 and February 2010. Each MDCT examination was reviewed independently by two experienced pediatric radiologists for the types, location, associated mass effect, and associated anomalous vessels of congenital lung anomalies on axial, multiplanar, and 3D MDCT images. The final diagnosis was determined by surgical and pathologic findings. Diagnostic accuracy, confidence level of diagnosis (scale of 1-3: 1 = highest confidence and 3 = lowest), perceived added diagnostic value of multiplanar or 3D MDCT images (scale of 1-5: 5 = highest added diagnostic value and 1 = lowest), and interobserver kappa agreement were evaluated. RESULTS: The final study cohort consisted of 46 pediatric patients (28 males and 18 females; mean age, 5.6 ± 6 [SD] months; range, 1 day-50 months). Histopathologic diagnoses included congenital pulmonary airway malformation (n = 19, 41%), sequestration (n = 15, 33%), congenital lobar emphysema (n = 7, 15%), and bronchogenic cyst (n = 5, 11%). Both independent reviewers correctly diagnosed types, location, associated mass effect, and associated anomalous arteries of all congenital lung anomalies with high accuracy (100%) and confidence level (mean confidence level < 1.2) on each type of image display (axial, multiplanar, and 3D). However, for the detection of anomalous veins, multiplanar and 3D images were associated with greater diagnostic accuracy and higher confidence level than axial images alone. Specifically, diagnostic accuracy for the detection of anomalous veins (n = 15; 33%) was 60% (9/15 cases) for axial MDCT images, 80% (12/15) for multiplanar MDCT images, and 100% (15/15) for 3D MDCT images (Friedman test, p = 0.011). Confidence levels for the detection of anomalous veins were significantly higher with 3D MDCT images (mean level = 1.0) and multiplanar MDCT images (mean level = 1.5) compared with axial MDCT images alone (mean level = 2.6) (Friedman test, p < 0.01). Both multiplanar and 3D MDCT images were found to provide added diagnostic value for accurately detecting anomalous veins associated with congenial lung anomalies (paired Student t tests, p < 0.012). CONCLUSION: Axial MDCT images allow accurate diagnosis of the types, location, associated mass effect, and anomalous arteries of congenital lung anomalies, but supplemental multiplanar and 3D MDCT images add diagnostic value for the evaluation of congenital lung lesions associated with anomalous veins.
Authors: Maria Pia Bondioni; Diego Gatta; Vassilios Lougaris; Nicoletta Palai; Marino Signorelli; Silvia Michelini; Giuseppe Di Gaetano; Paola Tessitore; Lorella Mascaro; Andrea Tironi; Giovanni Boroni; Roberto Maroldi; Daniele Alberti Journal: Radiol Med Date: 2014-03-08 Impact factor: 3.469
Authors: Salvatore Zirpoli; Alice Marianna Munari; Alessandra Primolevo; Marco Scarabello; Sara Costanzo; Andrea Farolfi; Gianluca Lista; Elena Zoia; Gian Vincenzo Zuccotti; Giovanna Riccipetitoni; Andrea Righini Journal: Eur Radiol Date: 2019-02-22 Impact factor: 5.315
Authors: Edward Y Lee; Kathy J Jenkins; Muhammad Muneeb; Audrey C Marshall; Donald A Tracy; David Zurakowski; Phillip M Boiselle Journal: Pediatr Radiol Date: 2013-03-10