Citations

Pulmonary developmental disorders comprise a heterogeneous group of congenital abnormalities involving the airways, lung parenchyma, pulmonary vasculature, or overlapping developmental pathways. Although these conditions commonly present during infancy or childhood, many remain clinically silent until adulthood, when they are discovered incidentally or manifest with recurrent respiratory symptoms such as infection, hemoptysis, or progressive dyspnea. These abnormalities may be broadly categorized into airway, vascular, parenchymal, and mixed developmental anomalies. Airway abnormalities include congenital tracheobronchomegaly, branching anomalies of the tracheobronchial tree, bronchial atresia, bronchogenic cysts, congenital pulmonary airway malformations (CPAM), and bronchopulmonary sequestration (BPS). Vascular anomalies include pulmonary artery sling, proximal interruption of the pulmonary artery, Scimitar syndrome, and meandering pulmonary veins. Parenchymal disorders encompass congenital lobar overinflation and pulmonary hypoplasia. Increasing recognition of overlapping lesions, particularly combinations of CPAM, sequestration, and bronchial atresia, has challenged traditional compartmental classification systems and supports a developmental spectrum model. This review synthesizes contemporary concepts regarding embryologic mechanisms, pathogenesis, imaging findings, and management of these entities in adults. Particular emphasis is placed on imaging evaluation with CT and MRI, updated terminology, evolving molecular understanding of CPAMs, including lesions with malignant potential, and distinctions between congenital sequestration and pseudosequestration. Recognition of these disorders and their associated anomalies is essential for accurate diagnosis, appropriate management, and surgical planning in adult patients.

Purpose: The aim of this study was to evaluate the ability of computer-aided detection (CAD) and human readers to detect pulmonary nodules ≥5 mm using 100 kV ultra–low-dose computed tomography (ULDCT) utilizing a tin filter. Materials and Methods: After informed consent, 55 patients prospectively underwent standard-dose chest CT (SDCT) using 120 kV followed by ULDCT using 100 kV/tin. Reference nodules ≥5 mm were identified by a thoracic radiologist using SDCT. Four thoracic radiologists marked detected nodules on SDCT and ULDCT examinations using a dedicated computer workstation. After a 6-month memory extinction, readers were shown the same ULDCT cases with all CAD markings as well as their original detections, and characterized CAD detections as true positive or false positive. Results: Volume CT Dose index (CTDIvol) for SDCT and ULDCT were 5.3±2 and 0.4±0.2 mGy (P<0.0001), respectively. Forty-five reference nodules were detected in 30 patients. Reader sensitivity varied widely but similarly for SDCT (ranging from 45% to 87%) and ULDCT (45% to 83%). CAD sensitivity was 76% (34/45) for SDCT and 71% (32/45) for ULDCT. After CAD, reader sensitivity substantially improved by 19% and 18% for 2 readers, and remained nearly unchanged for the other 2 readers (0% and 2%), despite reader perception that many more nodules were identified with CAD. There was a mean of 2 false-positive CAD detections/case. Conclusions: ULDCT with 100 kV/tin reduced patient dose by over 90% without compromising pulmonary nodule detection sensitivity. CAD can substantially improve nodule detection sensitivity at ULDCT for some readers, maintaining interobserver performance.

Despite its nonionizing technique and exquisite soft tissue characterization, noncardiovascular, and nonmusculoskeletal magnetic resonance imaging (MRI) of the chest has been considered impractical due to various challenges such as respiratory motion, cardiac motion, vascular pulsatility, air susceptibility, and paucity of signal in the lung. With advances in MRI, it is now possible to perform diagnostically useful and good quality MRIs of the chest, but literature on subspecialized chest MRI practices is limited. The purpose of this manuscript is to describe the rationale, nuances, and logistics that went into developing such a practice in the Division of Thoracic Radiology at our institution. The topics addressed include technical and clinical considerations, support at administrative and clinical levels, protocol development, and economic considerations compared with conventional practices. Various MRI techniques are also specifically discussed to facilitate chest MRI at other sites. Although chest MRI is used in a relatively small number of patients at this point, in certain patients, chest MRI can provide additional information to optimize medical management. A few clinical cases illustrate the quality and clinical utility of chest MRI. Given recent advances in MRI techniques, it is now an opportune time to develop a chest MRI practice.

Abstract Studies suggest that screening with spiral computed tomography can detect lung cancers at a smaller size and earlier stage than chest radiography can. To evaluate low-radiation-dose spiral computed tomography and sputum cytology in screening for lung cancer, we enrolled 1,520 individuals aged 50 yr or older who had smoked 20 pack-years or more in a prospective cohort study. One year after baseline scanning, 2,244 uncalcified lung nodules were identified in 1,000 participants (66%). Twenty-five cases of lung cancer were diagnosed (22 prevalence, 3 incidence). Computed tomography alone detected 23 cases; sputum cytology alone detected 2 cases. Cell types were: squamous cell, 6; adenocarcinoma or bronchioalveolar, 15; large cell, 1; small cell, 3. Twenty-two patients underwent curative surgical resection. Seven benign nodules were resected. The mean size of the non-small cell cancers detected by computed tomography was 17 mm (median, 13 mm). The postsurgical stage was IA, 13; IB, 1; IIA, 5; IIB, 1; IIIA, 2; limited, 3. Twelve (57%) of the 21 non-small cell cancers detected by computed tomography were stage IA at diagnosis. Computed tomography can detect early-stage lung cancers. The rate of benign nodule detection is high.