Levin, David L.

Growing evidence suggests that the larger conducting airways are smaller in women than men; however, evidence of this sex‐difference in airway geometry is yet to be demonstrated in a large cohort of adult, healthy non‐smokers. Furthermore, it is not known whether these sex differences persist after airway size is adjusted for its allometric relationship with absolute lung size. Purpose We examined the effect of sex on airway size in a large cohort of non‐smoking healthy adults after adjusting for the possible confounding effect of absolute lung size. Methods A total of 133 (75 men; 58 women) non‐smoking adults (50 ± 18 yrs) with normal pulmonary function (>80% pred.) participated in this study. Full thoracic CT scans were obtained in each participant during a breath‐hold at full inflation. Commercial software was used to automatically segment airways and assign 32 anatomical labels ranging from the 0 th to the 5 th generation. Intraluminal hydraulic diameters ( D h ) were obtained for each airway. An allometric relationship was assumed between D h and absolute lung size, as given by: D h = TLV β · e k , where TLV is the total lung volume at full inflation, β is the allometric scaling exponent, and k allowed for proportional effects of confounding variables. This allometric equation was log‐log transformed such that it could be examined using linear regression: e.g., ln( D h ) = β ·ln(TLV) + k . Sex, age and their interaction were allowed to contribute to both β and k as covariates. The model also included a term for reconstructed voxel size. Model averaging was used to provide parameter estimates of the log‐log transformed allometric equation. Results The allometric exponent, β , assigned to TLV was significant for all 32 anatomically labelled airways ( P < 0.05); neither sex nor age affected β . On the other hand, sex and age were significant mediators of k for the extra‐parenchymal airways only (Trachea, RMB, LMB, BronInt, see Figure 1, P < 0.05). Conclusions Our findings indicate that sex differences in D h remain present despite accounting for the allometric relationship between airway and lung size (see Figure 1). Importantly, however, this sex‐difference in airway size is seemingly confined to the extra‐parenchymal airways. Support or Funding Information This work was supported by NIH Grant HL71478. This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .

Pulmonary hypertension (PH) is highly heterogeneous and despite treatment advances it remains a life‐shortening condition. There have been significant advances in imaging technologies, but despite evidence of their potential clinical utility, practice remains variable, dependent in part on imaging availability and expertise. This statement summarizes current and emerging imaging modalities and their potential role in the diagnosis and assessment of suspected PH. It also includes a review of commonly encountered clinical and radiological scenarios, and imaging and modeling‐based biomarkers. An expert panel was formed including clinicians, radiologists, imaging scientists, and computational modelers. Section editors generated a series of summary statements based on a review of the literature and professional experience and, following consensus review, a diagnostic algorithm and 55 statements were agreed. The diagnostic algorithm and summary statements emphasize the key role and added value of imaging in the diagnosis and assessment of PH and highlight areas requiring further research.

There are physiological consequences of overeating that can lead to increased morbidity and mortality. The purpose of this review article is to acquaint the reader with the current state of the art in the non–cardiac-gated, noncontrast chest computed tomographic (NCCT) imaging biomarkers of the metabolic syndrome and their prognostic significance found in the lower neck and chest. NCCT imaging biomarkers associated with metabolic syndrome in the chest include premature coronary artery calcification, acceleration of large vessel arterial and valvular calcifications associated with atherosclerosis, and pulmonary arterial enlargement from pulmonary hypertension associated with sleep apnea. These easily identified imaging biomarkers have prognostic implications for major adverse cardiac events (MACE). These NCCT chest-imaging biomarkers are likely targets for artificial intelligence algorithms to harvest for longitudinal assessment of their individual and multifactorial contributions to chronic disease, MACE, and mortality. Early recognition and treatment of these common disorders may help improve patient outcomes and quality of life while decreasing medical costs.

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.

PurposeTo investigate the use of magnetic resonance elastography (MRE) in the quantitative assessment of pulmonary fibrosis by comparing quantitative shear stiffness measurements of lung parenchyma in patients diagnosed with fibrotic interstitial lung disease (ILD) and healthy controls.Materials and MethodsA 1.5T spin‐echo, echo planar imaging MRE (SE‐EPI MRE) pulse sequence was utilized to assess absolute lung shear stiffness in 15 patients with diagnosed ILD and in 11 healthy controls. Data were collected at residual volume (RV) and total lung capacity (TLC). Spirometry data were obtained immediately prior to scanning. To test for statistical significance between RV and TLC shear stiffness estimates a two‐sample t‐test was performed. To assess variability within individual subject shear stiffness estimates, the intraclass correlation coefficient (ICC) and Krippendorff's alpha were calculated.ResultsPatients with ILD exhibited an average (±1 standard deviation) shear stiffness of 2.74 (±0.896) kPa at TLC and 1.32 (±0.300) kPa at RV. The corresponding values for healthy individuals were 1.33 (±0.195) kPa and 0.849 (±0.250) kPa, respectively. The difference in shear stiffness between RV and TLC was statistically significant (P < 0.001). At TLC, the ICC and alpha values were 0.909 and 0.887, respectively. At RV, the ICC and alpha values were 0.852 and 0.862, respectively.ConclusionIn subjects with known fibrotic interstitial lung disease, parenchymal shear stiffness is increased when compared to normal controls at both RV and TLC, with TLC demonstrating the most significant difference. MRE‐derived parenchymal shear stiffness is a promising new noninvasive imaging‐based biomarker of interstitial lung disease.Level of Evidence:1J. MAGN. RESON. IMAGING 2017;46:1–1