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Background Clustering key clinical characteristics of participants in the Severe Asthma Research Program (SARP), a large, multicenter prospective observational study of patients with asthma and healthy controls, has led to the identification of novel asthma phenotypes. Purpose To determine whether quantitative CT (qCT) could help distinguish between clinical asthma phenotypes. Materials and Methods A retrospective cross-sectional analysis was conducted with the use of qCT images (maximal bronchodilation at total lung capacity [TLC], or inspiration, and functional residual capacity [FRC], or expiration) from the cluster phenotypes of SARP participants (cluster 1: minimal disease; cluster 2: mild, reversible; cluster 3: obese asthma; cluster 4: severe, reversible; cluster 5: severe, irreversible) enrolled between September 2001 and December 2015. Airway morphometry was performed along standard paths (RB1, RB4, RB10, LB1, and LB10). Corresponding voxels from TLC and FRC images were mapped with use of deformable image registration to characterize disease probability maps (DPMs) of functional small airway disease (fSAD), voxel-level volume changes (Jacobian), and isotropy (anisotropic deformation index [ADI]). The association between cluster assignment and qCT measures was evaluated using linear mixed models. Results A total of 455 participants were evaluated with cluster assignments and CT (mean age ± SD, 42.1 years ± 14.7; 270 women). Airway morphometry had limited ability to help discern between clusters. DPM fSAD was highest in cluster 5 (cluster 1 in SARP III: 19.0% ± 20.6; cluster 2: 18.9% ± 13.3; cluster 3: 24.9% ± 13.1; cluster 4: 24.1% ± 8.4; cluster 5: 38.8% ± 14.4

Rationale: Measuring disease extent and progression of systemic sclerosis-associated interstitial lung disease (SSc-ILD) is challenging, with recent studies suggesting potential utility of quantitative measurements from computed tomography (CT) scans.Objectives: To determine the associations of quantitative computed tomography (qCT) density-based measures with physiological parameters, visual CT scores, and survival in patients with SSc-ILD.Methods: Patients with SSc-ILD and volumetric high-resolution CT images with ≤1.25-mm slice thickness were retrospectively identified. Cardiothoracic radiologists produced visual CT scores of ground glass, reticulation, and honeycombing, with visual fibrosis score equaling the sum of reticulation and honeycombing. qCT measurements included high-attenuation areas (HAA), skewness, kurtosis, and mean lung attenuation (MLA). Associations of qCT measures with pulmonary physiology, visual CT scores, and mortality were analyzed using Spearman's rank correlation and Cox regression.Results: A total of 503 CT scans from 170 patients with SSc-ILD were included. qCT HAA, skewness, kurtosis, and MLA were associated with lung function and visual fibrosis scores, independent of age, sex, and pack-years, using both baseline and change data. Baseline and changes in qCT measures (except ∆skewness) were associated with mortality on unadjusted analysis. Changes in all qCT variables remained associated with survival after adjustment for baseline age, sex, pack-years, and lung function, but not when adjusting for changes in lung function. ∆HAA and ∆MLA were associated with survival after adjustment for age, sex, pack-years, and change in visual CT scores.Conclusions: CT density measurements correlate with physiologic impairment and visual CT scores in patients with SSc-ILD; however, they were not associated with survival independent of changes in pulmonary physiology. The clinical utility of more sophisticated qCT measures should be explored.

To evaluate the effect of oxytocin as a cervical dilator, a study was carried out on nulliparous goats inseminated transcervically at the beginning of the breeding season. One hundred sixteen nulliparous goats with a mean live weight of 33.4 ± 0.68 kg and an age of 13.7 ± 0.37 months were used. The goats were exposed to active bucks of proven fertility for a period of 14 d in order to induce oestrus. One week later, the Ovsynch protocol was applied, which consisted of the application of 20 mg of gonadorelin (Day Zero), 0.075 mg of cloprostenol (Day 7) and of a second dose of 20 mg of gonadorelin applied on Day 9. Artificial insemination (AI) was performed 16 hr later. Three treatments were evaluated: T1 = 50 IU saline, T2 = 25 IU oxytocin ; T3 = 50 IU of oxytocin, intravenously applied 10–15 min before AI. The time required to inseminate each treated goat from groups T2 and T3 was 49.56 and 56.25 s, respectively, versus 85.78 s needed for the goats from group T1 (p < .0001). In the T1 group of goats, the insemination catheter was inserted 2.1 cm into the cervical canal and in goats from groups T2 and T3 it reached 3.41 and 3.77 cm into the cervical canal, respectively (p = .02). Pregnancy rates and prolificacy (kids/doe) were higher (p = .02) for groups T2 (82.93% ; 1.16) and T3 (76.92% ; 1.21) respectively than for control goats (61.11% ; 0.69). In conclusion, the intravenous administration of oxytocin led to greater dilation and depth of cervical penetration, obtaining higher pregnancy rates and prolificacy.

Rationale: Chronic obstructive pulmonary disease (COPD) is characterized by airflow limitation, caused by emphysema and small airways disease (SAD). Computed tomography (CT) coupled with image anal...

Introduction: COPD is characterised by airflow limitation, caused by parenchymal destruction and small airways disease. This study aims to use a novel quantitative CT method (DPM) to assess the contribution of small airways disease in COPD. Methods: 38 Mild-moderate COPD subjects, 21 ex (ES) and 17 non-smokers (NS) had CT chest performed in inspiration and expiration. Image analysis was performed by VIDA Lungprints (DPM), which registers inspiratory and expiratory images, classifying each voxel as normal, emphysema or gas trapping due to small airway disease (DPMGT). Results: Minimal emphysema was found (COPD 1.3%, ES 0.0%, NS 0.0%). Significantly more DPMGT in COPD (12.3%) was found compared to ES (2.2%) or NS(1.4%). There were significant associations between DPMGT and FEV1% (-0.67) and peripheral airway resistance (R5-R19) (0.54). Strong associations between overall and lobar values of DPMGT (rho 0.78-0.96) were found. Greater lobar quantities of DPMGT were found in COPD compared to controls (p

Rationale and Objectives Quantifying changes in lung tumor volume is important for diagnosis, therapy planning, and evaluation of response to therapy. The aim of this study was to assess the performance of multiple algorithms on a reference data set. The study was organized by the Quantitative Imaging Biomarker Alliance (QIBA). Materials and Methods The study was organized as a public challenge. Computed tomography scans of synthetic lung tumors in an anthropomorphic phantom were acquired by the Food and Drug Administration. Tumors varied in size, shape, and radiodensity. Participants applied their own semi-automated volume estimation algorithms that either did not allow or allowed post-segmentation correction (type 1 or 2, respectively). Statistical analysis of accuracy (percent bias) and precision (repeatability and reproducibility) was conducted across algorithms, as well as across nodule characteristics, slice thickness, and algorithm type. Results Eighty-four percent of volume measurements of QIBA-compliant tumors were within 15% of the true volume, ranging from 66% to 93% across algorithms, compared to 61% of volume measurements for all tumors (ranging from 37% to 84%). Algorithm type did not affect bias substantially; however, it was an important factor in measurement precision. Algorithm precision was notably better as tumor size increased, worse for irregularly shaped tumors, and on the average better for type 1 algorithms. Over all nodules meeting the QIBA Profile, precision, as measured by the repeatability coefficient, was 9.0% compared to 18.4% overall. Conclusion The results achieved in this study, using a heterogeneous set of measurement algorithms, support QIBA quantitative performance claims in terms of volume measurement repeatability for nodules meeting the QIBA Profile criteria.

Rationale and objectives Tumor volume change has potential as a biomarker for diagnosis, therapy planning, and treatment response. Precision was evaluated and compared among semiautomated lung tumor volume measurement algorithms from clinical thoracic computed tomography data sets. The results inform approaches and testing requirements for establishing conformance with the Quantitative Imaging Biomarker Alliance (QIBA) Computed Tomography Volumetry Profile. Materials and Methods Industry and academic groups participated in a challenge study. Intra-algorithm repeatability and inter-algorithm reproducibility were estimated. Relative magnitudes of various sources of variability were estimated using a linear mixed effects model. Segmentation boundaries were compared to provide a basis on which to optimize algorithm performance for developers. Results Intra-algorithm repeatability ranged from 13% (best performing) to 100% (least performing), with most algorithms demonstrating improved repeatability as the tumor size increased. Inter-algorithm reproducibility was determined in three partitions and was found to be 58% for the four best performing groups, 70% for the set of groups meeting repeatability requirements, and 84% when all groups but the least performer were included. The best performing partition performed markedly better on tumors with equivalent diameters greater than 40 mm. Larger tumors benefitted by human editing but smaller tumors did not. One-fifth to one-half of the total variability came from sources independent of the algorithms. Segmentation boundaries differed substantially, not ony in overall volume but also in detail. Conclusions Nine of the 12 participating algorithms pass precision requirements similar to what is indicated in the QIBA Profile, with the caveat that the present study was not designed to explicitly evaluate algorithm profile conformance. Change in tumor volume can be measured with confidence to within ±14% using any of these nine algorithms on tumor sizes greater than 10 mm. No partition of the algorithms was able to meet the QIBA requirements for interchangeability down to 10 mm, although the partition comprising best performing algorithms did meet this requirement for a tumor size of greater than approximately 40 mm.