Sustained injury from factors such as hypoxia, infection, or physical damage may provoke improper tissue repair and the anomalous deposition of connective tissue that causes fibrosis. This phenomenon may take place in any organ, ultimately leading to their dysfunction and eventual failure. Tissue fibrosis has also been found to be central in both the process of carcinogenesis and cancer progression. Thus, its prompt diagnosis and regular monitoring is necessary for implementing effective disease-modifying interventions aiming to reduce mortality and improve overall quality of life. While significant research has been conducted on these subjects, a comprehensive understanding of how their relationship manifests through modern imaging techniques remains to be established. This work intends to provide a comprehensive overview of imaging technologies relevant to the detection of fibrosis affecting thoracic organs as well as to explore potential future advancements in this field.

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Up to now, Allen and Bergmann\'s rules have been studied in modern humans by analyzing differences in limb length, height, or body mass. However, there are no publications studying the effects of latitude in the 3D configuration of the ribcage. To assess this issue, we digitally reconstructed the ribcages of a balanced sample of 109 adult individuals of global distribution. Shape and size of the ribcage was quantified using geometric morphometrics. Our results show that the ribcage belonging to tropical individuals is smaller and slenderer compared to others living in higher latitudes, which is in line with Allen and Bergmann\'s rules and suggests an allometric relationship between size and shape. Although sexual dimorphism was observed in the whole sample, significant differences were only found in tropical populations. Our proposal is that, apart from potential sexual selection, avoiding heat loss might be the limiting factor for sexual dimorphism in cold-adapted populations.

Anomalies of the fetal chest require advanced imaging with ultrasound and MR imaging as well as expertise on the part of the interpreting pediatric radiologist. Congenital diaphragmatic hernia and congenital lung malformation are the most frequently seen, and in both conditions, the radiologist should provide both detailed anatomic description and measurement data for prognostication. This article provides a detailed approach to imaging the anatomy, in-depth explanation of available measurements and prognostic value, and keys to identifying candidates for fetal intervention. Less common congenital lung tumors and mediastinal and chest wall masses are also reviewed.

Electrical impedance tomography (EIT) is a non-radiation, non-invasive visual diagnostic technique. In order to improve the imaging resolution and the removing artifacts capability of the reconstruction algorithms for electrical impedance imaging in human-chest models, the HMANN algorithm was proposed using the Hadamard product to optimize multilayer artificial neural networks (MANN). The reconstructed images of the HMANN algorithm were compared with those of the generalized vector sampled pattern matching (GVSPM) algorithm, truncated singular value decomposition (TSVD) algorithm, backpropagation (BP) neural network algorithm, and traditional MANN algorithm. The simulation results showed that the correlation coefficient of the reconstructed images obtained by the HMANN algorithm was increased by 17.30% in the circular cross-section models compared with the MANN algorithm. It was increased by 13.98% in the lung cross-section models. In the lung cross-section models, some of the correlation coefficients obtained by the HMANN algorithm would decrease. Nevertheless, the HMANN algorithm retained the image information of the MANN algorithm in all models, and the HMANN algorithm had fewer artifacts in the reconstructed images. The distinguishability between the objects and the background was better compared with the traditional MANN algorithm. The algorithm could improve the correlation coefficient of the reconstructed images, and effectively remove the artifacts, which provides a new direction to effectively improve the quality of the reconstructed images for EIT.
电阻抗成像（EIT）是一种无辐射、非侵入式的可视化诊断技术。为提高胸部电阻抗成像技术重建算法的成像分辨率和去伪影能力，本研究提出了一种利用Hadamard product优化多层神经网络（MANN）的HMANN算法。将HMANN算法的重建图像与广义矢量模式匹配（GVSPM）算法、截断奇异值分解（TSVD）算法、反向传播（BP）神经网络算法和传统MANN算法的重建图像进行对比，仿真结果表明：相对于MANN算法，HMANN算法重建图像的相关系数在圆截面模型中可以提高17.30%，在肺截面模型中可以提高13.98%。虽然肺截面模型中HMANN算法重建图像的部分相关系数会有所下降，但在所有模型中，HMANN算法保留了MANN算法的图像信息，同时HMANN算法重建图像的伪影更少，检测目标与背景的可识别度比传统MANN算法高。本研究可以提升重建图像的相关系数，有效去除重建图像的伪影，为EIT成像技术提供了一种有效提升重建图像质量的新思路。.

BACKGROUND: Ankylosing spondylitis is chronic progressive disease, which decrease functions of musculoskeletal system including chest area. Those changes influences respiratory mechanics, worsen conditions of proper ventilation of lungs.
OBJECTIVE: Rating of functional and respiratory parameters and dependence between them at patients with ankylosing spondylitis.
METHODS: The study included 45 patients with diagnosed ankylosing spondylitis. Chest and upper limbs mobility, resting spinal curvature alignment were assessed, and respiratory parameters were measured in a plethysmographic chamber JAGGER MasterScreen Body.
RESULTS: Ankylosing spondylitis patients had lower respiratory parameters especially sReff, and FRC. Restriction of chest and upper limbs mobility was also demonstrated. Forward head extension was observed based on the occipital wall test. Correlations between functional parameters and correlations between functional and respiratory parameters were shown, in particular MIP, MEP, sReff, Rtot, TLC, ERV.
CONCLUSIONS: The study confirmed a decrease in functional and respiratory parameters in the examined patients with ankylosing spondylitis compared to the applicable standards. A significant relationship was found between functional parameters in the upper body and respiratory parameters, which worsen with increasing thoracic dysfunction. The obtained results indicate the directions of therapy that should be taken into account to improve respiratory parameters and reduce respiratory dysfunction in these patients. Chest-focused physiotherapy appears to be an important element in improving function in patients with ankylosing spondylitis.

Superficial fascia is a fibrofatty tissue found throughout the body. Initially described in relation to hernias, it has only recently received attention from the scientific community due to new evidence on its role in force transmission and structural integrity of the body. Considering initial difficulties in its anatomical identification, to date, a characterization of the superficial fascia through mechanical tests is still lacking. The mechanical properties of human superficial fasciae of abdominal and thoracic districts (back) of different subjects (n = 4) were then investigated, focusing on anisotropy and viscoelasticity. Experimental tests were performed on samples taken in two perpendicular directions according to body planes (cranio-caudal and latero-medial axes). Data collected from two different uniaxial tensile protocols, failure (i.e., ultimate tensile strength and strain at break, Young\'s modulus and toughness) and stress-relaxation (i.e., residual stress), were processed and then grouped for statistical analysis. Failure tests confirmed tissue anisotropy, revealing the stiffer nature of the latero-medial direction compared to the cranio-caudal one, for both the districts (with a ratio of the respective Young\'s moduli close to 2). Furthermore, the thoracic region exhibited significantly greater strength and resultant Young\'s modulus compared to the abdomen (with greater results along the latero-medial direction, such as 6.13 ± 3.11 MPa versus 0.85 ± 0.39 MPa and 24.87 ± 15.23 MPa versus 3.19 ± 1.62 MPa, respectively). On the contrary, both regions displayed similar strain at break (varying between 38 and 47%), with no clear dependence from the loading directions. Stress-relaxation tests highlighted the viscous behavior of the superficial fascia, with no significant differences in the stress decay between directions and districts (35-38% of residual stress after 300 s). All these collected results represent the starting point for a more in-depth knowledge of the mechanical characterization of the superficial fascia, which can have direct implications in the design, implementation, and effectiveness of site-specific treatments.

The purpose of the study was to assess the performance of readers in diagnosing thoracic anomalies on standard chest radiographs (CXRs) with and without a deep-learning-based AI tool (Rayvolve) and to evaluate the standalone performance of Rayvolve in detecting thoracic pathologies on CXRs. This retrospective multicentric study was conducted in two phases. In phase 1, nine readers independently reviewed 900 CXRs from imaging group A and identified thoracic abnormalities with and without AI assistance. A consensus from three radiologists served as the ground truth. In phase 2, the standalone performance of Rayvolve was evaluated on 1500 CXRs from imaging group B. The average values of AUC across the readers significantly increased by 15.94%, with AI-assisted reading compared to unaided reading (0.88 ± 0.01 vs. 0.759 ± 0.07, p < 0.001). The time taken to read the CXRs decreased significantly, by 35.81% with AI assistance. The average values of sensitivity and specificity across the readers increased significantly by 11.44% and 2.95% with AI-assisted reading compared to unaided reading (0.857 ± 0.02 vs. 0.769 ± 0.02 and 0.974 ± 0.01 vs. 0.946 ± 0.01, p < 0.001). From the standalone perspective, the AI model achieved an average sensitivity, specificity, PPV, and NPV of 0.964, 0.844, 0.757, and 0.9798. The speed and performance of the readers improved significantly with AI assistance.

Digital health technologies (DHTs) are increasingly being adopted in clinical trials, as they enable objective evaluations of health parameters in free-living environments. Although lumbar accelerometers notably provide reliable gait parameters, embedding accelerometers in chest devices, already used for vital signs monitoring, could capture a more comprehensive picture of participants\' wellbeing, while reducing the burden of multiple devices. Here we assess the validity of gait parameters measured from a chest accelerometer. Twenty healthy adults (13 females, mean ± sd age: 33.9 ± 9.1 years) instrumented with lumbar and chest accelerometers underwent in-lab and outside-lab walking tasks, while monitored with reference devices (an instrumented mat, and a 6-accelerometers set). Gait parameters were extracted from chest and lumbar accelerometers using our open-source Scikit Digital Health gait (SKDH-gait) algorithm, and compared against reference values via Bland-Altman plots, Pearson\'s correlation, and intraclass correlation coefficient. Mixed effects regression models were performed to investigate the effect of device, task, and their interaction. Gait parameters derived from chest and lumbar accelerometers showed no significant difference and excellent agreement across all tasks, as well as good-to-excellent agreement and strong correlation against reference values, thus supporting the deployment of a single multimodal chest device in clinical trials, to simultaneously measure gait and vital signs.Trial Registration: The study was reviewed and approved by the Advarra IRB (protocol number: Pro00043100).

The diversity in butterfly morphology has attracted many people around the world since ancient times. Despite morphological diversity, the wing and body kinematics of butterflies have several common features. In the present study, we constructed a bottom-up butterfly model, whose morphology and kinematics are simplified while preserving the important features of butterflies. The present bottom-up butterfly model is composed of two trapezoidal wings and a rod-shaped body with a thorax and abdomen. Its wings are flapped downward in the downstroke and backward in the upstroke by changing the geometric angle of attack (AOA). The geometric AOA is determined by the thorax-pitch and wing-pitch angles. The thorax-pitch angle is actively controlled by abdominal undulation, and the wing-pitch angle is passively determined because of a rotary spring representing the basalar and subalar muscles connecting the wings and thorax. We investigated the effectiveness of abdominal undulation for thorax-pitch control and how wing-pitch flexibility affects aerodynamic-force generation and thorax-pitch control, through numerical simulations using the immersed boundary-lattice Boltzmann method. As a result, the thorax-pitch angle perfectly follows the desired angle through abdominal undulation. In addition, there is an optimal wing-pitch flexibility that maximizes the flying speed in both the forward and upward directions, but the effect of wing-pitch flexibility on thorax-pitch control is not significant. Finally, we compared the flight behavior of the present bottom-up butterfly model with that of an actual butterfly. It was found that the present model does not reproduce reasonable body kinematics but can provide reasonable aerodynamics in butterfly flights.