Abstract Fibrosis is a pathological process involving the abnormal deposition of connective tissue, resulting from improper tissue repair in response to sustained injury caused by hypoxia, infection, ...or physical damage. It can impact any organ, leading to their dysfunction and eventual failure. Additionally, tissue fibrosis plays an important role in carcinogenesis and the progression of cancer. Early and accurate diagnosis of organ fibrosis, coupled with regular surveillance, is essential for timely disease-modifying interventions, ultimately reducing mortality and enhancing quality of life. While extensive research has already been carried out on the topics of aberrant wound healing and fibrogenesis, we lack a thorough understanding of how their relationship reveals itself through modern imaging techniques. This paper focuses on fibrosis of the genito-urinary system, detailing relevant imaging technologies used for its detection and exploring future directions.
Radiology of fibrosis. Part I: Thoracic organs Tarchi, Sofia Maria; Salvatore, Mary; Lichtenstein, Philip ...
Journal of translational medicine,
07/2024, Letnik:
22, Številka:
1
Journal Article
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Abstract 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.
This editorial describes the indications and technical aspects of the simultaneous retrieval of thoracic and abdominal organs in Maastricht III donors as well as the preservation of such organs until ...their implantation.
Segmentation of medical images plays a key role in the correct identification and management of different diseases. In this study, we present a new segmentation method that meets the difficulties ...posed by sophisticated organ shapes in computed tomography (CT) images, particularly targeting lung, breast, and gastric cancers.
Our suggested methods, Resio-Inception U-Net and Deep Cluster Recognition (RIUDCR), use a Residual Inception Architecture, which combines the power of residual connections and inception blocks to achieve cutting-edge segmentation performance while reducing the risk of overfitting.
We present mathematical equations and functions that describe the design, including the encoding and decoding steps within the UC-Net system. Furthermore, we provide strong testing results that show the effectiveness of our method. Through thorough testing on varied datasets, our method regularly beats current techniques, achieving amazing precision and stability in organ task segmentation. These results show the promise of our residual inception architecture in better medical picture analysis.
In summary, our research not only shows a state-of-the-art segment methodology but also reinforces its usefulness through thorough testing. The inclusion of residual inception architecture in medical picture segmentation offers good possibilities for improving the identification and management of disease planning.
Abstract Viscero-somatic referral and sensitization has been well documented clinically and widely investigated, whereas viscero-visceral referral and sensitization (termed cross-organ sensitization) ...has only recently received attention as important to visceral disease states. Because second order neurons in the CNS have been extensively shown to receive convergent input from different visceral organs, it has been assumed that cross-organ sensitization arises by the same convergence-projection mechanism as advanced for viscero-somatic referral and sensitization. However, increasing evidence also suggests participation of peripheral mechanisms to explain referral and sensitization. We briefly summarize behavioral, morphological and physiological support of and focus on potential mechanisms underlying cross-organ sensitization.
The authors report an unusual autopsy case of a motorcyclist who wore a full-face type helmet and had incomplete decapitation and herniation of the heart and a portion of the right lung through an ...extensive lacerate wound on the front of the neck after his motorcycle crashed. The authors identified 2 main offensive dynamics that occurred simultaneously: First, partial decapitation with a extensive gaping wound on the neck caused by the chin strap after a violent angular movement of the head; second, the translocation of the abdominal organs into the thorax and the herniation of the thoracic organs through the neck wound generated by a compressive trauma of the thorax and abdomen. This singular case, like few others in forensic literature, shows the possibility of helmet chin strap-related traumas and highlights the limitations of modern protective helmets. If the postulated mechanism is confirmed despite the massive benefits derived from the compulsory use of protective helmets, the properties of the helmet chin strap would need to be reassessed to improve the protection of the soft tissue and bones in the neck.
Aims To analyse the prevalence, and diagnostic and therapeutic consequences, of accidental findings in electron-beam tomographic scans performed for evaluation of coronary artery calcification. ...Methods and Results A total of 1812 consecutive patients with known or suspected coronary artery disease underwent electron-beam tomography. In 583 (32%) of the patients, i.v. contrast was also administered for non-invasive coronary angiography. A total of 2055 non-coronary pathological findings were observed in 953 (53%) of the patients. The prevalence of extra-cardiac disease, as shown in native scans and contrast studies, was assessed separately. In 583 (32%) patients, cardiac structures or the pericardium were affected, in 423 (23%) aortic disease was found. Lung disease was found in 357 (20%), and pathology of other organs in 273 patients (15%). The most frequent findings were aortic calcium in 423 (23%) patients and heart valve calcification in 317 patients (17%). Malignant disease could be detected in three patients. Further diagnostic investigations were done in 191 (11%) patients, 141 (74%) of which concerned the heart. In 22 (1·2%) patients, specific therapy was initiated following electron-beam tomographic findings. Conclusion Accidental non-coronary pathology is a frequent finding in electron-beam tomographic calcium scanning, and often requires diagnostic or therapeutic action. Profound knowledge of the radiological differential diagnosis of the thoracic organs is necessary for reporting electron-beam tomographic scans, in order to avoid misdiagnosis and to receive a high quality interpretation.
This paper analyses the geometry of intra-thoracic organs from computed tomography (CT) scans performed on 20 children aged from 4 months to 16 years. The aim is to find the most reliable ...measurements to characterise the growth of heart and lungs from CT data. Standard measurements available on chest radiographies are compared with original measurements only available on CT scans. These measurements should characterise the growth of organs as well as the changes in their position relative to the thorax. Measurements were considered as functions of age. Quadratic regression models were fitted to the data. Goodness of fit of the models was then evaluated. Positions of organs relative to the thorax have a high variability compared with their changes with age. The length and volume of the heart and lungs as well as the diameter of the thorax fit well to the models of growth. It could be interesting to study these measurements with a larger sample size in order to define growth standards.
This paper analyses geometry of intra-thoracic organs from computed tomography (CT) scans performed on 20 children aged from 4 months to 16 years. A set of two measurements on lungs and heart were ...performed by the same observer. A third set was performed by a second observer. Thus, the intra- and inter-observer relative deviation of measurements was analysed. Multiple regressions were used in order to study the relationship between the CT properties (scanner, voltage, dose, pixel size, slice increment) and the relative deviation of measurements. There is a very low systematic intra- and inter-observer bias in measurements except for the volume of the heart. None of the CT data properties has a significant influence on the relative deviation of measurement. In the present paper, the measurements and 3D reconstruction protocol described can be applied to characterise the growth of the intra-thoracic organs.
Medical images have become the important part in medical diagnosis and treatment. These images play a significant role in medical field because the doctors are highly interested in exploring the ...anatomy of the human body. The medical images captured with various modalities like (PET, CT, SPECT, MRI, etc.) have different variability based on the intensity level. The segmentation of organs in medical images is the most crucial image-related application. Organs segmentation in the medical images help the doctors in planning the treatment in lesser time and with higher efficiency. Results of manual segmentation vary from experts to experts and it is very time taking task. Automatic segmentation is the solution to the problem as it gives precise results. Several techniques had been addressed in the literature for the segmentation of thoracic organs (heart, aorta, trachea, esophagus) automatically in the medical images. Out of those deep learning-based techniques outperformed in the automatic segmentation of organs by giving precise accuracy. Using deep learning models for segmentation purposes improve the segmentation results in various clinical applications. In this paper various deep learning-based techniques for automatic segmentation had been discussed. Also, the three authors' results are compared based on the parameters such as Dice Coefficient (DC) and Hausdorff Metric (HM).
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