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Medicinski Glasnik : Official... Aug 2021Aim To analyse the resolution of chest X-ray findings in relation to laboratory parameters in patients infected with acute respiratory syndrome coronavirus 2...
Aim To analyse the resolution of chest X-ray findings in relation to laboratory parameters in patients infected with acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in a two- month followup. Analysis of chest X-ray findings in the first few months after the disease is the main goal of our work. Methods Out of the total of 343 patients chest X-ray findings were followed in 269 patients. Patients were divided into groups according to the severity of findings. D-dimer, inflammatory markers, blood cell count, neutrophil lymphocyte ratio (NLR) were analysed. Chest X-ray was analysed during the hospitalization on the day of admission, on the third, the seventh and the fourteenth day (scoring method was used). After discharge chest X-ray was performed in a two-week follow-up, then after one and two months, and after three months if necessary. Results Incomplete chest X-ray resolution was identified in 24 (39.34%) patients with severe, 27 (22.31 %) patients with moderate and in three (3.91%) patients with mild findings. Statistical significance was established in overall score by comparison between all groups (p<0.001), and in the moderate compared to the mild group (p=0.0051). The difference of NLR in the severe compared to the moderate group was observed (p=0.0021) and in the severe group compared to the mild group (p=0.00013). Conclusion Chest X-ray findings persisted mostly in the severe group followed by the moderate and mild ones. Long-term followup is necessary for the appropriate treatment and prevention of fibrosis, and reduction of symptoms.
Topics: COVID-19; Humans; Radiography, Thoracic; Retrospective Studies; X-Rays
PubMed: 34331436
DOI: 10.17392/1391-21 -
Seminars in Ultrasound, CT, and MR Feb 2023This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evolving field of artificial intelligence (AI). The range of AI... (Review)
Review
This topical review is focused on the clinical breast x-ray imaging applications of the rapidly evolving field of artificial intelligence (AI). The range of AI applications is broad. AI can be used for breast cancer risk estimation that could allow for tailoring the screening interval and the protocol that are woman-specific and for triaging the screening exams. It also can serve as a tool to aid in the detection and diagnosis for improved sensitivity and specificity and as a tool to reduce radiologists' reading time. AI can also serve as a potential second 'reader' during screening interpretation. During the last decade, numerous studies have shown the potential of AI-assisted interpretation of mammography and to a lesser extent digital breast tomosynthesis; however, most of these studies are retrospective in nature. There is a need for prospective clinical studies to evaluate these technologies to better understand their real-world efficacy. Further, there are ethical, medicolegal, and liability concerns that need to be considered prior to the routine use of AI in the breast imaging clinic.
Topics: Female; Humans; Artificial Intelligence; Retrospective Studies; X-Rays; Early Detection of Cancer; Mammography; Breast Neoplasms
PubMed: 36792270
DOI: 10.1053/j.sult.2022.12.002 -
Wiley Interdisciplinary Reviews.... Nov 2020X-ray imaging is the most widely used diagnostic imaging method in modern medicine and several advanced forms of this technology have recently emerged. Iodinated... (Review)
Review
X-ray imaging is the most widely used diagnostic imaging method in modern medicine and several advanced forms of this technology have recently emerged. Iodinated molecules and barium sulfate suspensions are clinically approved X-ray contrast agents and are widely used. However, these existing contrast agents provide limited information, are suboptimal for new X-ray imaging techniques and are developing safety concerns. Thus, over the past 15 years, there has been a rapid growth in the development of nanoparticles as X-ray contrast agents. Nanoparticles have several desirable features such as high contrast payloads, the potential for long circulation times, and tunable physicochemical properties. Nanoparticles have also been used in a range of biomedical applications such as disease treatment, targeted imaging, and cell tracking. In this review, we discuss the principles behind X-ray contrast generation and introduce new types of X-ray imaging modalities, as well as potential elements and chemical compositions that are suitable for novel contrast agent development. We focus on the progress in nanoparticle X-ray contrast agents developed to be renally clearable, long circulating, theranostic, targeted, or for cell tracking. We feature agents that are used in conjunction with the newly developed multi-energy computed tomography and mammographic imaging technologies. Finally, we offer perspectives on current limitations and emerging research topics as well as expectations for the future development of the field. This article is categorized under: Diagnostic Tools > in vivo Nanodiagnostics and Imaging Nanotechnology Approaches to Biology > Nanoscale Systems in Biology.
Topics: Contrast Media; Diagnostic Imaging; Nanoparticles; Nanotechnology; Tomography, X-Ray Computed; X-Rays
PubMed: 32441050
DOI: 10.1002/wnan.1642 -
Scientific Reports Nov 2020Amyloid plaque deposits in the brain are indicative of Alzheimer's and other diseases. Measurements of brain amyloid burden in small animals require laborious...
Amyloid plaque deposits in the brain are indicative of Alzheimer's and other diseases. Measurements of brain amyloid burden in small animals require laborious post-mortem histological analysis or resource-intensive, contrast-enhanced imaging techniques. We describe a label-free method based on spectral small-angle X-ray scattering with a polychromatic beam for in vivo estimation of brain amyloid burden. Our findings comparing 5XFAD versus wild-type mice correlate well with histology, showing promise for a fast and practical in vivo technique.
Topics: Amyloid beta-Peptides; Animals; Brain; Mice, Transgenic; Scattering, Small Angle; X-Ray Diffraction; X-Rays
PubMed: 33239703
DOI: 10.1038/s41598-020-77554-5 -
Journal of Biomedical Optics Jan 2024X-ray-induced acoustic computed tomography (XACT) offers a promising approach to biomedical imaging, leveraging X-ray absorption contrast. It overcomes the shortages of... (Review)
Review
SIGNIFICANCE
X-ray-induced acoustic computed tomography (XACT) offers a promising approach to biomedical imaging, leveraging X-ray absorption contrast. It overcomes the shortages of traditional X-ray, allowing for more advanced medical imaging.
AIM
The review focuses on the significance and draws onto the potential applications of XACT to demonstrate it as an innovative imaging technique.
APPROACH
This review navigates the expanding landscape of XACT imaging within the biomedical sphere. Integral topics addressed encompass the refinement of imaging systems and the advancement in image reconstruction algorithms. The review particularly emphasizes XACT's significant biomedical applications.
RESULTS
Key uses, such as breast imaging, bone density maps for osteoporosis, and X-ray molecular imaging, are highlighted to demonstrate the capability of XACT. A unique niche for XACT imaging is its application in dosimetry during radiotherapy, which has been validated on patients.
CONCLUSIONS
Because of its unique property, XACT has great potential in biomedicine and non-destructive testing. We conclude by casting light on potential future avenues in this promising domain.
Topics: Humans; X-Rays; Tomography, X-Ray Computed; Image Processing, Computer-Assisted; Breast; Acoustics; Algorithms; Phantoms, Imaging
PubMed: 38144393
DOI: 10.1117/1.JBO.29.S1.S11510 -
European Journal of Radiology Jun 2022According to the World Health Organization (WHO), at the end of 2020, 7.8 million women alive were diagnosed with breast cancer in the past 5 years, making it the...
According to the World Health Organization (WHO), at the end of 2020, 7.8 million women alive were diagnosed with breast cancer in the past 5 years, making it the world's most prevalent cancer. It is largely recognized and demonstrated that early detection represents the first strategy to follow in the fight against cancer. The effectiveness of mammography screening for early breast cancer detection has been proven in several surveys and studies over the last three decades. The estimation of the Mean Glandular Dose (MGD) is important to understand the radiation-associated risk from breast x-ray imaging exams. It continues to be the subject of numerous studies and debates, since its accuracy is directly related to risk estimation and for optimizing breast cancer screening programs. This manuscript reviews the main dosimetry formalisms used to estimate the MGD in mammography and to understand the continuing efforts to reduce the absorbed dose over the last forty years. The dosimetry protocols were formulated initially for mammography. Digital breast tomosynthesis (DBT) either in conjunction with synthesized digital mammogram (SDM) or with digital mammography (DM), is routinely used in many breast cancer screening programs and consequently the dosimetry protocols were extended for these techniques.
Topics: Breast; Breast Neoplasms; Early Detection of Cancer; Female; Humans; Mammography; Mass Screening; X-Rays
PubMed: 35430441
DOI: 10.1016/j.ejrad.2022.110278 -
ELife May 2023Disentangling human brain connectivity requires an accurate description of nerve fiber trajectories, unveiled via detailed mapping of axonal orientations. However, this...
Disentangling human brain connectivity requires an accurate description of nerve fiber trajectories, unveiled via detailed mapping of axonal orientations. However, this is challenging because axons can cross one another on a micrometer scale. Diffusion magnetic resonance imaging (dMRI) can be used to infer axonal connectivity because it is sensitive to axonal alignment, but it has limited spatial resolution and specificity. Scattered light imaging (SLI) and small-angle X-ray scattering (SAXS) reveal axonal orientations with microscopic resolution and high specificity, respectively. Here, we apply both scattering techniques on the same samples and cross-validate them, laying the groundwork for ground-truth axonal orientation imaging and validating dMRI. We evaluate brain regions that include unidirectional and crossing fibers in human and vervet monkey brain sections. SLI and SAXS quantitatively agree regarding in-plane fiber orientations including crossings, while dMRI agrees in the majority of voxels with small discrepancies. We further use SAXS and dMRI to confirm theoretical predictions regarding SLI determination of through-plane fiber orientations. Scattered light and X-ray imaging can provide quantitative micrometer 3D fiber orientations with high resolution and specificity, facilitating detailed investigations of complex fiber architecture in the animal and human brain.
Topics: Animals; Humans; Chlorocebus aethiops; X-Rays; Scattering, Small Angle; X-Ray Diffraction; Diffusion Magnetic Resonance Imaging; Brain; Image Processing, Computer-Assisted
PubMed: 37166005
DOI: 10.7554/eLife.84024 -
Folia Morphologica 2021Five-fingered hand (5-FH) with completely developed phalanges is a rare phenotype observed so far only in humans and characterised by three phalanges of the 1st ray. A...
BACKGROUND
Five-fingered hand (5-FH) with completely developed phalanges is a rare phenotype observed so far only in humans and characterised by three phalanges of the 1st ray. A long-lasting, debated question is if the missing element of the normal hand 1st ray is the metacarpal or the phalanx. In this study, comparative X-rays morphometry of long bones in normal and 5-FH is carried out with the aim to face this question through homology analysis of long bone segments in the transverse and longitudinal line of normal hand and 5-FH.
MATERIALS AND METHODS
In the normal hand X-rays (n =20) and in a 5-FH X-rays series (n = 9) the relative length of each segment on the ray total length and the index of growth rate (IGR) were assessed. The calculation of the first parameter in normal hand bi-phalangeal thumb was carried out on the 3rd ray total length in the same hand.
RESULTS
The parameters of relative length and the proximal/distal growth rate asymmetry in the post-natal period (assessed through the IGR) confirmed in 5-FH the homology of all the five segment on the transverse line. In the normal control hand, the relative length assessment methodology was biased by the missing segment of the thumb, therefore, the reference to the 3rd ray total length in the same hand (instead of the 1st), allowed the homology analysis of the thumb metacarpal and 1st phalanx with the lateral segments (2nd-5th ray) of the same hand. The 5-FH analysis was used to choose the more appropriate reference ray for the normal hand group.
CONCLUSIONS
The comparative analysis of relative lengths and IGRs in the two groups suggested homology of the (anatomical) 1st metacarpal with the 2nd-5th proximal phalanges in the same hand and that of the (anatomical) 1st proximal phalanx with the 2nd-5th mid phalanges. These data suggest that the missing segment of the normal hand thumb is the metacarpal.
Topics: Fingers; Hand; Humans; Metacarpal Bones; Thumb; X-Rays
PubMed: 32644183
DOI: 10.5603/FM.a2020.0074 -
Acta Biomaterialia Jul 2021Fibrous biocomposites like bone and tendons exhibit a hierarchical arrangement of their components ranging from the macroscale down to the molecular level. The...
Fibrous biocomposites like bone and tendons exhibit a hierarchical arrangement of their components ranging from the macroscale down to the molecular level. The multiscale complex morphology, together with the correlated orientation of their constituents, contributes significantly to the outstanding mechanical properties of these biomaterials. In this study, a systematic road map is provided to quantify the hierarchical structure of a mineralized turkey leg tendon (MTLT) in a holistic multiscale evaluation by combining micro-Computed Tomography (micro-CT), small-angle X-ray scattering (SAXS), and wide-angle X-ray diffraction (WAXD). We quantify the interplay of the main MTLT components with respect to highly ordered organic parts such as fibrous collagen integrating inorganic components like hydroxyapatite (HA). The microscale fibrous morphology revealing different types of porous features and their orientation was quantified based on micro-CT investigations. The quantitative analysis of the alignment of collagen fibrils and HA crystallites was established from the streak-like signal in SAXS using the Ruland approach and the broadening of azimuthal profiles of the small and wide-angle diffraction peaks. It has been in general agreement that HA crystallites are co-aligned with the nanostructure of mineralized tissue. However, we observe relatively lower degree of orientation of HA crystallites compared to the collagen fibrils, which supports the recent findings of the structural interrelations within mineralized tissues. The generic multiscale characterization approach of this study is relevant to any hierarchically structured biomaterials or bioinspired materials from the μm-nm-Å scale. Hence, it gives the basis for future structure-property relationship investigations and simulations for a wide range of hierarchically structured materials. STATEMENT OF SIGNIFICANCE: Many fibrous biocomposites such as tendon, bone, and wood possess multiscale hierarchical structures, responsible for their exceptional mechanical properties. In this study, the 3-dimensional hierarchical structure, the degree of orientation and composition of mineralized tendon extracted from a turkey leg were quantified using a multimodal X-ray based approach combining small-angle X-ray scattering and wide-angle X-ray diffraction with micro-Computed Tomography. We demonstrate that hydroxyapatite (HA) domains are co-aligned with the nanostructure of mineralized tissue. However, the lower degree of orientation of HA crystallites was observed when compared to the collagen fibrils. The generic multiscale characterization approach of this study is relevant to any hierarchically structured biomaterials or bioinspired materials from the micrometer over the nanometer to the Angström scale level.
Topics: Scattering, Small Angle; Tendons; X-Ray Diffraction; X-Ray Microtomography; X-Rays
PubMed: 34052502
DOI: 10.1016/j.actbio.2021.05.022 -
European Radiology Mar 2023To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their...
OBJECTIVE
To develop a two-phased deep learning sorting algorithm for post-X-ray image acquisition in order to facilitate large musculoskeletal image datasets according to their anatomical entity.
METHODS
In total, 42,608 unstructured and pseudonymized radiographs were retrieved from the PACS of a musculoskeletal tumor center. In phase 1, imaging data were sorted into 1000 clusters by a self-supervised model. A human-in-the-loop radiologist assigned weak, semantic labels to all clusters and clusters with the same label were merged. Three hundred thirty-two non-musculoskeletal clusters were discarded. In phase 2, the initial model was modified by "injecting" the identified labels into the self-supervised model to train a classifier. To provide statistical significance, data split and cross-validation were applied. The hold-out test set consisted of 50% external data. To gain insight into the model's predictions, Grad-CAMs were calculated.
RESULTS
The self-supervised clustering resulted in a high normalized mutual information of 0.930. The expert radiologist identified 28 musculoskeletal clusters. The modified model achieved a classification accuracy of 96.2% and 96.6% for validation and hold-out test data for predicting the top class, respectively. When considering the top two predicted class labels, an accuracy of 99.7% and 99.6% was accomplished. Grad-CAMs as well as final cluster results underlined the robustness of the proposed method by showing that it focused on similar image regions a human would have considered for categorizing images.
CONCLUSION
For efficient dataset building, we propose an accurate deep learning sorting algorithm for classifying radiographs according to their anatomical entity in the assessment of musculoskeletal diseases.
KEY POINTS
• Classification of large radiograph datasets according to their anatomical entity. • Paramount importance of structuring vast amounts of retrospective data for modern deep learning applications. • Optimization of the radiological workflow and increase in efficiency as well as decrease of time-consuming tasks for radiologists through deep learning.
Topics: Humans; Deep Learning; Retrospective Studies; X-Rays; Radiography; Algorithms; Musculoskeletal Diseases
PubMed: 36307553
DOI: 10.1007/s00330-022-09184-6