Current Medical Imaging Reviews最新文献

Background: Despite the availability of vaccines, there is an increasing number of SARS-CoV-2-breakthrough-infections.

Objective: The aim of this study was to determine whether there is a radiological difference in lung parenchymal involvement between infected vaccinated and unvaccinated patients. Additionally, we aimed to investigate whether vaccination has an impact on the course of illness and the need for intensive care.

Methods: This study includes all patients undergoing chest computed tomography (CT) or x-ray imaging in case of a proven SARS-CoV-2 infection between September and November 2021. Anonymized CT and x-ray images were reviewed retrospectively and in consensus by two radiologists, applying an internal severity score scheme for CT and x-ray as well as CARE and BRIXIA scores for x-ray. Radiological findings were compared to vaccination status, comorbidities, inpatient course of the patient's illness and the subjective onset of symptoms.

Results: In total, 38 patients with acute SARS-CoV-2 infection underwent a CT scan, and 168 patients underwent an x-ray examination during the study period. Of these, 32% were vaccinated in the CT group, and 45% in the x-ray group. For the latter, vaccinated patients exhibited significantly more comorbidities (cardiovascular (p=0.002), haemato-oncological diseases (p=0.016), immunosuppression (p=0.004)), and a higher age (p<0.001). Vaccinated groups showed significantly lower extent of lung involvement (severity scores in CT cohort and x-ray cohort both p≤0.020; ARDS 42% in unvaccinated CT cohort vs. 8% in vaccinated CT cohort). Furthermore, vaccinated patients in the CT cohort had significantly less need for intensive care treatment (p=0.040).

Conclusion: Our data suggest that vaccination, in the case of breakthrough infection, favours a milder course of illness concerning lung parenchymal involvement and the need for intensive care, despite negative predictors, such as immunosuppression or other pre-existing conditions.

The 2021 World Health Organization (WHO) Classification of Tumors of the Central Nervous System has brought a transformative shift in the categorization of adult gliomas. Departing from traditional histological subtypes, the new classification system is guided by molecular genotypes, particularly the Isocitrate Dehydrogenase (IDH) mutation. This alteration reflects a pivotal change in understanding tumor behavior, emphasizing the importance of molecular profiles over morphological characteristics. Gliomas are now categorized into IDH-mutant and IDH wildtype, with significant prognostic implications. For IDH-mutant gliomas, the concurrent presence of Alpha-Thalassemia/mental retardation syndrome X-linked (ATRX) gene expression and co-deletion of 1p19q genes further refine classification. In the absence of 1p19q co-deletion, further categorization depends on the phenotypic expression of CDKN2A/B. Notably, IDH wildtype gliomas exhibit a poorer prognosis, particularly when associated with TERT promoter mutations, EGFR amplification, and +7/-10 co-deletion. Although not part of the new guidelines, the methylation status of the MGMT gene is crucial for guiding alkylating agent treatment. The integration of structural and functional Magnetic Resonance Imaging (MRI) techniques may play a vital role in evaluating these genetic phenotypes, offering insights into tumor microenvironment changes. This multimodal approach may enhance diagnostic precision, aid in treatment planning, and facilitate effective prognosis evaluation of glioma patients.

Objective: To investigate the influence of improved exposure parameters on the image quality of multi-slice spiral computed tomography in nasal bone fracture imaging.

Methods: Fifty patients with optimised parameters combined with coronal scanning were allocated to the modified group and 50 patients with routine scanning parameters to the routine group. The image quality and nasal bone display of the two groups were assessed and statistically analysed, and the quality of scanned images before and after parameter optimisation was compared.

Results: The optimised image quality was better than that of conventional scanning parameters. The parameters used were 120 kv, 180 mA, a layer thickness of 0.625 mm, a layer spacing of 0.312 mm, a pitch of 0.516:1, a frame speed of 1 s, a scanning field of 12 cm and a reconstructed layer thickness for scanning of 0.625 mm; the scanned image was clear, and the parameter optimisation was achieved. This ensures that the annotation data in ITK labelling is more accurate.

Conclusion: The optimised parameters and scanned coronal plane show the nasal bone and its surrounding structures more comprehensively, which is of high diagnostic value for nasal bone fractures. The three-dimensional annotation data based on ITK is more standardised, laying a foundation for the subsequent research of artificial intelligence modelling.

Background: Breast Cancer (BC) is a significant threat affecting women globally. An accurate and reliable disease classification method is required to get an early diagnosis. However, existing approaches lack accurate and robust classification.

Objective: This study aims to design a model to classify BC Histopathology images accurately by leveraging segmentation techniques.

Methods: This work proposes a combined segmentation and classification approach for classifying BC using histopathology images to address these issues. Chan-Vese algorithm is used for segmentation to accurately delineate regions of interest within the histopathology images, followed by the proposed SegEIR-Net (Segmentation using EfficientNet, InceptionNet, and ResNet) for classification. Bilateral Filtering is also employed for noise reduction. The proposed model uses three significant networks, ResNet, InceptionNet, and EfficientNet, concatenates the outputs from each block followed by Dense and Dropout layers. The model is trained on the breakHis dataset for four different magnifications and tested on BACH (BreAst Cancer Histology) and UCSB (University of California, Santa Barbara) datasets.

Results: SegEIR-Net performs better than the existing State-of-the-Art (SOTA) methods in terms of accuracy on all three datasets, proving the robustness of the proposed model. The accuracy achieved on breakHis dataset are 98.66%, 98.39%, 97.52%, 95.22% on different magnifications, and 93.33% and 96.55% on BACH and UCSB datasets.

Conclusion: These performance results indicate the robustness of the proposed SegEIR-Net framework in accurately classifying BC from histopathology images.

Background: Immunoglobulin G4 (Ig G4)-related disease is rare; however, it is a fibroinflammatory disease that has been studied a lot so far. Although the expression pattern varies depending on the organ affected, it usually manifests as organ hypertrophy and organ dysfunction.

Case presentation: A 46-year-old man was referred to our otorhinolaryngology department for left submandibular swelling and tenderness that occurred 2 weeks ago. He was treated with antibiotics (augmentin 625mg, per oral) for 2 weeks, but his symptoms did not improve, and his white blood cell (WBC) count was 10,500 /μL (normal 3,800-10,000 /μL).

Conclusion: A mass-like lesion of the submandibular space has been concluded and the laboratory findings have been satisfactory (IgG4 level); IgG4-related disease, which is rare, but recently often reported, can be included in the differential diagnosis.

Background: Accurate preoperative judgment of lymph node (LN) metastasis is a critical step in creating a treatment strategy and evaluating prognosis in rectal cancer (RC) patients.

Objective: This study aimed to explore the value of T1 mapping and amide proton transfer weighted (APTw) imaging in predicting LN metastasis in patients with rectal cancer.

Methods: In a retrospective study, twenty-three patients with pathologically confirmed rectal adenocarcinoma who underwent MRI and surgery from August 2019 to August 2021 were selected. Then, 3.0T/MR sequences included conventional sequences (T1WI, T2WI, and DWI), APTw imaging, and T1 mapping. Patients were divided into LN metastasis (group A) and non-LN metastasis groups (group B). The intra-group correlation coefficient (ICC) was used to test the inter-observer consistency. Mann-Whitney U test was used to compare the differences between the two groups. Spearman correlation analysis was performed to evaluate the correlation between T1 and APT values. Logistic regression and receiver operating characteristic (ROC) curve analyses were performed to assess the differential performance of each parameter and their combination. The difference between AUCs was compared using the DeLong test.

Results: The APT value in patients with LN metastasis was significantly higher than in those without LN metastasis group (P=0.020). Also, similar results were observed for the T1 values (P=0.001). The area under the ROC curve of the APT value in the prediction of LN metastasis was 0.794; when the cutoff value was 1.73%, the sensitivity and specificity were 71.4% and 88.9%, respectively. The area under the ROC curve of the T1 value was 0.913; when the cutoff value was 1367.36 ms, the sensitivity and specificity were 78.6% and 100.0%, respectively. The area under the ROC curve of T1+APT was 0.929, with a sensitivity of 78.6% and specificity of 100.0%.

Conclusion: APT and T1 values show great diagnostic efficiency in predicting LN metastasis in rectal cancer.

Background: Diabetic Retinopathy (DR) is a growing problem in Asian countries. DR accounts for 5% to 7% of all blindness in the entire area. In India, the record of DR-affected patients will reach around 79.4 million by 2030.

Aims: The main objective of the investigation is to utilize 2-D colored fundus retina scans to determine if an individual possesses DR or not. In this regard, Engineering-based techniques such as deep learning and neural networks play a methodical role in fighting against this fatal disease.

Methods: In this research work, a Computational Model for detecting DR using Convolutional Neural Network (DRCNN) is proposed. This method contrasts the fundus retina scans of the DR-afflicted eye with the usual human eyes. Using CNN and layers like Conv2D, Pooling, Dense, Flatten, and Dropout, the model aids in comprehending the scan's curve and color-based features. For training and error reduction, the Visual Geometry Group (VGG-16) model and Adaptive Moment Estimation Optimizer are utilized.

Results: The variations in a dataset like 50%, 60%, 70%, 80%, and 90% images are reserved for the training phase, and the rest images are reserved for the testing phase. In the proposed model, the VGG-16 model comprises 138M parameters. The accuracy is achieved maximum rate of 90% when the training dataset is reserved at 80%. The model was validated using other datasets.

Conclusion: The suggested contribution to research determines conclusively whether the provided OCT scan utilizes an effective method for detecting DRaffected individuals within just a few moments.

Objectives: To evaluate the diagnostic value of ultrasound-guided attenuation parameter (UGAP) in metabolic fatty liver disease (MAFLD) and to explore the correlation between the attenuation coefficient (AC) value of UGAP and commonly used clinical obesity indicators.

Methods: A total of 121 subjects who had physical examinations from November 2021 to March 2022 were prospectively selected; the height, weight, and waist circumference (WC) of all subjects were collected, and conventional ultrasound and UGAP examinations for all subjects.

Results: Under the standard of conventional ultrasound, among the 121 subjects, 53 had normal liver, 42 had mild fatty liver, 21 had moderate fatty liver, and 5 had severe fatty liver. The mean AC value of 121 patients was 0.66 ± 0.13 dB/cm/MHz. The best cut-off values for diagnosing mild, moderate, and severe fatty liver were 0.65dB/cm/MHz, 0.72dB/cm/MHz, and 0.83dB/cm/MHz, respectively. The area under the curve (AUC) values were 0.891, 0.929, and 0.914, respectively. When grouped by WC, there was a statistically significant difference in AC value between the normal group and the obese group (t=-4.675, P<0.001). Overall WC and within group WC were moderately correlated with the AC value of UGAP (P<0.001).

Conclusions: UGAP has a good diagnostic value in the quantitative evaluation of liver steatosis in MAFLD, and the change of WC can reflect the occurrence of liver steatosis to a certain extent.

Background: Cancer is a major disease that threatens human life and health. Raman spectroscopy can provide an effective detection method.

Objective: The study aimed to introduce the application of Raman spectroscopy to tumor detection. We have introduced the current mainstream Raman spectroscopy technology and related application research.

Methods: This article has first introduced the grim situation of malignant tumors in the world. The advantages of tumor diagnosis based on Raman spectroscopy have also been analyzed. Secondly, various Raman spectroscopy techniques applied in the medical field are introduced. Several studies on the application of Raman spectroscopy to tumors in different parts of the human body are discussed. Then the advantages of combining deep learning with Raman spectroscopy in the diagnosis of tumors are discussed. Finally, the related problems of tumor diagnosis methods based on Raman spectroscopy are pointed out. This may provide useful clues for future work.

Conclusion: Raman spectroscopy can be an effective method for diagnosing tumors. Moreover, Raman spectroscopy diagnosis combined with deep learning can provide more convenient and accurate detection results.

Background: Medical imaging plays a key role in neurosurgery; thereby, imaging and analysis of the soft and hard tissues during bone grinding is of paramount importance for neurosurgeons. Bone grinding, a minimally invasive operation in the field of neurosurgery amid osteotomy, has been used during brain cancer surgery.

Aims and objectives: With increasing attention to neural tissue damage in machining operations, imaging of these neural tissues becomes vital and reducing temperature is imperative.

Method: In the present study, a novel attempt has been made to perform the imaging of bone tissues during the bone grinding procedure and further investigate the relationship between rotational speed, feed rate, depth of cut with cutting forces, and temperature. The role of cutting forces and temperature has been addressed as per the requirements of neurosurgeons. Firstly, a three-factor, three-level design was constructed with a full factorial design. Regression models were employed to construct the models between input parameters and response characteristics. Medical imaging techniques were used to perform a thorough analysis of thermal necrosis and damage to the bone. Subsequently, the non-dominated sorting genetic algorithm (NSGA-III) was used to optimize the parameters for reduction in the cutting forces and temperature during bone grinding while reducing neural tissue damage.

Results: The results revealed that the maximum value of tangential force was 21.32 N, thrust force was 9.25 N, grinding force ratio was 0.453, torque was 4.55 N-mm, and temperature was 59.3°C. It has been observed that maximum temperature was generated at a rotational speed of 55000 rpm, feed rate of 60 mm/min, and depth of cut of 1.0 mm. Histopathological imaging analysis revealed the presence of viable lacunas, empty lacunas, haversian canals, and osteocytes in the bone samples. Furthermore, the elemental composition of the bone highlights the presence of carbon (c) 59.49%, oxygen (O) 35.82%, sodium (Na) 0.11%, phosphorous 1.50%, sulphur 0.33%, chlorine 0.98%, and calcium 1.77%.

Conclusion: The study revealed that compared to the initial scenario, NSGA-III can produce better results without compromising the trial results. According to a statistical study, the rise in temperature during bone grinding was significantly influenced by rotating speed. The density of osteocytes in the lacunas was higher at lower temperatures. Furthermore, the results of surface electron microscopy and energy dispersive spectroscopy revealed the presence of bone over the surface of the grinding burr, which resulted in the loading of the grinding burr. The results of the present investigation will be beneficial for researchers and clinical practitioners worldwide.