Brain diffusion MRI biomarkers after oncology treatments.

In addition to providing a measurement of the tumor's size and dimensions, magnetic resonance imaging (MRI) provides excellent noninvasive radiographic detection of tumor location. The MRI technique is an important modality that has been shown to be useful in the prognosis, diagnosis, treatment planning, and evaluation of response and recurrence in solid cancers. Diffusion-weighted imaging (DWI) is an imaging technique that quantifies water mobility. This imaging approach is good for identifying sub-voxel microstructure of tissues, correlates with tumor cellularity, and has been proven to be valuable in the early assessment of cytotoxic treatment for a variety of malignancies. Diffusion tensor imaging (DTI) is an MRI method that assesses the preferred amount of water transport inside tissues. This enables precise measurements of water diffusion, which changes according to the direction of white matter fibers, their density, and myelination. This measurement corresponds to some related variables: fractional anisotropy (FA), mean diffusivity (MD), radial diffusivity (RD), axial diffusivity (AD), and others. DTI biomarkers can detect subtle changes in white matter microstructure and integrity following radiation therapy (RT) or chemoradiotherapy, which may have implications for cognitive function and quality of life. In our study, these indices were evaluated after brain chemoradiotherapy.

Increased incidence of the type 1 diabetes and diabetic ketoacidosis severity in children during COVID-19 pandemic.

AIM: The effect of COVID-19 on the occurrence of type 1 diabetes and ketoacidosis in children and adolescent. METHODS: In this descriptive-analytical cross-sectional study, the records of all children and adolescents hospitalized due to type1 diabetes for two years ago and during the COVID-19 pandemic and its peaks were investigated (January 2018-2022). Also, the desired variables including the frequency of hospitalized patients (known and new cases), the frequency of DKA, the severity of DKA, the duration of discharge from DKA, age, body mass index, duration of hospitalization, clinical symptoms including cerebral edema, laboratory data and the total daily dose insulin required at the time of discharge were compared and statistically analyzed. RESULTS: Out of the 334 hospitalized T1DM patients, the rate of new T1DM patients was significantly higher (P = 0.006) during the pandemic. Clearly, there were more cases of DKA during the pandemic (P = 0.007). The higher severity of DKA (0.026) and the need for higher doses of insulin (P = 0.005) were also observed. The hospitalization rate was higher during the corona peaks, particularly peaks 1 and 4, compared to the non-peak days of COVID-19. CONCLUSION: The increase in the incidence of diabetes (new cases) in the pandemic can suggest the role of the COVID-19 virus as an igniter. Also, as a trigger for the higher incidence of DKA with higher severities, which is probably caused by more damage to the pancreatic beta cells and requires higher doses of insulin.

HRCTCov19-a high-resolution chest CT scan image dataset for COVID-19 diagnosis and differentiation.

INTRODUCTION: Computed tomography (CT) was a widely used diagnostic technique for COVID-19 during the pandemic. High-Resolution Computed Tomography (HRCT), is a type of computed tomography that enhances image resolution through the utilization of advanced methods. Due to privacy concerns, publicly available COVID-19 CT image datasets are incredibly tough to come by, leading to it being challenging to research and create AI-powered COVID-19 diagnostic algorithms based on CT images. DATA DESCRIPTION: To address this issue, we created HRCTCov19, a new COVID-19 high-resolution chest CT scan image collection that includes not only COVID-19 cases of Ground Glass Opacity (GGO), Crazy Paving, and Air Space Consolidation but also CT images of cases with negative COVID-19. The HRCTCov19 dataset, which includes slice-level and patient-level labeling, has the potential to assist in COVID-19 research, in particular for diagnosis and a distinction using AI algorithms, machine learning, and deep learning methods. This dataset, which can be accessed through the web at http://databiox.com , includes 181,106 chest HRCT images from 395 patients labeled as GGO, Crazy Paving, Air Space Consolidation, and Negative.

The Clinical Role of CXCR4-Targeted PET on Lymphoproliferative Disorders: A Systematic Review.

Background/Objectives: We conducted a comprehensive investigation to explore the pathological expression of the CXCR4 receptor in lymphoproliferative disorders (LPDs) using [68Ga]Ga-Pentixafor PET/CT or PET/MRI technology. The PICO question was as follows: What is the diagnostic role (outcome) of [68Ga]Ga-Pentixafor PET (intervention) in patients with LPDs (problem/population)? Methods: The study was written based on the reporting items for systematic reviews and meta-analyses (PRISMA) 2020 guidelines, and it was registered on the prospective register of systematic reviews (PROSPERO) website (CRD42024506866). A comprehensive computer literature search of Scopus, MEDLINE, Scholar, and Embase databases was conducted, including articles indexed up to February 2024. To the methodological evaluation of the studies used the quality assessment of diagnosis accuracy studies-2 (QUADAS-2) tool. Results: Of the 8380 records discovered, 23 were suitable for systematic review. Fifteen studies (on 571 LPD patients) focused on diagnosis and staging, and eight trials (194 LPD patients) assessed treatment response. Conclusions: The main conclusions that can be inferred from the published studies are as follows: (a) [68Ga]Ga-Pentixafor PET may have excellent diagnostic performance in the study of several LPDs; (b) [68Ga]Ga-Pentixafor PET may be superior to [18F]FDG or complementary in some LPDs variants and settings; (c) multiple myeloma seems to have a high uptake of [68Ga]Ga-Pentixafor. Overall, this technique is probably suitable for imaging, staging, and follow-up on patients with LPD. Due to limited data, further studies are warranted to confirm the promising role of [68Ga]Ga-Pantixafor in this context.

Diagnostic Accuracy of PET with Different Radiotracers versus Bone Scintigraphy for Detecting Bone Metastases of Breast Cancer: A Systematic Review and a Meta-Analysis.

Due to the importance of correct and timely diagnosis of bone metastases in advanced breast cancer (BrC), we performed a meta-analysis evaluating the diagnostic accuracy of [18F]FDG, or Na[18F]F PET, PET(/CT), and (/MRI) versus [99mTc]Tc-diphosphonates bone scintigraphy (BS). The PubMed, Embase, Scopus, and Scholar electronic databases were searched. The results of the selected studies were analyzed using pooled sensitivity and specificity, diagnostic odds ratio (DOR), positive-negative likelihood ratio (LR+-LR-), and summary receiver-operating characteristic (SROC) curves. Eleven studies including 753 BrC patients were included in the meta-analysis. The patient-based pooled values of sensitivity, specificity, and area under the SROC curve (AUC) for BS (with 95% confidence interval values) were 90% (86-93), 91% (87-94), and 0.93, respectively. These indices for [18F]FDG PET(/CT) were 92% (88-95), 99% (96-100), and 0.99, respectively, and for Na[18F]F PET(/CT) were 96% (90-99), 81% (72-88), and 0.99, respectively. BS has good diagnostic performance in detecting BrC bone metastases. However, due to the higher and balanced sensitivity and specificity of [18F]FDG PET(/CT) compared to BS and Na[18F]F PET(/CT), and its advantage in evaluating extra-skeletal lesions, [18F]FDG PET(/CT) should be the preferred multimodal imaging method for evaluating bone metastases of BrC, if available.