Magnetic Resonance Imaging and 99Tc WBC-SPECT/CT Scanning in Differential Diagnosis between Osteomyelitis and Charcot Neuroarthropathy: A Case Series.

BACKGROUND: Distinguishing between Charcot Neuroarthropathy (CN), osteomyelitis (OM), and CN complicated with superimposed OM in diabetic patients is crucial for the treatment choice. Given that current diagnostic methods lack specificity, advanced techniques, e.g., magnetic resonance imaging (MRI) and 99mTc-HMPAO-WBC Single Photon Emission Computed Tomography (SPECT/CT), are needed. This study addresses the challenges in distinguishing OM and CN. METHODS: We included diabetic patients with CN and soft tissue ulceration. MRI and 99mTc-HMPAO-WBC SPECT/CT were used for the diagnosis. The patients were classified into three probability levels for OM (i.e., Definite, Probable, and Unlikely) according to the Consensus Criteria for Diabetic Foot Osteomyelitis (CC-DFO). RESULTS: Eight patients met the eligibility criteria. MRI, supported by SPECT-CT and CC-DFO, showed consistency with the OM diagnosis in three cases. The key diagnostic features included the location of signal abnormalities and secondary features such as skin ulcers, sinus tracts, and abscesses. Notably, cases with inconclusive MRI were clarified by SPECT/CT, emphasizing its efficacy in challenging scenarios. CONCLUSIONS: The primary objective of this study was to compare the results of MRI and 99mTc-HMPAO-WBC SPECT/CT with the CC-DFO score in the diabetic foot with CN and suspected OM. Advanced imaging offers a complementary approach to distinguish between CN and OM. This can help delineate the limits of the disease for presurgical planning. While MRI is valuable, 99mTc-HMPAO-WBC SPECT/CT provides additional clarity, especially in challenging cases or when metallic implants affect MRI accuracy.

Relationship between imaging-derived parameters and circulating microRNAs to study the degree of lung involvement in hospitalized geriatric patients with COVID-19 pneumonia.

AIM: Chest computed tomography (CT) scan is useful to evaluate the type and extent of lung lesions in coronavirus disease 2019 (COVID-19) pneumonia. This study explored the association between radiological parameters and various circulating serum-derived markers, including microRNAs, in older patients with COVID-19 pneumonia. METHODS: A retrospective analysis was designed to study geriatric patients (≥75 years) with COVID-19 pneumonia, who underwent chest CT scan on admission, and for whom clinical data and serum samples were obtained. To quantify the extent of lung involvement, CT-score, the percentage of healthy lung (HL%), the percentage of ground glass opacity (GGO%), and the percentage of lung consolidation were assessed using computer-aided tools. The association of these parameters with two circulating microRNAs, miR-483-5p and miR-320b, previously identified as biomarkers of mortality risk in COVID-19 geriatric patients, was tested. RESULTS: A total of 73 patients with COVID-19 pneumonia were evaluable (median age 85 years; interquartile range 82-90 years). Among chest CT-derived parameters, the percentage of lung consolidation (HR 1.08, 95% CI 1.02-1.14), CT-score (HR 1.14, 95% CI 1.03-1.25), and HL% (HR 0.97, 95% CI 0.95-0.99) emerged as significant predictors of mortality, whereas non-significant trends toward increased mortality were observed in patients with higher GGO%. We also found a significant positive association between serum miR-483-5p and GGO% (correlation coefficient 0.28; P = 0.018) and a negative association with HL% (correlation coefficient -0.27; P = 0.023). CONCLUSIONS: Overall, the extent of lung consolidation can be confirmed as a prognostic parameter of COVID-19 pneumonia in older patients. Among various serum-derived markers, miR-483-5p can help in exploring the degree of lung involvement, due to its association with higher GGO% and lower HL%. Geriatr Gerontol Int 2024; ••: ••-••.

Radiomics and Artificial Intelligence for the Diagnosis and Monitoring of Alzheimer's Disease: A Systematic Review of Studies in the Field.

The use of radiomics and artificial intelligence applied for the diagnosis and monitoring of Alzheimer's disease has developed in recent years. However, this approach is not yet completely applicable in clinical practice. The aim of this paper is to provide a systematic analysis of the studies that have included the use of radiomics from different imaging techniques and artificial intelligence for the diagnosis and monitoring of Alzheimer's disease in order to improve the clinical outcomes and quality of life of older patients. A systematic review of the literature was conducted in February 2023, analyzing manuscripts and articles of the last 5 years from the PubMed, Scopus and Embase databases. All studies concerning discrimination among Alzheimer's disease, Mild Cognitive Impairment and healthy older people performing radiomics analysis through machine and deep learning were included. A total of 15 papers were included. The results showed a very good performance of this approach in the differentiating Alzheimer's disease patients-both at the dementia and pre-dementia phases of the disease-from healthy older people. In summary, radiomics and AI can be valuable tools for diagnosing and monitoring the progression of Alzheimer's disease, potentially leading to earlier and more accurate diagnosis and treatment. However, the results reported by this review should be read with great caution, keeping in mind that imaging alone is not enough to identify dementia due to Alzheimer's.

Change of accent as an atypical onset of non fluent primary progressive aphasia.

Language disorders can be the first symptom of many neurodegenerative diseases, including Alzheimer's disease (AD) and primary progressive aphasia (PPA). The main variants of PPA are: the non-fluent/agrammatic variant, the semantic variant and the logopenic variant.Several additional variants of PPA, however, have been described and are considered as atypical presentations. We describe the case of a woman presenting a progressive isolated language disturbance, characterized by an early dysprosodia, phonological and semantic paraphasias, agrammatism, impairment in repetition, writing of non-words and sentence comprehension. This clinical picture pointed to an atypical presentation of the non-fluent variety. The frequent symptom overlap between the different variants of PPA, most likely reflecting differences in the topography of the pathological changes, needs to be considered in the definition of diagnostic criteria.