Amide proton transfer imaging for differentiation of tuberculomas from high-grade gliomas: Preliminary experience

Amide Proton Transfer-Weighted Magnetic Resonance Imaging for Application in Renal Fibrosis: A Radiological-Pathological-Based Analysis

INTRODUCTION

Renal fibrosis (RF), being the most important pathological change in the progression of CKD, is currently assessed by the evaluation of a biopsy. This present study aimed to apply a novel functional MRI (fMRI) protocol named amide proton transfer (APT) weighting to evaluate RF noninvasively.

METHODS

Male Sprague-Dawley (SD) rats were initially subjected to bilateral kidney ischemia/reperfusion injury (IRI), unilateral ureteral obstruction, and sham operation, respectively. All rats underwent APT mapping on the 7th and 14th days after operation. Besides, 26 patients underwent renal biopsy at the Nephrology Department of Shanghai Tongji Hospital between July 2022 and May 2023. Patients underwent APT and apparent diffusion coefficient (ADC) mappings within 1 week before biopsy. MRI results of both patients and rats were calculated by comparing with gold standard histology for fibrosis assessment.

RESULTS

In animal models, the cortical APT (cAPT) and medullary APT (mAPT) values were positively correlated with the degree of RF. Compared to the sham group, IRI group showed significantly increased cAPT and mAPT values on the 7th and 14th days after surgery, but no group differences were found in ADC values. Similar results were found in human patients. Cortical/medullary APT values were significantly increased in patients with moderate-to-severe fibrosis than in patients with mild fibrosis. ROC curve analysis indicated that APT value displayed a better diagnostic value for RF. Furthermore, combination of cADC and cAPT improved fibrosis detection by imaging variables alone (p < 0.1).

CONCLUSION

APT values had better diagnostic capability at early stage of RF compared to ADC values, and the addition of APT imaging to conventional ADC will significantly improve the diagnostic performance for predicting kidney fibrosis.

Tuberculosis conundrum - current and future scenarios: A proposed comprehensive approach combining laboratory, imaging, and computing advances

Tuberculosis (TB) remains a global threat, with the rise of multiple and extensively drug resistant TB posing additional challenges. The International health community has set various 5-yearly targets for TB elimination: mathematical modelling suggests that a 2050 target is feasible with a strategy combining better diagnostics, drugs, and vaccines to detect and treat both latent and active infection. The availability of rapid and highly sensitive diagnostic tools (Gene-Xpert, TB-Quick) will vastly facilitate population-level identification of TB (including rifampicin resistance and through it, multi-drug-resistant TB). Basic-research advances have illuminated molecular mechanisms in TB, including the protective role of Vitamin D. Also, Mycobacterium tuberculosis impairs the host immune response through epigenetic mechanisms (histone-binding modulation). Imaging will continue to be key, both for initial diagnosis and follow-up. We discuss advances in multiple imaging modalities to evaluate TB tissue changes, such as molecular imaging techniques (including pathogen-specific positron emission tomography imaging agents), non-invasive temporal monitoring, and computing enhancements to improve data acquisition and reduce scan times. Big data analysis and Artificial Intelligence (AI) algorithms, notably in the AI sub-field called “Deep Learning”, can potentially increase the speed and accuracy of diagnosis. Additionally, Federated learning makes multi-institutional/multi-city AI-based collaborations possible without sharing identifiable patient data. More powerful hardware designs - e.g., Edge and Quantum Computing- will facilitate the role of computing applications in TB. However, “Artificial Intelligence needs real Intelligence to guide it!” To have maximal impact, AI must use a holistic approach that incorporates time tested human wisdom gained over decades from the full gamut of TB, i.e., key imaging and clinical parameters, including prognostic indicators, plus bacterial and epidemiologic data. We propose a similar holistic approach at the level of national/international policy formulation and implementation, to enable effective culmination of TB’s endgame, summarizing it with the acronym “TB - REVISITED”.