European Journal of Molecular & Clinical Medicine

The term "diabetic nephropathy" refers to a clinical syndrome that includes persistent albuminuria, a consistent decrease in glomerular filtration rate (GFR) that eventually leads to end-stage renal disease, elevated arterial blood pressure, and increased cardiovascular morbidity and mortality. The apparent diffusion coefficient (ADC) has shown potential as a marker of renal function in several investigations, with decreased renal ADC in kidney disease. The aim of this study was to assess the difference in apparent diffusion coefficient (ADC) value in normal and diabetic kidney.
Methods: This was a cross sectional analytical study conducted from January 2021 to October 2022 in in Department of Radio diagnosis with the help of Department of Medicine. The cases coming to the Department of Medicine for routine follow up fulfilling the inclusion (age >18 years of diabetes mellitus with history of diabetic nephropathy). The MRI examination was performed using a 3 Tesla system.Binary logistic regression analysis was used for estimating the parameters of a logistic model (the coefficients in the linear combination). The p-value was taken significant when less than 0.05 and confidence interval of 95% was taken.
Results: In the study 26 (52%) cases were of diabetes mellitus while 24 (48%) cases were taken as control who were non diabetic. Out of 26 cases, majority belong to the stage 3 (46.2%) followed by the stage 4 and stage 5 with 6 (23.1%) cases each. The study included 1 case each of Stage 1 and stage 2. The ROC Analysis to find Accuracy of ADC Parameters for Detecting DM revealed that Lt, Rt and overall ADC values are highly accurate for detecting DM cases as their AUROC values comes out to be 0.999, 0.960 and 1.000 respectively, the very close/equal to perfect standard 1.000.
Conclusion: The magnetic resonance imaging- Apparent diffusion Coefficient (ADC) value is an appropriate method for assessment and evaluation of diabetic nephropathy. Renal ADC values show a significant correlation with clinical stages of diabetic nephropathy, it is a reliable diagnostic tool for differentiation between diabetic nephropathy patients from diabetic patients without nephropathy

Aim: The aim of the present study was to evaluate the role of Diffusion-weighted MRI with Apparent diffusion coefficient (ADC) calculation in fatty liver and chronic liver diseases.
Methods: The study was conducted at Dr. D. Y. Patil Medical College and Hospital and Research Centre in Pimpri, Pune from September 2020 to July 2022. There were 25 cases and 25 controls in the study.
Results:. The mean liver ADC value among cases vs controls was found to 901.48±79x10-6mm²/sec vs. 1238±107x10-6mm²/sec respectively concluding that when compared to the Control group, the mean ADC among Case group was significantly lower. The mean ADC liver among F0 was 1238.72±107.611, F1 was 990.00±24.259, F2 was 926.71±37.326, F3 was 898.20±75.80 and F4 was 826.13±61.98 using MRI elastography-based staging and grading. Mean ADC value decreased with increase in staging of fibrosis maximum sensitivity and specificity were reported for the Non-fibrotic (F0) vs Cirrhosis (F4) with 95.8% and 82.5% respectively with a cut-off value of 1043.50. ADC values showed best performance for discriminating non-fibrotic (F0) from cirrhotic(F4) stage. Lower performance was observed for discriminating differentiate low-stage fibrosis (F1 and F2) from high-stage fibrosis (F3 and F4). The comparison of mean ADC liver between Case group and Control group using the unpaired t-test showed mean ADC liver was significantly reduced among Case group compared to Control group.
Conclusion: The findings of our research demonstrate that hepatic ADC values demonstrated good diagnostic performance to discriminate non fibrotic from cirrhotic liver. This crucial in the determining early stages of the illness while there is still a chance that it can be aborted and reversed. Detection of advanced stages played pivotal role, for screening for hepatocellular carcinoma or other forms of malignancy in cirrhotic patients.

Background
With increase in the proportion of aging dependent population, the need for understanding the
pathogenesis of aging and the risk factors related to age related neurodegeneration is
increasing with definite certainty. Studies pertaining to age related neurodegeneration will
play a role in mitigating the impending issues related to aging population. Studies have
shown the relatively greater involvement of white matter compared to the grey matter with
age and therefore the evaluation of white matter tracts will further shed light onto the
processes that occur with aging.(1)
Methodology
MRI was performed on a 3T MR scanner (General Electric, Signa Pioneer) with a head‑neck
45 coil. The subjects’ brains were evaluated with conventional imaging using routine axial
T2/T1‑weighted and diffusion-tensor imaging (DTI) sequences. The DTI acquisition protocol
which was used is a dual-spin echo single shot echo-planar imaging sequence with the
following parameters: Forty 3mm thick slices with no inter-slice gap. TR=6400ms,
TE=88ms. FOV= 220x220mm2, matrix of 128x128 zero filled to 256x256. DTI was
performed with b=1000s/mm2 using 25 different encoding directions. The Total scanning
time was 11 mins. Various white matter tracts were evaluated from the DTI sequences using
fibertractographyfollowing which the average Apparent Diffusion Coefficient (ADC) and
Fractional Anisotropy (FA) values of each fiber was computed and tabulated with respect to
age.

Delay in development is a frequent pediatric clinical issue that affects 10-15% of children. The
use of an MRI scan is an important part of the thorough evaluation of children who have been
diagnosed with developmental delay. The current study adapted DTI to analyze the brain
morphology of children diagnosed with developmental delay based on developing evidence.
METHODOLOGY
In this cross sectional study we have studied 30 patients in Yenepoya Medical College Hospital,
Mangalore who met the inclusion and exclusion criteria. Study tool used for the study is the use
of Diffusion Tensor Imaging in addition to routine MR Sequences using 3T MRI. The
quantitative analysis of FA and apparent diffusion coefficient (ADC) maps were generated
automatically by the software and analysed.