Online ISSN: 2515-8260

Keywords : MRI

Balanced GradientEcho (FIESTA)- MRI Evaluation Of The Fatty Liver Disease.

Fatih Düzgün; GökhanPekindil .

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 3, Pages 2582-2587

FIESTA (FastImagingEmployingSteady-stateAcquisition) is
commonlyacceptedthatbelongstotheclass of gradient-echosequence (1). FIESTA has
provedto be useful in abdominalimagingformagneticresonansimaging (MRI) of
gastrointestinalsystem, oncologicimagings, assessingvascularpatency. However, FIESTA
MRI findings of fattyliver has not previouslybeenreported, although it
describedthesignalreductionduetofat in previousarticles.
Weobservedthatthepatientswithfattyliver had lowersignalintensity (SI) values at FIESTA
sequencescomparedto normal patientswithoutfattyliver.
ntswho had detectedfattyliver at T1W in-out of phase MRI (IOP-MRI)
imageswereevaluatedwithcoronalFIESTA sequence at 1.5 Teslascanner.
Allpatientswereobtained FIESTA sequenceusingthesame MRI acqusitionparameters.
LiverandspleenSI’sweremeasured as usingsame ROI on coronal FIESTA
sequencesandlivertospleen SI ratiowerecalculated. Allvalueswerecompared.
Decrease in SI of thefattyliver on FIESTA images is
negativelycorrelatedwiththefattyfraction of theliver. Patientswithfattyliver had liver / spleen
SI ratiofrom 0.15 to 0.71 (mean 0.39), and 0.41 to 0.96 in thecontrolgroup (mean 0.70).
Therewas a statisticallysignificantdifference.
Webelievesuggestthatbalancedgradientechosequencesuch as FIESTA, can
detectfattyliverhoweverfurtherstudiesarerequiredforevaluatethecapability of thesequence in
evaluation of fattyfraction of theliver.

Balanced GradientEcho (FIESTA)- MRI Evaluation Of The Fatty Liver Disease

Fatih Düzgün; GökhanPekindil .

European Journal of Molecular & Clinical Medicine, 2021, Volume 8, Issue 3, Pages 966-971

FIESTA (FastImagingEmployingSteady-stateAcquisition) is commonlyacceptedthatbelongstotheclass of gradient-echosequence (1). FIESTA has provedto be useful in abdominalimagingformagneticresonansimaging (MRI) of
gastrointestinalsystem, oncologicimagings, assessingvascularpatency. However, FIESTA MRI findings of fattyliver has not previouslybeenreported, although it describedthesignalreductionduetofat in previousarticles. Weobservedthatthepatientswithfattyliver had lowersignalintensity (SI) values at FIESTA sequencescomparedto normal patientswithoutfattyliver.

Segmentation on Brain Cancer Disease using Deep Learning Techniques

J. Josphin Mary; R. Charanya; V. Shanthi; G. Sridevi; Meda Srinivasa Rao

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 9, Pages 1439-1446
DOI: 10.31838/ejmcm.07.09.153

Segmenting brain tumors is a major challenge in the production of scientific pictures. To order to maximize care outcomes and increasing the hospital success rate, early detection of brain tumors plays an important part. A challenging and time-consuming job is the manual segmentation of brain tumors from large quantities of MRI images produced in clinical routine. Automatic brain tumor segmentation is possible. This article aims to analyze strategies for the segmentation of brain tumors dependent on MRI. Automatic segmentation using deep learning approaches has recently been proven common because these approaches accomplish the latest findings much better than other methods would solve this issue. Deep learning approaches may also provide for effective analysis and unbiased interpretation of vast volumes of picture evidence dependent on MRI. There are many papers on MRI based brain tumor segmentation which focus on traditional methods. Different from others, we concentrate on the recent trend in the field of deep learning. Next, the brain tumors and techniques for segmenting the brain tumor are added. Then, the new architectures are explored with a emphasis on the current development in deep learning methods. Finally, an evaluation is introduced and further improvements are discussed to standardize brain tumor segmentation procedures dependent on MRI in the day-to-day clinical practice.

Survey of the Occupational and Patients Biological Risks in Magnetic Resonance Imaging Departments

Batil Alonazi

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 10, Pages 311-319

Background: Technologists are exposed to a strong magnetic field (1.5-3.0 Tesla), higher than the earth magnetic field (≈0.5mT). In addition to that, the exposure to the radiofrequency (RF) may create currents producing skin burns. This study's objective was to assess the magnetic resonance imaging (MRI) safety practices in specific departments in Saudi Arabia in the Riyadh region, evaluate the incidence of biological effects and health implications of the electromagnetic fields present during MR scans, and to detect the occupational hazards. Methods: A survey questionnaire was designed and used to stimulate the target population's views on aspects of MRI safety and detected risks. The survey's target population includes consultants, radiologists, technologists, patients, and others who underwent MRI procedures. Results: A total of 28 technologists were responded from the five hospitals. The study results showed that 50% of the technologist reported various levels of effects, including vertigo and lack of concentration. It is well documented that exposure to MRI requires special consideration due to high magnetic field exposure. Conclusions: This study's main findings are that radiology nurses and patients in MRI units are highly exposed to the magnetic field, especially before and after MRI examination. Any department did not report projectile hazards. Staff is exposed to various degrees of radiation risks. No incident or accident was reported in all investigated hospitals. The staff is well protected in light of the current practice.


Dr. Amruta Dinesh Varma; Rajasbala Dhande

European Journal of Molecular & Clinical Medicine, 2020, Volume 7, Issue 2, Pages 1977-1982

Abstract: Background: Understanding the RELATION between anterior cruciate ligament
and postero lateral corner TRAUMA with antero-lateral ligament of knee with it’s clinical
diagnosis would help us better understand the pattern of injury and to take proper
treatment action .Objectives :To find the correlation between pattern of injury of
anterolateralligament , anterior cruciate ligament and posterolateral corner injury on MRI
with it’s clinical correlation and associated findings. Methodology: A cross-sectional study
will be done at Acharya Vinoba Bhave Rural Hospital, Sawangi, involving52 patients who
present with knee trauma for MRI. The sample will be selected and involvement of
Anterior cruciate ligament ,postero lateral corner injury and antero-lateral ligament with
associated findings will be evaluated using T1, T2 and PD MRI sequences. These will be
compared and there association will be calculated which can be used for better planning of
treatment. Results: After appropriate statistical analysis, we expect to find association
between anterolateral ligament and anterior cruciate ligament tear with posterolateral
corner injury and this will be considered for reconstruction. Conclusion: In this
observational study, we expect associations between injured ligaments with aid of clinical
findings . We also expect to find a positive association between anterolateral ligament with
posterolateral corner injury and anterior cruciate ligament tear.