scholarly journals SPECTRUM OF MAGNETIC RESONANCE IMAGING FINDINGS IN RHINO-ORBITO-CEREBRAL MUCORMYCOSIS PATIENTS DURING SECOND WAVE OF COVID-19 INFECTION IN A TERTIARY CARE HOSPITAL – A PROSPECTIVE STUDY.

2021 ◽  
pp. 43-46
Author(s):  
Sweta Swaika ◽  
Akshara Gupta

Introduction- Mucormycosis is a lethal intrusive opportunistic fungal infection with increased morbidity and mortality. Its most common form is Rhino-Orbital-Cerebral Mucormycosis (ROCM). It has been described more in immunosuppressed people and currently in patients with recent history of/ concomitant Covid-19 infection. Magnetic Resonance Imaging (MRI) has been used to delineate extent of infection and spread and preoperative planning. MRI shows varied T1 and T2 signal intensity lesions with nonenhancement in necrosed tissues and extension of infection into adjacent structures. This prospective study aimed at delineating the spectrum of MRI findings in ROCM patients. Methods and results- A prospective study of 31 patients with ROCM was done in Department of Radiology, Superspeciality hospital, Gajra Raja Medical College, Gwalior in May and June 2021 during second wave of COVID-19 pandemic. We found that 64.5% patients in study group had previously / recently diagnosed diabetes mellitus and 77.4% cases had recently treated or concomitant COVID-19 infection. All the patients had sinonasal involvement at the time of imaging. The other areas of involvement were orbit and its contents, some of adjacent soft tissues, cavernous sinus and cerebral parenchyma, hard palate and cavernous ICA in order of frequency. Conclusion- ROCM is a grave infection which readily causes perivascular, perineural and soft tissue infiltration within a short span of time, hence most of the patients in this study had extension beyond the sinuses at the time of imaging. MRI is an essential tool for early identification of extrasinus extension of disease, detection of intracranial and vascular complications and presurgical planning.

2018 ◽  
Vol 31 (4) ◽  
pp. 362-371 ◽  
Author(s):  
Ravi Datar ◽  
Asuri Narayan Prasad ◽  
Keng Yeow Tay ◽  
Charles Anthony Rupar ◽  
Pavlo Ohorodnyk ◽  
...  

Background White matter abnormalities (WMAs) pose a diagnostic challenge when trying to establish etiologic diagnoses. During childhood and adult years, genetic disorders, metabolic disorders and acquired conditions are included in differential diagnoses. To assist clinicians and radiologists, a structured algorithm using cranial magnetic resonance imaging (MRI) has been recommended to aid in establishing working diagnoses that facilitate appropriate biochemical and genetic investigations. This retrospective pilot study investigated the validity and diagnostic utility of this algorithm when applied to white matter signal abnormalities (WMSAs) reported on imaging studies of patients seen in our clinics. Methods The MRI algorithm was applied to 31 patients selected from patients attending the neurometabolic/neurogenetic/metabolic/neurology clinics at a tertiary care hospital. These patients varied in age from 5 months to 79 years old, and were reported to have WMSAs on cranial MRI scans. Twenty-one patients had confirmed WMA diagnoses and 10 patients had non-specific WMA diagnoses (etiology unknown). Two radiologists, blinded to confirmed diagnoses, used clinical abstracts and the WMSAs present on patient MRI scans to classify possible WMA diagnoses utilizing the algorithm. Results The MRI algorithm displayed a sensitivity of 100%, a specificity of 30.0% and a positive predicted value of 74.1%. Cohen’s kappa statistic for inter-radiologist agreement was 0.733, suggesting “good” agreement between radiologists. Conclusions Although a high diagnostic utility was not observed, results suggest that this MRI algorithm has promise as a clinical tool for clinicians and radiologists. We discuss the benefits and limitations of this approach.


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