Two Russian radiologists have died from complications due to COVID-19, according to reports posted by the regional and national media at the end of last week.
Dr. Victor Parafilo of St. Petersburg died on 15 May at the age of 72. He had taken over reading all diagnostic tests of patients with suspected COVID-19, according to a KXAN36 report.
Parafilo graduated from the Maxim Gorky Donetsk Medical Institute and the S.M. Kirov Military Medical Academy. He served 22 years in his country's armed forces, retiring with the rank of colonel. For 25 years, he served as head of the radiotherapy department at the City Clinical Hospital No. 31.
"We have lost not only a [fine] professional, but also a very dedicated [doctor]," said Dr. Anatoly Ryvkin, head of Hospital No. 31, in the KXAN36 report.
Also, Novosibirsk radiologist Dr. Nelya Nikolaevna Shcheglova died of COVID-19 complications at the age of 69, according to a Global News report.
Her medical career spanned 44 years. She died in Hospital No. 11, which had been repurposed for patients with COVID-19, Global News stated.
![Overview of the study design. (A) The fully automated deep learning framework was developed to estimate body composition (BC) (defined as subcutaneous adipose tissue [SAT] in liters; visceral adipose tissue [VAT] in liters; skeletal muscle [SM] in liters; SM fat fraction [SMFF] as a percentage; and intramuscular adipose tissue [IMAT] in deciliters) from MRI. The fully automated framework comprised one model (model 1) to quantify different BC measures (SAT, VAT, SM, SMFF, and IMAT) as three-dimensional (3D) measures from whole-body MRI scans. The second model (model 2) was trained to identify standardized anatomic landmarks along the craniocaudal body axis (z coordinate field), which allowed for subdividing the whole-body measures into different subregions typically examined on clinical routine MRI scans (chest, abdomen, and pelvis). (B) BC was quantified from whole-body MRI in over 66,000 individuals from two large population-based cohort studies, the UK Biobank (UKB) (36,317 individuals) and the German National Cohort (NAKO) (30,291 individuals). Bar graphs show age distribution by sex and cohort. BMI = body mass index. (C) After the performance assessment of the fully automated framework, the change in BC measures, distributions, and profiles across age decades were investigated. Age-, sex-, and height-adjusted body composition reference curves were calculated and made publicly available in a web-based z-score calculator (https://circ-ml.github.io).](https://img.auntminnieeurope.com/mindful/smg/workspaces/default/uploads/2026/05/body-comp.XgAjTfPj1W.jpg?auto=format%2Ccompress&dpr=2&fit=crop&h=167&q=70&w=250)
