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Detection of COVID-19 pulmonary manifestations with radiotherapy simulation CT imaging.
Wu, Abraham J; Plodkowski, Andrew; Ginsberg, Michelle; Shin, Jacob; LaPlant, Quincey; Shepherd, Annemarie; Shaverdian, Narek; Ng, Victor; Gelblum, Daphna; Braunstein, Lior; Rimner, Andreas.
  • Wu AJ; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America. Electronic address: wua@mskcc.org.
  • Plodkowski A; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Ginsberg M; Department of Radiology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Shin J; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • LaPlant Q; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Shepherd A; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Shaverdian N; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Ng V; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Gelblum D; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Braunstein L; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
  • Rimner A; Department of Radiation Oncology, Memorial Sloan Kettering Cancer Center, New York, NY, United States of America.
Clin Imaging ; 93: 83-85, 2023 Jan.
Article in English | MEDLINE | ID: covidwho-2120455
ABSTRACT
COVID-19 is associated with characteristic lung CT findings. Radiotherapy simulation CT scans may reveal characteristic COVID-19 findings and identify patients with active or prior infection. We reviewed patients undergoing CT simulation at a major cancer center in an early epicenter of the COVID-19 pandemic in the United States. Scans were reviewed by radiation oncologists using established radiographic criteria for COVID-19 pneumonia. Radiographic classifications were compared with available COVID-19 PCR test results. A one-tailed t-test was used to compare the rate of positive COVID-19 tests in radiographically suspicious vs. non-suspicious groups. Scans deemed suspicious were re-reviewed by expert diagnostic radiologists. 414 CT simulation scans were performed on 400 patients. 119 patients had COVID-19 PCR test results available. Radiation oncologists considered 71 scans (17.1%) suspicious for COVID-19. Of these, 23 had corresponding COVID-19 PCR tests, and 3/23 (15.7%) were positive for COVID. 107 non-suspicious scans had corresponding COVID-19 test results, and 9 were positive (8.4%). The difference in positive test results between suspicious and non-suspicious groups was not significant (p = 0.23). Upon re-review by a diagnostic radiologist, 25 (35%) scans deemed suspicious by radiation oncologists were confirmed to meet criteria, while the rest were re-classified as "atypical" for COVID-19. We conclude that radiotherapy simulation CT scans can be reviewed for signs of COVID-19 pneumonia by radiation oncologists. However, suspicious CT simulation was not associated with a higher incidence of COVID infection compared with non-suspicious CT simulation, and there was low concordance between radiation oncologist and diagnostic radiologist classification of scans.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Randomized controlled trials Limits: Humans Language: English Journal: Clin Imaging Journal subject: Diagnostic Imaging Year: 2023 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Diagnostic study / Experimental Studies / Observational study / Randomized controlled trials Limits: Humans Language: English Journal: Clin Imaging Journal subject: Diagnostic Imaging Year: 2023 Document Type: Article