Using Statistical Measures and Density Maps Generated From Chest Computed Tomography Scans to Identify and Monitor COVID-19 Cases in Radiation Oncology Rapidly.

Objectives This study aimed to evaluate quantitative and qualitative screening measures for anomalous computed tomography (CT) scans in cancer patients with potential coronavirus disease 2019 (COVID-19) as an automated detection tool in a radiation oncology treatment setting. Methods We identified a non-COVID-19 cohort and patients with suspected COVID-19 with chest CT scans from February 1, 2020 to June 30, 2020. Lungs were segmented, and a mean normal Hounsfield Unit (HU) histogram was generated for the non-COVID-19 CT scans; these were used to define thresholds for designating the COVID-19-suspected histograms as normal or abnormal. Statistical measures were computed and compared to the threshold levels, and density maps were generated to examine the difference between lungs with and without COVID-19 qualitatively. Results The non-COVID-19 cohort consisted of 70 patients with 70 CT scans, and the cohort of suspected COVID-19 patients consisted of 59 patients with 80 CT scans. Sixty-two patients were positive for COVID-19. The mean HUs and skewness of the intensity histogram discriminated between COVID-19 positive and negative cases, with an area under the curve of 0.948 for positive and 0.944 for negative cases. Skewness correctly identified 57 of 62 positive cases, whereas mean HUs correctly identified 17 of 18 negative cases. Density maps allowed for visualization of the temporal evolution of COVID-19 disease. Conclusions The statistical measures and density maps evaluated here could be employed in an automated screening algorithm for COVID-19 infection. The accuracy is high enough for a simple and rapid screening tool for early identification of suspected infection in patients treated with chemotherapy and radiation therapy already receiving CT scans as part of clinical care. This screening tool could also identify other infections that present critical risks for patients undergoing chemotherapy and radiation therapy, such as pneumonitis.

Association of Race and Ethnicity With Comorbidities and Survival Among Patients With COVID-19 at an Urban Medical Center in New York.

Importance: As of May 11, 2020, there have been more than 290 000 deaths worldwide from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). Risk-adjusted differences in outcomes among patients of differing ethnicity and race categories are not well characterized. Objectives: To investigate whether presenting comorbidities in patients with COVID-19 in New York City differed by race/ethnicity and whether case fatality rates varied among different ethnic and racial groups, controlling for presenting comorbidities and other risk factors. Design, Setting, and Participants: This cohort study included 5902 patients who presented for care to the Montefiore Medical Center, a large urban academic medical center in the Bronx, New York, between March 14 and April 15, 2020, and tested positive for SARS-CoV-2 on reverse transcription quantitative polymerase chain reaction assay. Final data collection was April 27, 2020. Exposures: Patient characteristics, including self-identified ethnicity/race, age, sex, socioeconomic status, and medical comorbidities, were tabulated. Main Outcomes and Measures: Overall survival. Associations between patient demographic characteristics, comorbidities, and race/ethnicity were examined using χ2 tests, and the association with survival was assessed using univariable and multivariable Cox proportional hazards regression, based on time from positive COVID-19 test. Results: Of 9268 patients who were tested, 5902 ethnically diverse patients (63.7%) had SARS-CoV-2. Of these, 3129 patients (53.0%) were women, and the median (interquartile range) age was 58 (44-71) years. A total of 918 patients (15.5%) died within the study time frame. Overall, 1905 patients (32.3%) identified as Hispanic; 1935 (32.8%), non-Hispanic Black; 509 (8.6%), non-Hispanic White; and 171 (2.9%), Asian; the death rates were 16.2% (309), 17.2% (333), 20.0% (102), and 17.0% (29), respectively (P = .25). Hispanic and non-Hispanic Black patients had a higher proportion of more than 2 medical comorbidities with 654 (34.3%) and 764 (39.5%), respectively, compared with 147 (28.9%) among non-Hispanic White patients (P < .001). Hispanic and non-Hispanic Black patients were also more likely to test positive for COVID-19 than White patients, with 1905 of 2919 Hispanic patients (65.3%), 1935 of 2823 non-Hispanic Black patients (68.5%), and 509 of 960 non-Hispanic White patients (53.0%) having positive test results for SARS-CoV-2 (P < .001). While controlling for age, sex, socioeconomic status and comorbidities, patients identifying as Hispanic (hazard ratio, 0.77; 95% CI, 0.61-0.98; P = .03) or non-Hispanic Black (hazard ratio, 0.69; 95% CI, 0.55-0.87; P = .002) had slightly improved survival compared with non-Hispanic White patients. Conclusions and Relevance: In this cohort study of patients with COVID-19 who presented for care at the same urban medical center, non-Hispanic Black and Hispanic patients did not experience worse risk-adjusted outcomes compared with their White counterparts. This finding is important for understanding the observed population differences in mortality by race/ethnicity reported elsewhere.

COVID-19 Incidentally Detected on PET/CT During Work-up for Locally Advanced Head and Neck Cancer.

AIM: To describe the incidental detection of COVID-19 disease on positron-emission tomography/computed tomography (PET/CT) in a patient with cancer despite initial negative swab by polymerase chain reaction (PCR). CASE REPORT: Clinical and radiographic data were obtained from the electronic medical record. Nasopharyngeal swabs were obtained and evaluated for COVID-19 by the Food and Drug Administration-approved reverse transcription-PCR assays. On radiographic examination, PET/CT was consistent with COVID-19-related pneumonia not seen on prior imaging. Initial nasopharyngeal swab 2 days after PET/CT imaging was negative for COVID-19. Subsequent repeat swab 10 days later was positive for COVID-19, while the patient was febrile on screening assessment. The patient remained COVID-19-positive until 1 month after abnormal PET/CT imaging. CONCLUSION: PET/CT can be sensitive for early COVID-19 detection, even in the setting of a negative confirmatory PCR test. This highlights the importance of continued patient surveillance and use of appropriate personal protective equipment to minimize COVID-19 transmission.

Extent of Prior Lung Irradiation and Mortality in COVID-19 Patients With a Cancer History.

PURPOSE: There have been nearly 200,000 deaths worldwide so far from coronavirus disease 2019 (COVID-19), which is caused by a coronavirus called SARS-CoV-2. Cancer history appears to be a poor prognostic factor for COVID-19 patients, although the reasons for this are unclear. In this report, we assess whether extent of prior lung irradiation is a risk factor for death as a result of COVID-19 infection. METHODS AND MATERIALS: Patients who tested positive for COVID-19 between March 14 and April 15, 2020, at our institution and who previously received radiation therapy for cancer in our department were included in this analysis. Patient characteristics and metrics describing the extent of lung irradiation were tabulated. Cox regression models were used to identify predictors of death after COVID-19 diagnosis. A logistic model was used to characterize the association between mean lung radiation therapy dose and 14-day mortality risk after COVID-19 diagnosis. RESULTS: For the study, 107 patients met the inclusion criteria. With a median follow-up of 7 days from COVID-19 diagnosis for surviving patients, 24 deaths have been observed. The actuarial survival rate 14 days after COVID-19 testing is 66%. Increasing mean lung dose (hazard ratio [HR] per Gy = 1.1, P = .002), lung cancer diagnosis (HR = 3.0, P = .034), and receiving radiation therapy between 1 month and 1 year before COVID-19 testing (HR = 3.4, P = .013) were associated with increased risk of death. Our survival model demonstrates a near linear relationship between mortality risk after COVID-19 diagnosis and mean lung radiation therapy dose. CONCLUSIONS: COVID-19 patients with a history of radiation therapy for cancer have a poor prognosis, and mortality risk appears to be associated with extent of lung irradiation. Validation of these findings will be critical as the COVID-19 pandemic continues.