Prognostic Value of Vertebral Bone Density in the CT Scans of Sepsis Patients Admitted to the Intensive Care Unit.

AIM: To evaluate the prognostic value of vertebral bone mineral density (BMD) and its relationship with mortality using the computed tomography (CT) scans of sepsis patients admitted to the intensive care unit. METHODS: In this retrospective study, patients diagnosed with sepsis at the intensive care unit between January and December 2022 were evaluated. Bone density was manually measured from the vertebral body using axial CT images. The relationship of clinical variables and patient outcomes with vertebral BMD, mortality, and mechanical ventilation was investigated. A lower BMD (osteoporosis) was defined as ≤100 HU. RESULTS: The study included 213 patients (95 females, 44.6%). The mean age of all patients was 60.1±18.7 years. At least one comorbidity was present in 64.7% (n=138) of the patients, and the most common comorbidity was hypertension (n=73, 34.2%). The mortality rate was 21.1% (n=45), and the mechanical ventilation rate was 17.4% (n=37), both being statistically significantly higher among the patients with a lower BMD (36.4 vs. 12.9%; p<0.001 and 29.7 vs. 10.8%; p=0.001, respectively). The rate of a lower BMD was significantly higher in the mortality group (59.5 vs. 29.5%; p=0.001). In the regression analysis, a lower BMD [odds ratio (OR), 2.785; 95% confidence interval (CI): 1.231-6.346, p=0.014] was a significant independent predictor of mortality. Interobserver agreement for BMD measurement was excellent, with an intraclass correlation coefficient of 0.919 (95% CI: 0.904-0.951). CONCLUSION: Vertebral BMD is a strong independent predictor of mortality and can be easily and reproducible evaluated on the thoracoabdominal CT images of patients admitted to the intensive care unit with a diagnosis of sepsis.

The Prognostic Value of Vertebral Bone Density on Chest CT in Hospitalized COVID-19 Patients.

The aim of this study is to evaluate the prognostic value of the vertebral bone mineral density (BMD) on chest computed tomography (CT) in COVID-19 patients. The chest CT of hospitalized patients with COVID-19 pneumonia were evaluated for Pneumonia Severity Score (PSS) as the ratio of the volume of involved lung parenchyma to the total lung volume. In addition, BMD was manually measured from the vertebral corpus using axial CT images. The relationships of clinical variables, PSS and vertebral BMD with patient outcomes, namely mortality, intensive care unit (ICU) admission and mechanical ventilation were investigated. Lower BMD was defined as ≤100 HU. The study included 209 patients (118 males, 56.4%). As a result of the univariate analysis, the rates of mortality, ICU admission and mechanical ventilation were 17.2% (n = 36), 24.8% (n = 52), and 20.6% (n = 43), respectively, and they were significantly higher among the patients with lower BMD (38.1 vs 13.0%, p < 0.001; 33.4 vs 21.2%, p = 0.002; and 38.1 vs 8.2%, p < 0.001, respectively). In the mortality group, PSS was significantly higher (median, 9 vs 5; p < 0.001) and vertebral BMD was significantly lower (median, 83 vs 139; p < 0.001). Severe clinical incidence was significantly higher in patients with lower BMD compared to those with higher BMD (39.7 vs 24.7% and p = 0.028). There was a significant correlation between clinical classification and lower BMD (r = 0.152 and p = 0.028). The multivariate analysis revealed vertebral BMD [odds ratio (OR), 1.028; 95% CI, 1.011-1.045, p = 0.001) and lower BMD (OR, 4.682; 95% CI, 1.784-12.287, p = 0.002) as significant independent predictors of mortality. Vertebral BMD is a strong independent predictor of mortality that is reproducible and can be easily evaluated on the chest CT images of COVID-19 patients.

Quantitative differentiation of breast lesions at 3T diffusion-weighted imaging (DWI) using the ratio of distributed diffusion coefficient (DDC).

PURPOSE: To investigate the accuracy of diffusion coefficients and diffusion coefficient ratios of breast lesions and of glandular breast tissue from mono- and stretched-exponential models for quantitative diagnosis in diffusion-weighted magnetic resonance imaging (MRI). MATERIALS AND METHODS: We analyzed pathologically confirmed 170 lesions (85 benign and 85 malignant) imaged using a 3.0T MR scanner. Small regions of interest (ROIs) focusing on the highest signal intensity for lesions and also for glandular tissue of contralateral breast were obtained. Apparent diffusion coefficient (ADC) and distributed diffusion coefficient (DDC) were estimated by performing nonlinear fittings using mono- and stretched-exponential models, respectively. Coefficient ratios were calculated by dividing the lesion coefficient by the glandular tissue coefficient. RESULTS: A stretched exponential model provides significantly better fits then the monoexponential model (P < 0.001): 65% of the better fits for glandular tissue and 71% of the better fits for lesion. High correlation was found in diffusion coefficients (0.99-0.81 and coefficient ratios (0.94) between the models. The highest diagnostic accuracy was found by the DDC ratio (area under the curve [AUC] = 0.93) when compared with lesion DDC, ADC ratio, and lesion ADC (AUC = 0.91, 0.90, 0.90) but with no statistically significant difference (P > 0.05). At optimal thresholds, the DDC ratio achieves 93% sensitivity, 80% specificity, and 87% overall diagnostic accuracy, while ADC ratio leads to 89% sensitivity, 78% specificity, and 83% overall diagnostic accuracy. CONCLUSION: The stretched exponential model fits better with signal intensity measurements from both lesion and glandular tissue ROIs. Although the DDC ratio estimated by using the model shows a higher diagnostic accuracy than the ADC ratio, lesion DDC, and ADC, it is not statistically significant. J. Magn. Reson. Imaging 2016;44:1633-1641.

Frequency of hepatic steatosis and its association with the pneumonia severity score on chest computed tomography in adult COVID-19 patients.

BACKGROUND: Recent studies of the coronavirus disease 2019 (COVID-19) demonstrated that obesity is significantly associated with increased disease severity, clinical outcome, and mortality. The association between hepatic steatosis, which frequently accompanies obesity, and the pneumonia severity score (PSS) evaluated on computed tomography (CT), and the prevalence of steatosis in patients with COVID-19 remains to be elucidated. AIM: To assess the frequency of hepatic steatosis in the chest CT of COVID-19 patients and its association with the PSS. METHODS: The chest CT images of 485 patients who were admitted to the emergency department with suspected COVID-19 were retrospectively evaluated. The patients were divided into two groups as COVID-19-positive [CT- and reverse transcriptase-polymerase chain reaction (RT-PCR)-positive] and controls (CT- and RT-PCR-negative). The CT images of both groups were evaluated for PSS as the ratio of the volume of involved lung parenchyma to the total lung volume. Hepatic steatosis was defined as a liver attenuation value of ≤ 40 Hounsfield units (HU). RESULTS: Of the 485 patients, 56.5% (n = 274) were defined as the COVID-19-positive group and 43.5% (n = 211) as the control group. The average age of the COVID-19-positive group was significantly higher than that of the control group (50.9 ± 10.9 years vs 40.4 ± 12.3 years, P < 0.001). The frequency of hepatic steatosis in the positive group was significantly higher compared with the control group (40.9% vs 19.4%, P < 0.001). The average hepatic attenuation values were significantly lower in the positive group compared with the control group (45.7 ± 11.4 HU vs 53.9 ± 15.9 HU, P < 0.001). Logistic regression analysis showed that after adjusting for age, hypertension, diabetes mellitus, overweight, and obesity there was almost a 2.2 times greater odds of hepatic steatosis in the COVID-19-positive group than in the controls (odds ratio 2.187; 95% confidence interval: 1.336-3.580, P < 0.001). CONCLUSION: The prevalence of hepatic steatosis was significantly higher in COVID-19 patients compared with controls after adjustment for age and comorbidities. This finding can be easily assessed on chest CT images.

Does COVID-19 cause an increase in spleen dimensions? Possible effects of immune activation, hematopoietic suppression and microthrombosis.

PURPOSE: To radiologically examine how the spleen size, which has important functions in hematological and immunological balance, is affected in COVID-19. METHODS: Between July 1 and August 31, 2020, consecutive patients diagnosed with COVID-19 were analyzed. Among these patients, those who underwent chest computed tomography (CT) examination at the time of presentation, patients with follow-up CT due to clinical deterioration were included in the study. The CTs of the patients were evaluated in terms of spleen size and volume. RESULTS: A total of 160 patients (88 females, 55%) were included in the study. The mean time between the initial and follow-up CT was 7.2 ± 2.8 days. The splenic volume (244.3 ± 136.7 vs. 303.5 ± 156.3 cm3) and splenic index (421.2 ± 235.5 vs. 523.2 ± 269.4 cm3) values were significantly higher in the follow-up CT compared to the initial CT (p < 0.001). The increase in the splenic volume and splenic index values was 59.2 ± 52.4 cm3 and 101.9 ± 90.3 cm3 (p < 0.001), respectively. The COVID-19 severity score was significantly higher in the follow-up CT compared to the initial CT (3.7 ± 4.2 vs. 12.5 ± 5.7, respectively; p < 0.001). The spleen width measured separately on the initial and follow-up CTs showed a highest positive correlation (r = 0.982, p < 0.001). CONCLUSION: Our study indicates that spleen size increases slightly-moderately in the first stages of the infection, and this increase is correlated with the COVID-19 severity score calculated on the chest CT data, and in this respect, it is similar to infections presenting with cytokine storm.

Diagnostic Value of Diffusion-weighted Imaging and Apparent Diffusion Coefficient Values in the Differentiation of Breast Lesions, Histpathologic Subgroups and Correlation with Prognostic Factors using 3.0 Tesla MR.

OBJECTIVE: The aim of this study was to evaluate the effect of the apparent diffusion coefficient (ADC) and diffusion-weighted imaging in differentiating benign from malignant breast lesions, histopathologic subtypes of breast tumors, and to find a correlation with prognostic factors using 3T MR. MATERIALS AND METHODS: A total of 165 patients aged between 16 and 78 years with 181 histopathologically-verifed breast lesions were enrolled in this study. A 3T MR system and bilateral phased array breast coil was used. Diffusion-weighted imaging was performed with spin echo "echo planar" with "b" values: 50, 400, and 800 seconds/mm2. ADC values were calculated for normal fibroglandular tissue and breast lesions. ADC values of independent groups were compared using Student's t-test. ROC analysis was used to find a threshold ADC value in the differentiation of lesions. RESULTS: The mean ADC values were 1.35±0.16 × 10-3 mm2/s for normal fibroglandular tissue, 1.41±0.24 × 10-3 mm2/s for benign breast lesions and 0.83±0.19 × 10-3 mm2/s for malignant breast lesions. The AUC with ROC analysis was 0.945 and the threshold for ADC was 1.08 × 10-3 mm2/s with a sensitivity and specificity of 92% and 92%, respectively. The threshold value for ADC ratio was 0.9 with 96% sensitivity and 89% specificity. The mean ADC of malignant breast lesions was statistically lower for benign lesions (p<0.01). We found no correlation between the mean ADC values and ER-PR receptor, Her2, and Ki-67 values. CONCLUSION: Diffusion-weighted imaging has high diagnostic value with high sensitivity and specificity in differentiating malignant and benign breast lesions.