Endoleak detection using single-acquisition split-bolus dual-energy computer tomography (DECT).

OBJECTIVES: To assess a single-phase, dual-energy computed tomography (DECT) with a split-bolus technique and reconstruction of virtual non-enhanced images for the detection of endoleaks after endovascular aneurysm repair (EVAR). METHODS: Fifty patients referred for routine follow-up post-EVAR CT and a history of at least one post-EVAR follow-up CT examination using our standard biphasic (arterial and venous phase) routine protocol (which was used as the reference standard) were included in this prospective trial. An in-patient comparison and an analysis of the split-bolus protocol and the previously used double-phase protocol were performed with regard to differences in diagnostic accuracy, radiation dose, and image quality. RESULTS: The analysis showed a significant reduction of radiation dose of up to 42 %, using the single-acquisition split-bolus protocol, while maintaining a comparable diagnostic accuracy (primary endoleak detection rate of 96 %). Image quality between the two protocols was comparable and only slightly inferior for the split-bolus scan (2.5 vs. 2.4). CONCLUSIONS: Using the single-acquisition, split-bolus approach allows for a significant dose reduction while maintaining high image quality, resulting in effective endoleak identification. KEY POINTS: • A single-acquisition, split-bolus approach allows for a significant dose reduction. • Endoleak development is the most common complication after endovascular aortic repair (EVAR). • CT angiography is the imaging modality of choice for aortic aneurysm evaluation.

Three-Tesla dynamic contrast-enhanced MRI: a critical assessment of its use for differentiation of renal lesion subtypes.

PURPOSE: To evaluate the ability of dynamic contrast-enhanced (DCE) 3-T MRI for preoperative differentiation between benign and malignant renal tumors and RCC subtypes. METHODS: Sixty consecutive patients undergoing preoperative DCE 3-T MRI of the kidney were evaluated in this retrospective IRB-approved evaluation. Fifty-four malignant tumors and 17 benign tumors upon surgical verification were included. Relative enhancement values of complete lesions and the most enhancing part of the lesions (hotspot) were measured using four repetitions: precontrast, arterial, venous, and delayed. RESULTS: Mean relative enhancement patterns between malignant and benign lesions did not differ significantly during any postcontrast phase (p > 0.05). The highest mean enhancement during all postcontrast phases was identified in clear cell RCC followed by chromophobic RCC. The enhancement pattern in papillary RCC was significantly less than that of non-papillary RCC lesions. Arterial enhancement was an independent predictor for RCC subtypes (papillary vs. non-papillary, p = 0.008). The diagnostic accuracy for differentiation of papillary from non-papillary RCC based on ROC analysis was 76.4% [95% CI 62.2-87.2%]; p < 0.0001. CONCLUSIONS: Dynamic contrast-enhanced MRI at 3 T showed intermediate diagnostic capability for differentiation between papillary and non-papillary RCC subtypes but could not differentiate between benign and malignant renal lesions.

Deep learning analysis provides accurate COVID-19 diagnosis on chest computed tomography.

INTRODUCTION: Computed Tomography is an essential diagnostic tool in the management of COVID-19. Considering the large amount of examinations in high case-load scenarios, an automated tool could facilitate and save critical time in the diagnosis and risk stratification of the disease. METHODS: A novel deep learning derived machine learning (ML) classifier was developed using a simplified programming approach and an open source dataset consisting of 6868 chest CT images from 418 patients which was split into training and validation subsets. The diagnostic performance was then evaluated and compared to experienced radiologists on an independent testing dataset. Diagnostic performance metrics were calculated using Receiver Operating Characteristics (ROC) analysis. Operating points with high positive (>10) and low negative (<0.01) likelihood ratios to stratify the risk of COVID-19 being present were identified and validated. RESULTS: The model achieved an overall accuracy of 0.956 (AUC) on an independent testing dataset of 90 patients. Both rule-in and rule out thresholds were identified and tested. At the rule-in operating point, sensitivity and specificity were 84.4 % and 93.3 % and did not differ from both radiologists (p > 0.05). At the rule-out threshold, sensitivity (100 %) and specificity (60 %) differed significantly from the radiologists (p < 0.05). Likelihood ratios and a Fagan nomogram provide prevalence independent test performance estimates. CONCLUSION: Accurate diagnosis of COVID-19 using a basic deep learning approach is feasible using open-source CT image data. In addition, the machine learning classifier provided validated rule-in and rule-out criteria could be used to stratify the risk of COVID-19 being present.

Placental MRI shows preservation of brain volume in growth-restricted fetuses who suffer substantial reduction of putative functional placenta tissue (PFPT).

OBJECTIVE: Recently, a potentially useful diagnostic approach based on MR diffusion-tensor-imaging (DTI) was reported for the estimation of putative functional placenta tissue (PFPT), thus providing direct information about placental function. Yet, the relation between reduced PFPT and the phenomenon of brain-sparing remains unclear. This study aimed to investigate the relation between brain-sparing and reduced PFPT volume, as found in fetuses with intrauterine growth restriction (IUGR). METHODS: A total of 40 consecutive patients with a US-based diagnosis of placental IUGR were examined using fetal MRI. A control group of 78 patients who received fetal MRI, due to non-placental pathologies, was established. A somatic energy index was calculated as IE=1-(Vbrain/Vpfpt) from brain and PFPT volumes measured with DTI in both groups. IE, Vpfpt, and Vbrain were analyzed with respect to the gestational week. RESULTS: Vbrain corrected for gestational weeks was no different between both groups, while Vpfpt was significantly reduced in IUGR patients. IE was significantly different between both groups and indicated a higher Vbrain at a comparable Vpfpt. CONCLUSIONS: Fetuses with IUGR show preserved energetic resources necessary for brain growth. Because IE drops in IUGR more rapidly as pregnancy progresses, depending on Vpfpt, IE could prove useful for estimating fetal well-being.

Utility and limitations of 3-Tesla diffusion-weighted magnetic resonance imaging for differentiation of renal tumors.

OBJECTIVE: To investigate utility and limitations of 3-Tesla diffusion-weighted (DW) magnetic resonance imaging (MRI) for differentiation of benign versus malignant renal lesions and renal cell carcinoma (RCC) subtypes. MATERIALS AND METHODS: Sixty patients with 71 renal lesions underwent 3 Tesla DW-MRI of the kidney before diagnostic tissue confirmation. The images were retrospectively evaluated blinded to histology. Single-shot echo-planar imaging was used as the DW imaging technique. Apparent diffusion coefficient (ADC) values were measured and compared with histopathological characteristics. RESULTS: There were 54 malignant and 17 benign lesions, 46 lesions being small renal masses ≤ 4 cm. Papillary RCC lesions had lower ADC values (p=0.029) than other RCC subtypes (clear cell or chromophobe). Diagnostic accuracy of DW-MRI for differentiation of papillary from non-papillary RCC was 70.3% resulting in a sensitivity and specificity of 64.3% (95% CI, 35.1-87.2) and 77.1 (95% CI, 59.9-89.6%). Accuracy increased to 83.7% in small renal masses (≤ 4 cm diameter) and sensitivity and specificity were 75.0% and 88.5%, respectively. The ADC values did not differ significantly between benign and malignant renal lesions (p=0.45). CONCLUSIONS: DW-MRI seems to distinguish between papillary and other subtypes of RCCs especially in small renal masses but could not differentiate between benign and malignant renal lesions. Therefore, the use of DW-MRI for preoperative differentiation of renal lesions is limited.

In vivo assessment of putative functional placental tissue volume in placental intrauterine growth restriction (IUGR) in human fetuses using diffusion tensor magnetic resonance imaging.

OBJECTIVES: Intrauterine growth restriction (IUGR) is a diagnostic challenge, since ultrasound fetal biometry (UFB) provides only a 50% detection rate for IUGR. This may be attributable to the fact that UFB does not allow a direct evaluation of functional placental tissue. We hypothesized that direct assessment, using magnetic resonance diffusion tensor imaging (DT-MRI), can provide better detection of IUGR by reliably distinguishing between normal and non-functional placental tissue. METHODS: Patients with normal placenta function (n = 21) and suspected IUGR (n = 14) according to UFB were examined. DT-MRI-based properties of areas of the placenta that were judged to represent normal functional tissue, in normal pregnancies, were used to perform volumetry of the putative functional placental tissue (PFPT) in a control- and an IUGR-group. Fractional anisotropy (FRC), as well as maximum and mean diffusivity were also calculated. RESULTS: PFPT volumetry showed a significant reduction of functional placental tissue in the IUGR group of up to 33%. Analysis of global PFPT, maximum diffusivity, mean diffusivity, and FRC also showed a significant difference. CONCLUSIONS: PFPT volume is dramatically reduced in IUGR. Several DT-MRI parameters suggest an additional placental micro-architecture disturbance in IUGR. PFPT volumetry appears to be a promising tool for improving the detection of IUGR.

Making minority-owned, women-owned and small business contracting a reality.

While government agencies require businesses with which they contract to meet a specific quota for purchasing from minority-owned businesses, many hospitals are exempt from these requirements. Sutter Community Hospitals in Sacramento, CA, however, established a goal to purchase a certain percentage of their services, supplies and equipment from minority-owned, women-owned and small businesses. Several attempts to get a program off the ground met with failure due to problems with locating appropriate businesses and with excessive paperwork and requirements of government entities the hospital system tried to work with. Eventually, Sutter's Materials Management Department defined, in a simple format, what it considered these businesses to be. Without a complicated qualifying process, Sutter had added 74 minority-owned, women-owned and small business suppliers to its vendor list, and 34 are currently providing products and services to the hospitals. It is thus able to build community support, keep money spent by Sutter in the community and engender cultural conscientiousness and acceptance throughout its facilities.