Contrast enhancement in abdominal computed tomography: influence of photon energy of different scanners

Feasibility of Bone Mineral Density and Bone Microarchitecture Assessment Using Deep Learning With a Convolutional Neural Network

OBJECTIVES

We evaluated the feasibility of using deep learning with a convolutional neural network for predicting bone mineral density (BMD) and bone microarchitecture from conventional computed tomography (CT) images acquired by multivendor scanners.

METHODS

We enrolled 402 patients who underwent noncontrast CT examinations, including L1-L4 vertebrae, and dual-energy x-ray absorptiometry (DXA) examination. Among these, 280 patients (3360 sagittal vertebral images), 70 patients (280 sagittal vertebral images), and 52 patients (208 sagittal vertebral images) were assigned to the training data set for deep learning model development, the validation, and the test data set, respectively. Bone mineral density and the trabecular bone score (TBS), an index of bone microarchitecture, were assessed by DXA. BMDDL and TBSDL were predicted by deep learning with a convolutional neural network (ResNet50). Pearson correlation tests assessed the correlation between BMDDL and BMD, and TBSDL and TBS. The diagnostic performance of BMDDL for osteopenia/osteoporosis and that of TBSDL for bone microarchitecture impairment were evaluated using receiver operating characteristic curve analysis.

RESULTS

BMDDL and BMD correlated strongly (r = 0.81, P < 0.01), whereas TBSDL and TBS correlated moderately (r = 0.54, P < 0.01). The sensitivity and specificity of BMDDL for identifying osteopenia or osteoporosis were 93% and 90%, and 100% and 94%, respectively. The sensitivity and specificity of TBSDL for identifying patients with bone microarchitecture impairment were 73% for all values.

CONCLUSIONS

The BMDDL and TBSDL derived from conventional CT images could identify patients who should undergo DXA, which could be a gatekeeper tool for detecting latent osteoporosis/osteopenia or bone microarchitecture impairment.

Evaluation of the Practice of Performing Abdominal CT Scan with Manually Administered Fixed Dose of Contrast in Achieving Adequate Hepatic Enhancement: An Institutional-Based Cross-Sectional Study

Background

Intravenous (IV) iodine-based contrast agents are administered during computed tomography (CT) examination to enhance the density differences between lesions and surrounding parenchyma, which is important for lesion characterization, and to demonstrate vascular anatomy and vessel patency. Quality of contrast enhancement has a significant influence on diagnostic interpretation and subsequent management. In this study, we assessed the quality of portal venous phase abdominal CT scans performed with a manual injection of a fixed dose of contrast, which is the routine practice at Tikur Anbessa Specialized Hospital (TASH). The effect of age and sex was also assessed.

Method

A hospital-based retrospective review was performed to identify patients who have had a precontrast and postcontrast abdominal CT scan from November 4, 2020, to September 30, 2022. All patients with abdominal CT scans having precontrast and portal venous phase scans were included in the study. All CT scans were reviewed by the principal investigator and the quality of contrast enhancement was assessed.

Results

In this study, there were a total of 379 patients. The mean hepatic attenuations in precontrast and portal venous phase scans were 59.05 ± 6.69 HU and 103.73 ± 12.84 HU. The proportion of scans with less than 50 HU enhancement was 68% (n = 258). There was a significant association between age and sex with contrast enhancement.

Conclusion

The hepatic contrast enhancement pattern of abdominal CT scan at the study institution reveals a concerning degree of image quality. This is evidenced by the high number of suboptimal contrast enhancement indices and the highly variable enhancement patterns across different patients. This can have a negative impact on the diagnostic performance of CT imaging and can adversely affect the management. Furthermore, both sex and age affect the pattern of enhancement.

Evaluation of Computed Tomography Attenuation Value of Proximal Femoral Marrow to Diagnose and Differentiate Hematologic Malignancies, Myelofibrosis, and Aplastic Anemia

OBJECTIVE

The aim of this study was to diagnose hematologic diseases using computed tomography (CT) number of proximal femoral marrow.

METHODS

The average CT number of marrow in hematologic diseases was measured on the caudal side of the greater trochanter.

RESULTS

The CT numbers were -60.3 ± 16.8 in 12 patients with aplastic anemia, -53.2 ± 19.4 in 11 patients with monoclonal gammopathy of undetermined significance, -44.2 ± 21.1 in 10 normal controls, -30.9 ± 42.3 in 9 patients with chronic lymphatic leukemia, -29.8 ± 29.9 in 17 patients with benign anemia, -13.7 ± 40.9 in 33 patients with multiple myeloma, 0.32 ± 44.6 in 17 patients with myelodysplastic syndrome (MDS), 18.7 ± 40.0 in 44 patients with acute myeloid leukemia, 50.3 ± 27.4 in 13 patients with acute lymphatic leukemia, 51.5 ± 16.8 in 8 patients with myelofibrosis, and 56.4 ± 15.6 in 9 patients with chronic myeloid leukemia. Significant differences were observed between acute myeloid leukemia and MDS, between MDS and aplastic anemia, and between multiple myeloma and monoclonal gammopathy of undetermined significance (P < 0.01).

CONCLUSION

The marrow CT numbers may be indicators of hematologic diseases and can be used as a diagnostic tool.

Influence of beam hardening in dual-energy CT imaging: phantom study for iodine mapping, virtual monoenergetic imaging, and virtual non-contrast imaging

In this study, we investigated the influence of beam hardening on the dual-energy computed tomography (DECT) values of iodine maps, virtual monoenergetic (VME) images, and virtual non-contrast (VNC) images. 320-row DECT imaging was performed by changing the x-ray tube energy for the first and second rotations. DECT values of 5 mg/mL iodine of the multi-energy CT phantom were compared with and without a 2-mm-thick attenuation rubber layer (~700 HU) wound around the phantom. It was found that the CT density values UH, with/without the rubber layer had statistical differences in the iodine map (184 ± 0.7 versus 186 ± 1.8), VME images (125 ± 0.3 versus 110 ± 0.4), and VNC images (−58 ± 0.7 versus −76 ± 1.7) (p < 0.010 for all). This suggests that iodine mapping may be underestimated by DECT and overestimated by VME imaging because of x-ray beam hardening. The use of VNC images instead of plain CT images requires further investigation because of underestimation.