Comparison of diagnostic performance of radiologist- and AI-based assessments of T2-FLAIR mismatch sign and quantitative assessment using synthetic MRI in the differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, IDH-mutant and 1p/19q-codeleted

PURPOSE

This study aimed to compare assessments by radiologists, artificial intelligence (AI), and quantitative measurement using synthetic MRI (SyMRI) for differential diagnosis between astrocytoma, IDH-mutant and oligodendroglioma, and IDH-mutant and 1p/19q-codeleted and to identify the superior method.

METHODS

Thirty-three cases (men, 14; women, 19) comprising 19 astrocytomas and 14 oligodendrogliomas were evaluated. Four radiologists independently evaluated the presence of the T2-FLAIR mismatch sign. A 3D convolutional neural network (CNN) model was trained using 50 patients outside the test group (28 astrocytomas and 22 oligodendrogliomas) and transferred to evaluate the T2-FLAIR mismatch lesions in the test group. If the CNN labeled more than 50% of the T2-prolonged lesion area, the result was considered positive. The T1/T2-relaxation times and proton density (PD) derived from SyMRI were measured in both gliomas. Each quantitative parameter (T1, T2, and PD) was compared between gliomas using the Mann-Whitney U-test. Receiver-operating characteristic analysis was used to evaluate the diagnostic performance.

RESULTS

The mean sensitivity, specificity, and area under the curve (AUC) of radiologists vs. AI were 76.3% vs. 94.7%; 100% vs. 92.9%; and 0.880 vs. 0.938, respectively. The two types of diffuse gliomas could be differentiated using a cutoff value of 2290/128 ms for a combined 90th percentile of T1 and 10th percentile of T2 relaxation times with 94.4/100% sensitivity/specificity with an AUC of 0.981.

CONCLUSION

Compared to the radiologists' assessment using the T2-FLAIR mismatch sign, the AI and the SyMRI assessments increased both sensitivity and objectivity, resulting in improved diagnostic performance in differentiating gliomas.

Multiple mutations of SARS-CoV-2 Omicron BA.2 variant orchestrate its virological characteristics

IMPORTANCE

Most studies investigating the characteristics of emerging SARS-CoV-2 variants have been focusing on mutations in the spike proteins that affect viral infectivity, fusogenicity, and pathogenicity. However, few studies have addressed how naturally occurring mutations in the non-spike regions of the SARS-CoV-2 genome impact virological properties. In this study, we proved that multiple SARS-CoV-2 Omicron BA.2 mutations, one in the spike protein and another downstream of the spike gene, orchestrally characterize this variant, shedding light on the importance of Omicron BA.2 mutations out of the spike protein.

Estimation of effective imaging dose and excess absolute risk of secondary cancer incidence for four-dimensional cone-beam computed tomography acquisition

This study was conducted to estimate the organ equivalent dose and effective imaging dose for four-dimensional cone-beam computed tomography (4D-CBCT) using a Monte Carlo simulation, and to evaluate the excess absolute risk (EAR) of secondary cancer incidence. The EGSnrc/BEAMnrc were used to simulate the on-board imager (OBI) from the TrueBeam linear accelerator. Specifically, the OBI was modeled based on the percent depth dose and the off-center ratio was measured using a three-dimensional (3D) water phantom. For clinical cases, 15 lung and liver cancer patients were simulated using the EGSnrc/DOSXYZnrc. The mean absorbed doses to the lung, stomach, bone marrow, esophagus, liver, thyroid, bone surface, skin, adrenal glands, gallbladder, heart, intestine, kidney, pancreas and spleen, were quantified using a treatment planning system, and the equivalent doses to each organ were calculated. Subsequently, the effective dose was calculated as the weighted sum of the equivalent dose, and the EAR of the secondary cancer incidence was determined for each organ with the use of the biologic effects of ionizing radiation (BEIR) VII model. The effective doses were 3.9 ± 0.5, 15.7 ± 2.0, and 7.3 ± 0.9 mSv, for the lung, and 4.2 ± 0.6, 16.7 ± 2.4, and 7.8 ± 1.1 mSv, for the liver in the respective cases of the 3D-CBCT (thorax, pelvis) and 4D-CBCT modes. The lung EARs for males and females were 7.3 and 10.7 cases per million person-years, whereas the liver EARs were 9.9 and 4.5 cases per million person-years. The EAR increased with increasing time since radiation exposure. In clinical studies, we should use 4D-CBCT based on consideration of the effective dose and EAR of secondary cancer incidence.