Quantitative Diagnosis of Nonalcoholic Fatty Liver Disease with Ultrasound Attenuation Imaging in a Biopsy-Proven Cohort.

RATIONALE AND OBJECTIVES: To evaluate the performance of attenuation imaging (ATI) based on ultrasound for detection of hepatic steatosis in patients with nonalcoholic fatty liver disease (NAFLD). MATERIALS AND METHODS: This prospective study was approved by our institutional review board (B2021-092R). Written informed consent was obtained from all patients. This study included 60 patients who had clinical suspicion of NAFLD and were referred for liver biopsy after ATI and controlled attenuation parameter (CAP) examinations between September 2020 and December 2021. The histologic hepatic steatosis was graded. The area under curve (AUC) analysis was performed. RESULTS: The success rate of the ATI examination was 100%. The intraobserver reproducibility of ATI was 0.981. The AUCs of ATI for detecting ≥S1, ≥S2, and S3 were 0.968 (cut-off value of 0.671 dB/cm/MHz), 0.911 (cut-off value of 0.726 dB/cm/MHz), and 0.766 (cut-off value of 0.757 dB/cm/MHz), respectively. The AUCs of CAP for detecting ≥S1, ≥S2, and S3 were 0.916 (cut-off value of 258.5 dB/m), 0.872 (cut-off value of 300.0 dB/m), and 0.807 (cut-off value of 315.0 dB/m), respectively. The diagnostic values showed no significant difference between ATI and CAP in detecting ≥S1, ≥S2, and S3 (P = .281, P = .254, and P = .330, respectively). The ATI had significant correlations with high-density lipoprotein cholesterol (P < .001), and with triglycerides (P = .015). CONCLUSION: ATI showed good feasibility and diagnostic performance in the detection of varying degrees of hepatic steatosis in NAFLD patients.

Transfer learning radiomics based on multimodal ultrasound imaging for staging liver fibrosis.

OBJECTIVES: To propose a transfer learning (TL) radiomics model that efficiently combines the information from gray scale and elastogram ultrasound images for accurate liver fibrosis grading. METHODS: Totally 466 patients undergoing partial hepatectomy were enrolled, including 401 with chronic hepatitis B and 65 without fibrosis pathologically. All patients received elastography and got liver stiffness measurement (LSM) 2-3 days before surgery. We proposed a deep convolutional neural network by TL to analyze images of gray scale modality (GM) and elastogram modality (EM). The TL process was used for liver fibrosis classification by Inception-V3 network which pretrained on ImageNet. The diagnostic performance of TL and non-TL was compared. The value of single modalities, including GM and EM alone, and multimodalities, including GM + LSM and GM + EM, was evaluated and compared with that of LSM and serological indexes. Receiver operating characteristic curve analysis was performed to calculate the optimal area under the curve (AUC) for classifying fibrosis of S4, ≥ S3, and ≥ S2. RESULTS: TL in GM and EM demonstrated higher diagnostic accuracy than non-TL, with significantly higher AUCs (all p < .01). Single-modal GM and EM both performed better than LSM and serum indexes (all p < .001). Multimodal GM + EM was the most accurate prediction model (AUCs are 0.950, 0.932, and 0.930 for classifying S4, ≥ S3, and ≥ S2, respectively) compared with GM + LSM, GM and EM alone, LSM, and biomarkers (all p < .05). CONCLUSIONS: Liver fibrosis can be staged by a transfer learning modal based on the combination of gray scale and elastogram ultrasound images, with excellent performance. KEY POINTS: • Transfer learning consists in applying to a specific deep learning algorithm that pretrained on another relevant problem, expected to reduce the risk of overfitting due to insufficient medical images. • Liver fibrosis can be staged by transfer learning radiomics with excellent performance. • The most accurate prediction model of transfer learning by Inception-V3 network is the combination of gray scale and elastogram ultrasound images.

A Nude Mouse Model of Orthotopic Liver Transplantation of Human Hepatocellular Carcinoma HCCLM3 Cell Xenografts and the Use of Imaging to Evaluate Tumor Progression.

BACKGROUND This study aimed to develop a nude mouse model of orthotopic liver transplantation of HCCLM3 human hepatocellular carcinoma (HCC) cell xenografts and the use of imaging and histology to evaluate tumor development and progression. MATERIAL AND METHODS HCCLM3 cells were injected subcutaneously into 25 healthy male athymic BALB/c (nu/nu) nude mice. The tumors that developed were transplanted into the liver of a new set of nude mice. After four weeks and six weeks, the mice were imaged using ultrasound (US), software-assisted contrast-enhanced ultrasound (CEUS), fluorodeoxyglucose-positron emission tomography (FDG-PET). Histology was performed on the liver and liver tumors, and included immunohistochemistry for vascular endothelial growth factor (VEGF), CD31, CD34, and alpha-smooth muscle actin (alpha-SMA). RESULTS The success rate for orthotopic tumor transplantation in the mouse liver was 90% (18/20). Liver tumors measured 11.8±2.6 mm in diameter and 525.9±250.8 mm3 in volume on the sixth week. CEUS showed rapid wash-in and washout in the liver tumors, and PET showed low tumor cell metabolism. Bone metastases were present in 45% (9/20) of mice in the sixth week. Immunohistochemistry showed positive expression for VEGF, CD31, CD34, and alpha-SMA. CONCLUSIONS The nude mouse orthotopic liver transplantation model of human HCC was shown to be a reliable model that has the potential for future research on the pathogenesis and progression of HCC and studies on drug development.

[Identification of Tritielytrigia alien disomic addition line shannong 87074-519 with yellow rust resistance].

In this paper, Shannong 87074-519, a derivative of wheat-decaploid Elytrigia elongata, was identified by inoculation assessment, cytological analysis, simple sequence repeat (SSR), molecular marker technique,and genomic in situ hybridization (GISH). The results are as follows: the chromosome number of Shannong87074-519 in root tip cells was 2n=44, 22 bivalents were observed in most PMC at MI, and the average chromosome configuration was 2n=44=21.82 II+0.36 I , and the chromosome configuration (2n=43=21 II +1 I) was observed in most PMC of F1 between Shannong87074-519 and C.S. at MI. Therefore, it was an alien disomic addition line with one pair chromosome of Elytrigia elongata. Then the St total genomic DNA was labeled as probe in GISH, the green-yellow hybridization signal was observed in two intact chromosomes, indicating that Shannong87074-519 was added by one pair chromosome of St genome. The SSR-PCR technique was employed in the primer filtration, and the molecular marker BARC165 was singled out from 170 primers, which could amplify the specific molecular marker BARC165(268) of Elytrigia elongata in Shannong87074-519. Subsequently, the specific segment in Elytrigia elongata was cloned and labeled as probe in GISH of root tip cells of Shannong87074-519, the light yellow hybridization signal was observed in both chromatin at interphase and chromosome at mitotic metaphase, thus the BARC165(268) could be applied as a specific molecular marker to detect alien chromatin of Elytrigia elongata in Shannong87074-519. Because of the good agronomic characteristics, high immunity to yellow rust, and dominant new yellow rust resistant gene located at the added chromosome St, assigned as YrSt temporarily, Shannong87074-519 has very important value in wheat breeding and genetics improvement.