Diagnostic performance of ultrasound elastography in differentiating hepatocellular carcinoma and intrahepatic cholangiocarcinoma: a systematic review and meta-analysis.

PURPOSE: To evaluate the diagnostic value of ultrasound elastography (USE) for characterizing hepatocellular carcinoma (HCC) and intrahepatic cholangiocarcinoma (ICC). METHODS: The protocol was pre-registered a priori at ( https://osf.io/namvk/ ). Using PubMed, Web of Science, Embase, and Cochrane Library, we found studies up to April 20, 2024 by searching HCC, ICC, and USE as keywords. Parameters of USE were directly compared between HCC and ICC patients using random-effects bivariate model on STATA 17.0, MedCalc 20.0, and Psychometrica. Trim & fill method and sensitivity analysis were also performed. RESULTS: Eighteen studies were included with 1057 patients, consisting of 863 HCC lesions, 188 ICC lesions, and 6 mixed lesions. The pooled Emean values of HCC and ICC were 28.3 (CI = 19.8 to 36.8) and 44.0 (CI = 20.9 to 67.2). HCC tumors were 34.3% softer than ICC while peritumoral tissue in HCC lesions was 75% stiffer than ICC lesions based on Emean. The strain value index (tumoral-to-peritumoral ratio) in HCC patients was 49.4% less than that of ICC patients. USE demonstrated a pool sensitivity of 87% (CI = 73-95%), specificity of 82% (CI = 65-92%), positive likelihood ratio of 4.8 (CI = 2.2 to 10.3), negative likelihood ratio of 0.16 (CI = 0.07 to 0.37), and diagnostic odds ratio of 31 (CI = 7 to 127) in differentiation of ICC from HCC. CONCLUSION: By evaluating tumoral and pre-tumoral stiffness, along with strain value index, USE may provide a valuable quantitative diagnostic tool for accurately differentiating HCC and ICC.

Qualitative and quantitative differentiation efficiency of dual-tracer PET/CT with 18F-fluorodeoxyglucose and 11C-acetate for primary hepatocellular carcinoma: a systematic review and meta-analysis.

PURPOSE: Primary hepatocellular carcinoma (HCC) represents a substantial global health challenge. Early diagnosis of HCC is crucial for improved patient outcomes. The aim of this study was to assess qualitative and quantitative diagnostic performance of PET/CT using 11C-acetate and [18F]-fluorodeoxyglucose (FDG) in detection of primary HCC and to determine if 11C-acetate added to [18F]-FDG alleviates the low sensitivity rate mentioned in guidelines. METHODS: Protocol was pre-registered at https://osf.io/2vcb9 . We searched PubMed, Web of Science, Embase, and the Cochrane Library for included studies. Quality Assessment of Diagnostic Accuracy Studies 2 was used to assess the risk of bias. Possible sources of statistical heterogeneity were explored. Additionally, mentioned three PET/CT tests were evaluated for their diagnostic performance in differentiating HCC from its differential diagnoses. Grades of Recommendation, Assessment, Development, and Evaluation was used to assess quality of generated evidence. RESULTS: Twenty-four studies were analyzed. Qualitative dual-tracer PET/CT demonstrated 92.0% per-lesion sensitivity, and a significantly higher direct sensitivity difference of 30% to conventional CT, 44.7% to [18F]-FDG, and 12.0% to 11C-acetate. Regarding differentiation rate, [18F]-FDG was superior to 11C-acetate in poorly differentiated lesions while 11C-acetate was superior in well-differentiated lesions. Regarding size, dual tracer combination solved the high missing rate of HCC lesions in 1-2 cm and 2-5 cm groups but could not help in size < 1 cm. CONCLUSION: Dual-tracer PET/CT utilizing 11C-acetate and [18F]-FDG represents a sensitive method for detecting primary HCC. By concurrently quantifying or qualifying the uptake of 11C-acetate and [18F]-FDG, this multimodal approach enables precise localization of intrahepatic lesions.

Full head-to-head comparison of ultrasonography and CT scan in volumetric quantification of pleural effusion: a systematic review and meta-analysis.

Pleural effusion is a very common clinical finding. Quantifying pleural effusion volume and its response to treatment over time has become increasingly important for clinicians, which is currently performed via computed tomography (CT) or drainage. To determine and compare ultrasonography (US), CT, and drainage agreements in pleural effusion volumetry. Protocol pre-registration was performed a priori at ( https://osf.io/rnugd/ ). We searched PubMed, Web of Science, Embase, and Cochrane Library for studies up to January 7, 2024. Risk of bias was assessed using Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2), QUADAS-C, and Consensus-based Standards for the selection of health Measurement Instruments (COSMIN). Volumetric performances of CT, US, and drainage in assessment of pleural effusion volume were evaluated through both aggregated data (AD) and individual participant data (IPD) analyses. Certainty of evidence was evaluated using Grading of Recommendations, Assessment, Development, and Evaluations (GRADE). Six studies were included with 446 pleural effusion lesions. AD results showed a perfect level of agreement with pooled Pearson correlation and intraclass correlation coefficient (ICC) of 0.933 and 0.948 between US and CT. IPD results demonstrated a high level of agreement between US and CT, with Finn's coefficient, ICC, concordance correlation coefficient (CCC), and Pearson correlation coefficient values of 0.856, 0.855, 0.854, and 0.860, respectively. Also, both results showed an overall perfect level of agreement between US and drainage. As for comparing the three combinations, US vs. CT and US vs. drainage were both superior to CT vs. drainage, suggesting the US is a good option for pleural effusion volumetric assessment. Ultrasound provides a highly reliable, to-the-point, cost-effective, and noninvasive method for the assessment of pleural effusion volume and is a great alternative to CT or drainage.

Enhanced staging of extrahepatic hepatocellular carcinoma metastasis through dual-tracer PET/computed tomography: a systematic review and meta-analysis.

The aim of this study was to quantify the diagnostic value of dual-tracer PET/computed tomography (CT) with 11 C-acetate and fluorodeoxyglucose (FDG) in per-lesion and per-patient and its effect on clinical decision-making for choosing the most appropriate management. The study protocol is registered a priori at https://osf.io/rvm75/ . PubMed, Web of Science, Embase , and Cochrane Library were searched for relevant studies until 1 June 2023. Studies regarding the review question were included. The Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) was used to assess bias risk. Per-lesion and per-patient diagnostic performance were calculated for: (1) 11 C-acetate alone; (2) FDG alone; and (3) dual tracer of 11 C-acetate and FDG. A direct comparison of these three combinations was made. The possible sources of statistical heterogeneity were also examined. We also calculated the percentage change in clinical decision-making when dual-tracer PET/CT was added to conventional imaging routinely used for metastatic evaluation (CT/MRI). Grading of Recommendations, Assessment, Development, and Evaluations tool was used to evaluate the certainty of evidence. Eight studies including 521 patients and 672 metastatic lesions were included. Dual-tracer PET/CT had a per-lesion sensitivity of 96.3% [95% confidence interval (CI), 91.8-98.4%] and per-patient sensitivity of 95.5% (95% CI, 89.1-98.2%) which were highly superior to either of tracers alone. Per-patient specificity was 98.5% (84.1-99.9%) which was similar to either of tracers alone. Overall, 9.3% (95% CI, 4.7-13.9%) of the patients had their management beneficially altered by adding dual-tracer PET/CT to their conventional CT/MRI results. Dual-tracer PET/CT substantially outperforms single-tracer methods in detecting extrahepatic hepatocellular carcinoma metastases, evidencing its reliability and significant role in refining clinical management strategies based on robust diagnostic performance.

Enhancing Mechanical Metamodels With a Generative Model-Based Augmented Training Dataset.

Modeling biological soft tissue is complex in part due to material heterogeneity. Microstructural patterns, which play a major role in defining the mechanical behavior of these tissues, are both challenging to characterize and difficult to simulate. Recently, machine learning (ML)-based methods to predict the mechanical behavior of heterogeneous materials have made it possible to more thoroughly explore the massive input parameter space associated with heterogeneous blocks of material. Specifically, we can train ML models to closely approximate computationally expensive heterogeneous material simulations where the ML model is trained on datasets of simulations with relevant spatial heterogeneity. However, when it comes to applying these techniques to tissue, there is a major limitation: the number of useful examples available to characterize the input domain under study is often limited. In this work, we investigate the efficacy of both ML-based generative models and procedural methods as tools for augmenting limited input pattern datasets. We find that a style-based generative adversarial network with an adaptive discriminator augmentation mechanism is able to successfully leverage just 1000 example patterns to create authentic generated patterns. In addition, we find that diverse generated patterns with adequate resemblance to real patterns can be used as inputs to finite element simulations to meaningfully augment the training dataset. To enable this methodological contribution, we have created an open access finite element analysis simulation dataset based on Cahn-Hilliard patterns. We anticipate that future researchers will be able to leverage this dataset and build on the work presented here.