Integration of Artificial Intelligence Decision Aids to Reduce Workload and Enhance Efficiency in Thyroid Nodule Management.

Importance: To optimize the integration of artificial intelligence (AI) decision aids and reduce workload in thyroid nodule management, it is critical to incorporate personalized AI into the decision-making processes of radiologists with varying levels of expertise. Objective: To develop an optimized integration of AI decision aids for reducing radiologists' workload while maintaining diagnostic performance compared with traditional AI-assisted strategy. Design, Setting, and Participants: In this diagnostic study, a retrospective set of 1754 ultrasonographic images of 1048 patients with 1754 thyroid nodules from July 1, 2018, to July 31, 2019, was used to build an optimized strategy based on how 16 junior and senior radiologists incorporated AI-assisted diagnosis results with different image features. In the prospective set of this diagnostic study, 300 ultrasonographic images of 268 patients with 300 thyroid nodules from May 1 to December 31, 2021, were used to compare the optimized strategy with the traditional all-AI strategy in terms of diagnostic performance and workload reduction. Data analyses were completed in September 2022. Main Outcomes and Measures: The retrospective set of images was used to develop an optimized integration of AI decision aids for junior and senior radiologists based on the selection of AI-assisted significant or nonsignificant features. In the prospective set of images, the diagnostic performance, time-based cost, and assisted diagnosis were compared between the optimized strategy and the traditional all-AI strategy. Results: The retrospective set included 1754 ultrasonographic images from 1048 patients (mean [SD] age, 42.1 [13.2] years; 749 women [71.5%]) with 1754 thyroid nodules (mean [SD] size, 16.4 [10.6] mm); 748 nodules (42.6%) were benign, and 1006 (57.4%) were malignant. The prospective set included 300 ultrasonographic images from 268 patients (mean [SD] age, 41.7 [14.1] years; 194 women [72.4%]) with 300 thyroid nodules (mean [SD] size, 17.2 [6.8] mm); 125 nodules (41.7%) were benign, and 175 (58.3%) were malignant. For junior radiologists, the ultrasonographic features that were not improved by AI assistance included cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, and nodules smaller than 5 mm, whereas for senior radiologists the features that were not improved by AI assistance were cystic or almost completely cystic nodules, anechoic nodules, spongiform nodules, very hypoechoic nodules, nodules taller than wide, lobulated or irregular nodules, and extrathyroidal extension. Compared with the traditional all-AI strategy, the optimized strategy was associated with increased mean task completion times for junior radiologists (reader 11, from 15.2 seconds [95% CI, 13.2-17.2 seconds] to 19.4 seconds [95% CI, 15.6-23.3 seconds]; reader 12, from 12.7 seconds [95% CI, 11.4-13.9 seconds] to 15.6 seconds [95% CI, 13.6-17.7 seconds]), but shorter times for senior radiologists (reader 14, from 19.4 seconds [95% CI, 18.1-20.7 seconds] to 16.8 seconds [95% CI, 15.3-18.3 seconds]; reader 16, from 12.5 seconds [95% CI, 12.1-12.9 seconds] to 10.0 seconds [95% CI, 9.5-10.5 seconds]). There was no significant difference in sensitivity (range, 91%-100%) or specificity (range, 94%-98%) between the 2 strategies for readers 11 to 16. Conclusions and Relevance: This diagnostic study suggests that an optimized AI strategy in thyroid nodule management may reduce diagnostic time-based costs without sacrificing diagnostic accuracy for senior radiologists, while the traditional all-AI strategy may still be more beneficial for junior radiologists.

Value of Multimodal Data From Clinical and Sonographic Parameters in Predicting Recurrence of Hepatocellular Carcinoma After Curative Treatment.

OBJECTIVE: The objective of the work described here was to assess the value of the combination of pre-operative multimodal data-including clinical data, contrast-enhanced ultrasound (CEUS) information and liver stiffness measurement (LSM) based on 2-D shear wave elastography (SWE)-in predicting early (within 1 y) and late (after 1 y) recurrence of hepatocellular carcinoma (HCC) after curative treatment. METHODS: We retrospectively included 101 patients with HCC who met the Milan criteria and received curative treatment. The multimodel data from clinical parameters, LSM by 2-D SWE and CEUS enhancement patterns were collected. The association between different variables in HCC recurrence was accessed using a Cox proportional hazard model. On the basis of the independent factors of early recurrence, models with different source variables were established (Clinical Model, CEUS-Clinical Model, SWE-Clinical Model, CEUS-SWE-Clinical Model). The goodness-of-fit of models was evaluated and the performance trends of different models were calculated by time-dependent area under the curve (AUC). RESULTS: Two-dimensional SWE, CEUS enhancement patterns and clinical parameters (spleen length, multiple tumors, α-fetoprotein, albumin and prothrombin time) were independently associated with early recurrence (all p values <0.05). Multiple tumors and a decrease in albumin independently contributed to the late recurrence. The model fit of CEUS-SWE-Clinical Model was superior to other models in predicting early recurrence (all p values <0.05). The AUCs of the CEUS-Clinical Model were higher from 2 mo to 7 mo, while the SWE-Clinical Model had higher AUCs from 9 mo to 12 mo. CONCLUSION: CEUS enhancement patterns and 2-D SWE were independent predictors of HCC early recurrence as the two factors contributed to the predictive performance at different times. The multimodal model, which included diverse data in predicting early HCC recurrence, had the best goodness-of-fit.

Differentiation between combined hepatocellular carcinoma and hepatocellular carcinoma: comparison of diagnostic performance between ultrasomics-based model and CEUS LI-RADS v2017.

BACKGROUND: The imaging findings of combined hepatocellular cholangiocarcinoma (CHC) may be similar to those of hepatocellular carcinoma (HCC). CEUS LI-RADS may not perform well in distinguishing CHC from HCC. Studies have shown that radiomics has an excellent imaging analysis ability. This study aimed to establish and confirm an ultrasomics model for differentiating CHC from HCC. METHODS: Between 2004 and 2016, we retrospectively identified 53 eligible CHC patients and randomly included 106 eligible HCC patients with a ratio of HCC:CHC = 2:1, all of whom were categorized according to Contrast-Enhanced (CE) ultrasonography (US) Liver Imaging Reporting and Data System (LI-RADS) version 2017. The model based on ultrasomics features of CE US was developed in 74 HCC and 37 CHC and confirmed in 32 HCC and 16 CHC. The diagnostic performance of the LI-RADS or ultrasomics model was assessed by the area under the curve (AUC), accuracy, sensitivity and specificity. RESULTS: In the entire and validation cohorts, 67.0% and 81.3% of HCC cases were correctly assigned to LR-5 or LR-TIV contiguous with LR-5, and 73.6% and 87.5% of CHC cases were assigned to LR-M correctly. Up to 33.0% of HCC and 26.4% of CHC were misclassified by CE US LI-RADS. A total of 90.6% of HCC as well as 87.5% of CHC correctly diagnosed by the ultrasomics model in the validation cohort. The AUC, accuracy, sensitivity of the ultrasomics model were higher though without significant difference than those of CE US LI-RADS in the validation cohort. CONCLUSION: The proposed ultrasomics model showed higher ability though the difference was not significantly different for differentiating CHC from HCC, which may be helpful in clinical diagnosis.

Can monodisperse microbubble-based three-dimensional contrast-enhanced ultrasound reduce quantitative heterogeneity? An in vitro study.

BACKGROUND: Heterogeneity within the tumor may cause large heterogeneity in quantitative perfusion parameters. Three-dimensional contrast-enhanced ultrasound (3D-CEUS) can show the spatial relationship of vascular structure after post-acquisition reconstruction and monodisperse bubbles can resonate the ultrasound pulse, resulting in the increase in sensitivity of CEUS imaging. OBJECTIVES: To evaluate whether the combination of 3D-CEUS and monodisperse microbubbles could reduce the heterogeneity of quantitative CEUS. MATERIAL AND METHODS: Three in vitro perfusion models with perfusion volume ratio of 1:2:4 were set up. Both quantitative 2D-CEUS and 3D-CEUS were used to acquire peak intensity (PI) with 2 kinds of ultrasound agents. One was a new kind of monodisperse bubbles produced in this study, named Octafluoropropane-loaded cerasomal microbubbles (OC-MBs), the other was SonoVue®. The coefficient of variation (CV) was calculated to evaluate the cross-sectional variability. Pearson's correlation analysis was used to assess the correlation between weighted PIs (average of PIs of 3 different planes) and perfusion ratios. RESULTS: The average CVs of quantitative 3D-CEUS was slightly lower than that of 2D-CEUS (0.41 ±0.17 compared to 0.55 ±0.26, p = 0.3592). As for quantitative 3D-CEUS, the PI of the OC-MBs has shown better stability than that of SonoVue®, but without a significant difference (average CVs: 0.32 ±0.19 compared to 0.50 ±0.10, p = 0.0711). In the 2D-CEUS condition, the average CVs of OC-MBs group and SonoVue® group were 0.68 ±0.15 and 0.41 ±0.17 (p = 0.2747). As for 3D-CEUS condition, using OC-MBs group and SonoVue®, the r-values of the weighted PI and perfusion ratio were 0.8685 and 0.5643, respectively, while that of 2D-CEUS condition were 0.7760 and 0.3513, respectively. CONCLUSIONS: Our in vitro experiments showed that OC-MBs have the potential in acquiring more stable quantitative CEUS value, as compared to the SonoVue® in 3D-CEUS condition. The combination of 3D-CEUS and OC-MBs can reflect perfusion volume more precisely and may be a potential way to reduce quantitative heterogeneity.

Contrast-Enhanced Ultrasound for Differentiation Between Poorly Differentiated Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma.

PURPOSE: To evaluate the diagnostic performance of LR-5 for diagnosing poorly differentiated hepatocellular carcinoma (p-HCC). To build a contrast-enhanced ultrasound (CEUS) signature for improving the differential diagnostic performance between p-HCC and intrahepatic cholangiocarcinoma (ICC). METHODS: The B-mode ultrasound (BUS) and CEUS features of 60 p-HCCs and 56 ICCs were retrospectively analyzed. The CEUS LI-RADS category was assigned according to CEUS LI-RADS v2017. A diagnostic CEUS signature was built based on the independent significant features. An ultrasound (US) signature combining both BUS and CEUS features was also built. The diagnostic performances of the CEUS signature, US signature, and LR-5 were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: One (1.7%) p-HCC and 26 (46.4%) ICC patients presented cholangiectasis or cholangiolithiasis (P < .001). Fifty-four (90.0%) p-HCCs and 8 (14.3%) ICCs showed clear boundaries in the artery phase (P < .001). The washout times of p-HCCs and ICCs were 81.0 ± 42.5 s and 34.7 ± 8.6 s, respectively (P < .001). The AUC, sensitivity, and specificity of the CEUS signature, US signature, and LR-5 were 0.955, 91.67%, and 90.57% versus 0.976, 96.67%, and 92.45% versus 0.758, 51.67%, and 100%, respectively. The AUC and sensitivity of CEUS LI-RADS were much lower than those of the CEUS and US signatures (P < .001). CONCLUSION: LR-5 had high specificity but low sensitivity in diagnosing p-HCC. When the washout time and tumor boundary were included in the CEUS signature, the sensitivity and AUC were remarkably increased in the differentiation between p-HCC and ICC.

Contrast-Enhanced Ultrasound-Based Nomogram: A Potential Predictor of Individually Postoperative Early Recurrence for Patients With Combined Hepatocellular-Cholangiocarcinoma.

PURPOSES: To evaluate the postsurgical prognostic implication of contrast-enhanced ultrasound (CEUS) for combined hepatocellular-cholangiocarcinoma (CHC). To build a CEUS-based early recurrence prediction classifier for CHC, in comparison with tumor-node-metastasis (TNM) staging. METHODS: The CEUS features and clinicopathological findings of each case were analyzed, and the Liver Imaging Reporting and Data System categories were assigned. The recurrence-free survival associated factors were evaluated by Cox proportional hazard model. Incorporating the independent factors, nomograms were built to estimate the possibilities of 3-month, 6-month, and 1-year recurrence and whose prognostic value was determined by time-dependent receiver operating characteristics, calibration curves, and hazard layering efficiency validation, comparing with TNM staging system. RESULTS: In the multivariable analysis, the levels of carbohydrate antigen 19-9, prothrombin time and total bilirubin, and tumor shape, the Liver Imaging Reporting and Data System category were independent factors for recurrence-free survival. The LR-M category showed longer recurrence-free survival than did the LR-4/5 category. The 3-month, 6-month, and 1-year area under the curves of the CEUS-clinical nomogram, clinical nomogram, and TNM staging system were 0.518, 0.552, and 0.843 versus 0.354, 0.240, and 0.624 (P = .048, .049, and .471) vs. 0.562, 0.545, and 0.843 (P = .630, .564, and .007), respectively. The calibration curves of the CEUS-clinical model at different prediction time pionts were all close to the ideal line. The CEUS-clinical model effectively stratified patients into groups of high and low risk of recurrence in both training and validation set, while the TNM staging system only works on the training set. CONCLUSIONS: Our CEUS-clinical nomogram is a reliable early recurrence prediction tool for hepatocellular-cholangiocarcinoma and helps postoperative risk stratification.

Ultrasomics for Early Evaluation of the Tumor Response to MicroRNA-122 in a Nude Mouse Hepatocellular Carcinoma Model.

OBJECTIVES: To explore the value of ultrasomics in temporal monitoring of tumor changes in response to gene therapy in hepatocellular carcinoma compared with methods according to the Response Evaluation Criteria in Solid Tumors (RECIST) and modified RECIST (mRECIST). METHODS: Hepatocellular carcinoma-bearing mice were injected intratumorally with microRNA-122 (miR-122) mimics and an miR-122 negative control in the treatment and control groups, respectively. The injections were performed every 3 days for 5 times (on days 0, 3, 6, 9, and 12). Before each injection and at the experiment ending, 2-dimensional ultrasound imaging was performed for tumor size measurement with RECIST and computing a quantitative imaging analysis with ultrasomics. To analyze the tumor perfusion by mRECIST, perfusion parameters were analyzed offline based on dynamic contrast-enhanced ultrasound image videos using SonoLiver software (TomTec, Unterschleissheim, Germany) on day 13. Tumor miR-122 expression was then analyzed by real-time reverse transcription-polymerase chain reaction experiments. RESULTS: Tumors in mice treated with miR-122 mimics demonstrated a mean ± SD 763- ± 60-fold increase in miR-122 levels compared with tumors in the control group. With RECIST, a significant therapeutic response evaluated by tumor size changes was detected after day 9 (days 9, 12, and 13; P < .001). With mRECIST, no parameters showed significant differences (P > .05). Significant different features of the 2-dimensional ultrasound images between the groups were detected by the ultrasomics analysis, and the model could be successfully built. The ultrasomics score values between the groups were statistically significant after day 6 (days 6, 9, 12, and 13; P < .05). CONCLUSIONS: Ultrasomics revealed significant changes after the second injection of miR-122, showing the potential as an important imaging biomarker for gene therapy.

Comparison of Real-Time Two-Dimensional and Three-Dimensional Contrast-Enhanced Ultrasound to Quantify Flow in an In Vitro Model: A Feasibility Study.

BACKGROUND This feasibility study aimed to compare real-time two-dimensional contrast-enhanced ultrasound (2D-CEUS) and three-dimensional contrast-enhanced ultrasound (3D-CEUS) to quantify flow in an in vitro model. MATERIAL AND METHODS Five polyvinyl chloride (PVC) tubes were used for the perfusion models and used SonoVue ultrasound contrast agent with a perfusion volume ratio of 1: 2: 4: 8: 16. The contrast was injected at a constant speed to compare the raw quantitative data of 2D-CEUS and 3D-CEUS at angles of 0°, 45°, and 90°. The coefficient of variation (CV) of the peak intensity (PI) in the model were compared and the correlations between weighted PI and perfusion volume were analyzed. RESULTS In the three angles used, real-time 3D-CEUS resulted in a more comprehensive view of the spatial relationships in the perfusion model. Using real-time 2D-CEUS, the mean CV was 0.92±0.36, and the mean CV in the real-time 3D-CEUS model was significantly less at 0.48±0.32 (p<0.001). Quantitative 3D-CEUS parameters showed a good correlation with those of 2D-CEUS with an r-value of 0.93 (p=0.02). The r-value of weighted PI and the perfusion ratio using 2D-CEUS was 0.66 (p=0.23) compared with values in 3D-CEUS of 0.84 (p=0.08). CONCLUSIONS The combination of real-time 3D-CEUS and quantitative analysis identified the spatial distribution of the changes in angle in the model, which was less influenced by sectional planes, and was more representative of the perfusion volume when compared with 2D-CEUS. Quantitative real-time 3D-CEUS requires in vivo studies to evaluate the potential role in the clinical evaluation of vascular perfusion of malignant tumors.

Thermal Field Distributions of Ablative Experiments Using Cyst-mimicking Phantoms: Comparison of Microwave and Radiofrequency Ablation.

RATIONALE AND OBJECTIVES: The objective of this study was to explore the thermal field distribution of cystic lesions undergoing microwave ablation (MWA) and radiofrequency ablation (RFA) using in vitro phantoms. MATERIALS AND METHODS: Cyst-mimicking lesions filled with sodium chloride (NaCl) solution in acrylamide phantoms were treated with MWA and RFA in vitro. The radiofrequency electrodes or MWA antennas were implanted in the centers of the artificial cystic lesions. We used temperature fields located 5, 15, and 25 mm from the electrode or the antenna to plot the temperature-rise curves. Solid phantoms without cysts were also fabricated as controls. RESULTS: The temperature within cysts increased faster and reached a higher maximum temperature during MWA than during RFA, and this result was independent of the NaCl solution concentration. RFA treatment caused the temperatures within the lesion to increase significantly faster in the cysts containing 0.9% NaCl than in those containing 5.0% NaCl. However, the MWA temperature-rise curves were only weakly affected by the ionic concentration. The median temperature difference values between the 5- and 15-mm points were markedly lower in the 0.9% NaCl cyst-mimicking phantom (P <0.001) than in the solid phantom after either MWA or RFA. CONCLUSIONS: Our data indicate that MWA is a more effective technique for focal cystic lesions than RFA and has higher overall energy utilization. MWA was also less affected by the ionic concentration of the cystic fluid.

Hilar biliary neurofibroma without neurofibromatosis: case report with contrast-enhanced ultrasound findings.

Solitary neurofibroma located in the hilum of the liver is extremely rare, particularly without neurofibromatosis. We herein report a case of hilar biliary neurofibroma without signs of von Recklinghausen's disease. A 36-year-old man was admitted to our department with progressive jaundice. The case was diagnosed as hilar cholangiocarcinoma based on preoperative imaging. The patient consequently received a Roux-en-Y hepaticojejunostomy and was confirmed with neurofibroma pathologically. This is the first reported imaging finding of hilar biliary neurofibroma using contrast-enhanced ultrasound, emphasizing the differential diagnosis of biliary tumors.