Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.

MRI for Hepatitis B-Associated Intrahepatic Cholangiocarcinoma: A Multicenter Comparative Study.

BACKGROUND: The diagnosis of intrahepatic cholangiocarcinoma (iCCA) is challenging in hepatitis B virus (HBV)-infected patients, due to the overlapping clinical manifestations and atypical imaging patterns compared to patients without HBV. PURPOSE: To investigate the preoperative imaging characteristics of iCCA in patients with HBV in comparison to those without HBV. STUDY TYPE: Retrospective. SUBJECTS: 431 patients with histopathologically confirmed iCCA (143 HBV-positive and 288 HBV-negative patients) were retrospectively enrolled from three institutes, and patients were allocated to the training (n = 302) and validation (n = 129) cohorts from different institutes or time period; 100 matching HBV-positive hepatocellular carcinoma (HCC) patients were also enrolled. FIELD STRENGTH/SEQUENCE: 1.5-T and 3-T, including T1- and T2-weighted, diffusion-weighted and dynamic gadopentetate dimeglumine-enhanced imaging. ASSESSMENT: Clinical and MRI features were analyzed and compared between HBV-positive and HBV-negative patients with iCCA, and between HBV-positive patients with iCCA and HCC. STATISTICAL TESTS: Univariate and multivariate logistic regression analyses with odds ratio (OR) to identify independent features for discriminating HBV-associated iCCA. Diagnostic model generation by incorporating independent features, and the performance for discrimination was evaluated by receiver operating characteristics with the area under the curve (AUC) and 95% confidence interval (CI). AUCs were compared by the DeLong's method. A P-value <0.05 was considered statistically significant. RESULTS: Compared to patients without HBV, washout or degressive enhancement pattern (OR = 51.837), well-defined tumor margin (OR = 8.758) and no peritumoral bile duct dilation (OR = 4.651) were independent significant features for discriminating HBV-associated iCCAs. All these features were also the predominant MRI manifestations for HBV-associated HCC. The combined index showed an AUC of 0.798 (95% CI 0.748-0.842) in the training cohort and an AUC of 0.789 (95% CI 0.708-0.856) in the validation cohort for discrimination. The sensitivity, specificity, and accuracy were all >70%, which was superior to each single feature alone in both cohorts. [Correction added after first online publication on 29 June 2023. The Field Strength/Sequence has been updated from 5-T to 1.5-T.] DATA CONCLUSION: Preoperative MRI may help to discriminate HBV-associated iCCA. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY STAGE: 2.

Deep Learning-Based Approach for Identifying and Measuring Focal Liver Lesions on Contrast-Enhanced MRI.

BACKGROUND: The number of focal liver lesions (FLLs) detected by imaging has increased worldwide, highlighting the need to develop a robust, objective system for automatically detecting FLLs. PURPOSE: To assess the performance of the deep learning-based artificial intelligence (AI) software in identifying and measuring lesions on contrast-enhanced magnetic resonance imaging (MRI) images in patients with FLLs. STUDY TYPE: Retrospective. SUBJECTS: 395 patients with 1149 FLLs. FIELD STRENGTH/SEQUENCE: The 1.5 T and 3 T scanners, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: The diagnostic performance of AI, radiologist, and their combination was compared. Using 20 mm as the cut-off value, the lesions were divided into two groups, and then divided into four subgroups: <10, 10-20, 20-40, and ≥40 mm, to evaluate the sensitivity of radiologists and AI in the detection of lesions of different sizes. We compared the pathologic sizes of 122 surgically resected lesions with measurements obtained using AI and those made by radiologists. STATISTICAL TESTS: McNemar test, Bland-Altman analyses, Friedman test, Pearson's chi-squared test, Fisher's exact test, Dice coefficient, and intraclass correlation coefficients. A P-value <0.05 was considered statistically significant. RESULTS: The average Dice coefficient of AI in segmentation of liver lesions was 0.62. The combination of AI and radiologist outperformed the radiologist alone, with a significantly higher detection rate (0.894 vs. 0.825) and sensitivity (0.883 vs. 0.806). The AI showed significantly sensitivity than radiologists in detecting all lesions <20 mm (0.848 vs. 0.788). Both AI and radiologists achieved excellent detection performance for lesions ≥20 mm (0.867 vs. 0.881, P = 0.671). A remarkable agreement existed in the average tumor sizes among the three measurements (P = 0.174). DATA CONCLUSION: AI software based on deep learning exhibited practical value in automatically identifying and measuring liver lesions. TECHNICAL EFFICACY: Stage 2.

Association Between MRI-Based Radiomics Features and Regional Lymph Node Metastasis in Intrahepatic Cholangiocarcinoma and Its Clinical Outcome.

BACKGROUND: Regional lymph node metastasis (LNM) assessment is crucial for predicting intrahepatic cholangiocarcinoma (iCCA) prognosis. However, imaging assessment has limitations for identifying LNM. PURPOSE: To investigate the association between MRI radiomics features, regional LNM status, and prognosis in iCCA. STUDY TYPE: Retrospective. SUBJECTS: Two hundred ninety-six patients (male = 197) with surgically confirmed iCCA. FIELD STRENGTH/SEQUENCE: 1.5 T and 3.0 T. DWI, T2WI, and contrast-enhanced T1WI. ASSESSMENT: Clinical information, radiologic, and MRI-based radiomics features associated with LNM status were collected to establish models. Performance of MRI, PET/CT, and the combined LNM models were compared in training (N = 207) and test (N = 89) datasets. Overall survival (OS) was compared based on LNM status. STATISTICAL TESTS: The independent features were selected by 5-fold cross-validation. The performance of MRI, PET/CT, and the models was evaluated using the area under receiver operating characteristic curve (AUC). Univariable and multivariable Cox regression were used to identify independent variables for OS. Kaplan-Meier curves were compared with the log-rank test between LNM positive and negative groups. P < 0.05 was considered statistically significant. RESULTS: Intrahepatic duct dilatation, enhancement pattern, and CA19-9 were independent clinicoradiologic features. The radiomics model was constructed by the independent radiomics features extracted from T2WI and delay phase T1WI. The combined LNM model showed AUC of 0.888, 0.884, and 0.811 in training, validation, and test cohorts with a positive net benefit. PET/CT exhibited similar sensitivity to the combined LNM model (0.750 vs. 0.733, P > 0.999) while the combined LNM model showed higher specificity (0.703 vs. 0.630, P = 0.039) in the test cohort. High risk of regional LNM was significantly associated with worse OS (median: 24 months) than low risk (median: 30 months, P < 0.0001). DATA CONCLUSIONS: The combined LNM model has the strongest correlation with LNM status for mass-forming iCCA patients. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

A Transformer-Based microvascular invasion classifier enhances prognostic stratification in HCC following radiofrequency ablation.

BACKGROUND & AIMS: We aimed to develop a Transformer-based deep learning (DL) network for prognostic stratification in hepatocellular carcinoma (HCC) patients undergoing RFA. METHODS: A Swin Transformer DL network was trained to establish associations between magnetic resonance imaging (MRI) datasets and the ground truth of microvascular invasion (MVI) based on 696 surgical resection (SR) patients with solitary HCC ≤3 cm, and was validated in an external cohort (n = 180). The multiphase MRI-based DL risk outputs using an optimal threshold of .5 was employed as a MVI classifier for prognosis stratification in the RFA cohort (n = 180). RESULTS: Over 90% of all enrolled patients exhibited hepatitis B virus infection. Liver cirrhosis was significantly more prevalent in the RFA cohort compared to the SR cohort (72.2% vs. 44.1%, p < .001). The MVI risk outputs exhibited good performance (area under the curve values = .938 and .883) for predicting MVI in the training and validation cohort, respectively. The RFA patients at high risk of MVI classified by the MVI classifier demonstrated significantly lower recurrence-free survival (RFS) and overall survival rates at 1, 3 and 5 years compared to those classified as low risk (p < .001). Multivariate cox regression modelling of a-fetoprotein > 20 ng/mL [hazard ratio (HR) = 1.53; 95% confidence interval (95% CI): 1.02-2.33, p = .047], high risk of MVI (HR = 3.76; 95% CI: 2.40-5.88, p < .001) and unfavourable tumour location (HR = 2.15; 95% CI: 1.40-3.29, p = .001) yielded a c-index of .731 (bootstrapped 95% CI: .667-.778) for evaluating RFS after RFA. Among the three risk factors, MVI was the most powerful predictor for intrahepatic distance recurrence. CONCLUSIONS: The proposed MVI classifier can serve as a valuable imaging biomarker for prognostic stratification in early-stage HCC patients undergoing RFA.

Diagnostic algorithm for subcentimeter hepatocellular carcinoma using alpha-fetoprotein and imaging features on gadoxetic acid-enhanced MRI.

OBJECTIVE: To investigate the role of serum alpha-fetoprotein (AFP) in diagnosing subcentimeter hepatocellular carcinoma (HCC) on gadoxetic acid-enhanced MRI (EOB-MRI). METHODS: This study retrospectively enrolled treatment-naïve patients with chronic hepatitis B who had a solitary subcentimeter observation on EOB-MRI from January 2017 to March 2023. Final diagnosis was confirmed by pathology for HCC and pathology or follow-up for benign controls. The AFP cutoff value for HCC was determined using Youden's index. Diagnostic criteria were developed according to significant findings in logistic regression analyses based on AFP and imaging features. The diagnostic performance of possible criteria was compared to the diagnostic hallmarks of HCC (arterial-phase hyperintensity and portal-phase hypointensity). RESULTS: A total of 305 patients (mean age, 51.5 ± 10.7 years; 153 men) were divided into derivation and temporal validation cohorts. Four findings, namely AFP >13.7 ng/mL, arterial-phase hyperintensity, portal-phase hypointensity, and transitional-phase hypointensity, were predictors of HCC. A new criterion (at least three of the four findings) showed higher sensitivity than the diagnostic hallmarks (derivation cohort, 71.6% vs. 52.3%, p < 0.001; validation cohort, 75.0% vs. 47.5%, p = 0.003) without decreasing specificity (derivation cohort, 92.5% vs. 92.5%, p > 0.999; validation cohort, 92.0% vs. 92.0%, p > 0.999). Another criterion (all four findings) achieved a slightly higher specificity than the diagnostic hallmark (derivation cohort, 99.1% vs. 92.5%, p = 0.023; validation cohort, 100.0% vs. 92.0%, p = 0.134). Subgroup analysis for hepatobiliary hypointense observations yielded similar results. CONCLUSION: Including AFP in the diagnostic algorithm may improve the diagnostic performance for subcentimeter HCC. CLINICAL RELEVANCE STATEMENT: Combining imaging features on gadoxetic acid-enhanced MRI with alpha-fetoprotein may enhance the diagnostic performance for subcentimeter HCC in treatment-naïve patients with chronic hepatitis B. KEY POINTS: • The traditional diagnostic hallmark of HCC (arterial-phase hyperintensity and portal-phase hypointensity) shows modest diagnostic performance for subcentimeter HCC on EOB-MRI. • Serum alpha-fetoprotein > 13.7 ng/mL, arterial-phase hyperintensity, portal-phase hypointensity, and transitional-phase hypointensity were independent predictors for subcentimeter HCC. • A criterion of at least three of the four above findings achieved a higher sensitivity without decreasing specificity.

A multi-center diagnostic system for intrahepatic mass-forming cholangiocarcinoma based on preoperative MRI and clinical features.

OBJECTIVES: To establish a non-invasive diagnostic system for intrahepatic mass-forming cholangiocarcinoma (IMCC) via decision tree analysis. METHODS: Totally 1008 patients with 504 pathologically confirmed IMCCs and proportional hepatocellular carcinomas (HCC) and combined hepatocellular cholangiocarcinomas (cHCC-CC) from multi-centers were retrospectively included (internal cohort n = 700, external cohort n = 308). Univariate and multivariate logistic regression analyses were applied to evaluate the independent clinical and MRI predictors for IMCC, and the selected features were used to develop a decision tree-based diagnostic system. Diagnostic efficacy of the established system was calculated by the receiver operating characteristic curve analysis in the internal training-testing and external validation cohorts, and also in small lesions ≤ 3 cm. RESULTS: Multivariate analysis revealed that female, no chronic liver disease or cirrhosis, elevated carbohydrate antigen 19-9 (CA19-9) level, normal alpha-fetoprotein (AFP) level, lobulated tumor shape, progressive or persistent enhancement pattern, no enhancing tumor capsule, targetoid appearance, and liver surface retraction were independent characteristics favoring the diagnosis of IMCC over HCC or cHCC-CC (odds ratio = 3.273-25.00, p < 0.001 to p = 0.021). Among which enhancement pattern had the highest weight of 0.816. The diagnostic system incorporating significant characteristics above showed excellent performance in the internal training (area under the curve (AUC) 0.971), internal testing (AUC 0.956), and external validation (AUC 0.945) cohorts, as well as in small lesions ≤ 3 cm (AUC 0.956). CONCLUSIONS: In consideration of the great generalizability and clinical efficacy in multi-centers, the proposed diagnostic system may serve as a non-invasive, reliable, and easy-to-operate tool in IMCC diagnosis, providing an efficient approach to discriminate IMCC from other HCC-containing primary liver cancers. CLINICAL RELEVANCE STATEMENT: This study established a non-invasive, easy-to-operate, and explainable decision tree-based diagnostic system for intrahepatic mass-forming cholangiocarcinoma, which may provide essential information for clinical decision-making. KEY POINTS: • Distinguishing intrahepatic mass-forming cholangiocarcinoma (IMCC) from other primary liver cancers is important for both treatment planning and outcome prediction. • The MRI-based diagnostic system showed great performance with satisfying generalization ability in the diagnosis and discrimination of IMCC. • The diagnostic system may serve as a non-invasive, easy-to-operate, and explainable tool in the diagnosis and risk stratification for IMCC.

Comparison of machine learning-based CT fractional flow reserve with cardiac MR perfusion mapping for ischemia diagnosis in stable coronary artery disease.

OBJECTIVES: To compare the diagnostic performance of machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and cardiac magnetic resonance (MR) perfusion mapping for functional assessment of coronary stenosis. METHODS: Between October 2020 and March 2022, consecutive participants with stable coronary artery disease (CAD) were prospectively enrolled and underwent coronary CTA, cardiac MR, and invasive fractional flow reserve (FFR) within 2 weeks. Cardiac MR perfusion analysis was quantified by stress myocardial blood flow (MBF) and myocardial perfusion reserve (MPR). Hemodynamically significant stenosis was defined as FFR ≤ 0.8 or > 90% stenosis on invasive coronary angiography (ICA). The diagnostic performance of CT-FFR, MBF, and MPR was compared, using invasive FFR as a reference. RESULTS: The study protocol was completed in 110 participants (mean age, 62 years ± 8; 73 men), and hemodynamically significant stenosis was detected in 36 (33%). Among the quantitative perfusion indices, MPR had the largest area under receiver operating characteristic curve (AUC) (0.90) for identifying hemodynamically significant stenosis, which is in comparison with ML-based CT-FFR on the vessel level (AUC 0.89, p = 0.71), with comparable sensitivity (89% vs 79%, p = 0.20), specificity (87% vs 84%, p = 0.48), and accuracy (88% vs 83%, p = 0.24). However, MPR outperformed ML-based CT-FFR on the patient level (AUC 0.96 vs 0.86, p = 0.03), with improved specificity (95% vs 82%, p = 0.01) and accuracy (95% vs 81%, p < 0.01). CONCLUSION: ML-based CT-FFR and quantitative cardiac MR showed comparable diagnostic performance in detecting vessel-specific hemodynamically significant stenosis, whereas quantitative perfusion mapping had a favorable performance in per-patient analysis. CLINICAL RELEVANCE STATEMENT: ML-based CT-FFR and MPR derived from cardiac MR performed well in diagnosing vessel-specific hemodynamically significant stenosis, both of which showed no statistical discrepancy with each other. KEY POINTS: • Both machine learning (ML)-based computed tomography-derived fractional flow reserve (CT-FFR) and quantitative perfusion cardiac MR performed well in the detection of hemodynamically significant stenosis. • Compared with stress myocardial blood flow (MBF) from quantitative perfusion cardiac MR, myocardial perfusion reserve (MPR) provided higher diagnostic performance for detecting hemodynamically significant coronary artery stenosis. • ML-based CT-FFR and MPR from quantitative cardiac MR perfusion yielded similar diagnostic performance in assessing vessel-specific hemodynamically significant stenosis, whereas MPR had a favorable performance in per-patient analysis.

Time-of-Flight Intracranial MRA at 3 T versus 5 T versus 7 T: Visualization of Distal Small Cerebral Arteries.

Background Three-dimensional (3D) time-of-flight (TOF) MR angiography (MRA) at 7 T has been reported to have high image quality for visualizing small perforating vessels. However, B1 inhomogeneity and more physiologic considerations limit its applications. Angiography at 5 T may provide another choice for intracranial vascular imaging. Purpose To evaluate the image quality and cerebrovascular visualization of 5-T 3D TOF MRA for visualizing intracranial small branch arteries. Materials and Methods Participants (healthy volunteers or participants with a history of ischemic stroke undergoing intracranial CT angiography or MRA for identifying steno-occlusive disease) were prospectively included from September 2021 to November 2021. Each participant underwent 3-T, 5-T, and 7-T 3D TOF MRA with use of customized MR protocols within 48 hours. Radiologist scoring from 0 (invisible) to 3 (excellent) and quantitative assessment were obtained to evaluate the image quality. The Friedman test was used for comparison of characteristics derived from 3 T, 5 T, and 7 T. Results A total of 12 participants (mean age ± SD, 38 years ± 9; nine men) were included. Visualizations of the distal arteries and small vessels at 5-T TOF MRA were significantly higher than those at 3 T (median score: 3.0 vs 2.0, all P < .001 for distal segments and lenticulostriate artery; median score: 2.0 vs 0, P < .001 for pontine artery). The total length of small vessel branches detected at 5 T was larger than that at 3 T (5.1 m ± 0.7 vs 1.9 m ± 0.4; P < .001). However, there was no evidence of a significant difference compared with 7 T in either the depiction of distal segments and small vessel branches (average median score, 2.5; all P > .05) or the quantitative measurements (total length, 5.6 m ± 0.5; P = .41). Conclusion Three-dimensional time-of-flight MR angiography at 5 T presented the capability to provide superior visualization of distal large arteries and small vessel branches (in terms of subjective and quantitative assessment) to 3 T and had image quality similar to 7 T. © RSNA, 2022 Online supplemental material is available for this article. An earlier incorrect version appeared online. This article was corrected on September 14, 2022.

Deciphering intratumoral heterogeneity of hepatocellular carcinoma with microvascular invasion with radiogenomic analysis.

BACKGROUND AND AIMS: The recurrence and metastasis of hepatocellular carcinoma (HCC) are mainly caused by microvascular invasion (MVI). Our study aimed to uncover the cellular atlas of MVI+ HCC and investigate the underlying immune infiltration patterns with radiomics features. METHODS: Three MVI positive HCC and three MVI negative HCC samples were collected for single-cell RNA-seq analysis. 26 MVI positive HCC and 30 MVI negative HCC tissues were underwent bulk RNA-seq analysis. For radiomics analysis, radiomics features score (Radscore) were built using preoperative contrast MRI for MVI prediction and overall survival prediction. We deciphered the metabolism profiles of MVI+ HCC using scMetabolism and scFEA. The correlation of Radscore with the level of APOE+ macrophages and iCAFs was identified. Whole Exome Sequencing (WES) was applied to distinguish intrahepatic metastasis (IM) and multicentric occurrence (MO). Transcriptome profiles were compared between IM and MO. RESULTS: Elevated levels of APOE+ macrophages and iCAFs were detected in MVI+ HCC. There was a strong correlation between the infiltration of APOE+ macrophages and iCAFs, as confirmed by immunofluorescent staining. MVI positive tumors exhibited increased lipid metabolism, which was attributed to the increased presence of APOE+ macrophages. APOE+ macrophages and iCAFs were also found in high levels in IM, as opposed to MO. The difference of infiltration level and Radscore between two nodules in IM was relatively small. Furthermore, we developed Radscore for predicting MVI and HCC prognostication that were also able to predict the level of infiltration of APOE+ macrophages and iCAFs. CONCLUSION: This study demonstrated the interactions of cell subpopulations and distinct metabolism profiles in MVI+ HCC. Besides, MVI prediction Radscore and MVI prognostic Radscore were highly correlated with the infiltration of APOE+ macrophages and iCAFs, which helped to understand the biological significance of radiomics and optimize treatment strategy for MVI+ HCC.

Evolocumab attenuate pericoronary adipose tissue density via reduction of lipoprotein(a) in type 2 diabetes mellitus: a serial follow-up CCTA study.

BACKGROUND: Pericoronary adipose tissue (PCAT) density is a biomarker of vessel inflammation, which is supposed to be increased in patients with type 2 diabetes mellitus (T2DM). However, whether the coronary inflammation revealed by this novel index could be alleviated after evolocumab treatment in T2DM remains unknown. METHODS: From January 2020 to December 2022, consecutive T2DM patients with low-density lipoprotein cholesterol ≥ 70 mg/dL on maximally tolerated statin and taking evolocumab were prospectively included. In addition, patients with T2DM who were taking statin alone were recruited as control group. The eligible patients underwent baseline and follow-up coronary CT angiography with an interval of 48-week. To render patients with evolocumab as comparable to those controls, a propensity-score matching design was used to select the matched pairs with a 1:1 ratio. Obstructive lesion was defined as the extent of coronary artery stenosis ≥ 50%; the numbers inside the brackets were interquartile ranges. RESULTS: A total of 170 T2DM patients with stable chest pain were included [(mean age 64 ± 10.6 [range 40-85] years; 131 men). Among those patients, 85 were in evolocumab group and 85 were in control group. During follow-up, low-density lipoprotein cholesterol (LDL-C) level (2.02 [1.26, 2.78] vs. 3.34 [2.53, 4.14], p < 0.001), and lipoprotein(a) (12.1 [5.6, 21.8] vs. 18.9 [13.2, 27.2], p = 0.002) were reduced after evolocumab treatment. The prevalence of obstructive lesions and high-risk plaque features were significantly decreased (p < 0.05 for all). Furthermore, the calcified plaque volume were significantly increased (188.3 [115.7, 361.0] vs. 129.3 [59.5, 238.3], p = 0.015), while the noncalcified plaque volume and necrotic volume were diminished (107.5 [40.6, 180.6] vs. 125.0 [65.3, 269.7], p = 0.038; 0 [0, 4.7] vs. 0 [0, 13.4], p < 0.001, respectively). In addition, PCAT density of right coronary artery was significantly attenuated in evolocumab group (- 85.0 [- 89.0, - 82.0] vs. - 79.0 [- 83.5, - 74.0], p < 0.001). The change in the calcified plaque volume inversely correlated with achieved LDL-C level (r = - 0.31, p < 0.001) and lipoprotein(a) level (r = - 0.33, p < 0.001). Both the changes of noncalcified plaque volume and necrotic volume were positively correlated with achieved LDL-C level and Lp(a) (p < 0.001 for all). However, the change of PCATRCA density only positively correlated with achieved lipoprotein(a) level (r = 0.51, p < 0.001). Causal mediation analysis revealed Lp(a) level mediated 69.8% (p < 0.001) for the relationship between evolocumab and changes of PCATRCA. CONCLUSIONS: In patients with T2DM, evolocumab is an effective therapy to decrease noncalcified plaque volume necrotic volume, and increase calcified plaque volume. Furthermore, evolocumab could attenuate PCAT density, at least in part, via the reduction of lipoprotein(a).

Evaluate the Microvascular Invasion of Hepatocellular Carcinoma (≤5 cm) and Recurrence Free Survival with Gadoxetate Disodium-Enhanced MRI-Based Habitat Imaging.

BACKGROUND: Tumors are heterogenous and consist of subregions, also known as tumoral habitats, each exhibiting varied biological characteristics. Each habitat corresponds to a cluster of tissue sharing similar structural, metabolic, or functional characteristics. The habitat imaging technique facilitates both the visualization and quantification of these tumoral habitats. PURPOSE: To evaluate the microvascular invasion (MVI) in hepatocellular carcinoma (HCC) (≤5 cm) and assess the recurrence-free survival (RFS) using gadoxetate disodium-enhanced MRI-based habitat imaging. STUDY TYPE: Retrospective. SUBJECTS: 180 patients (52.9 years ± 11.7, 156 men) with HCC. FIELD STRENGTH/SEQUENCE: 1.5T/contrast-enhanced T1-weighted gradient-echo sequence. ASSESSMENT: The enhancement ratio of signal intensity at the arterial phase (AER) and hepatobiliary phase (HBPER) were calculated. The HCC lesions and their peritumoral tissues of 3, 5, and 7 mm were encoded into four habitats. The volume fraction of each habitat was then quantified. The diagnostic performance was assessed using the receiver operating characteristic analysis with 5-fold cross-validation. The RFS was evaluated with Kaplan-Meier curves. RESULTS: Habitat 2 (with median to high AER and low HBPER) within the peritumoral tissue of 3 mm (f2 -P3 ) and tumor diameter could serve as independent risk factors for MVI and showed the statistical significance (odds ratio (OR) of f2 -P3 = 1.170, 95% CI = 1.099-1.246; OR of tumor diameter: 6.112, 95% CI = 2.162-17.280). A nomogram was developed by incorporating f2 -P3 and tumor diameter, demonstrating high diagnostic accuracy. The area under the curve from 5-fold cross-validation ranged from 0.880 to 1.000. Additionally, the nomogram model demonstrated high efficacy in risk stratification for RFS. CONCLUSION: Habitat imaging of HCC and its peritumoral microenvironment has the potential for noninvasive and preoperative identification of MVI and prognostic assessment. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

Apparent Diffusion Coefficient MRI Shows Association With Early Progression of Unresectable Intrahepatic Cholangiocarcinoma With Combined Targeted-Immunotherapy.

BACKGROUND: Most intrahepatic cholangiocarcinomas (ICCs) are diagnosed at advanced stage with an extremely poor prognosis. For these patients, combining targeted therapies and immunotherapy may have a promising therapeutic effect, and current Response Evaluation Criteria in Solid Tumors (RECIST) criteria have limited applicability. PURPOSE: To investigate the associations between pretreatment MRI features and the efficacy of combined targeted-immunotherapy by estimating the risk of early progression (EP) in unresectable ICC, with special emphasis on diffusion-weighted imaging. STUDY TYPE: Retrospective. SUBJECTS: A total of 43 unresectable ICC patients (24 with EP [disease progression ≤12 months after treatment] and 19 with nonearly progression [NEP, disease progression >12 months]), who received first-line systemic therapy with lenvatinib plus PD1 antibody combination. FIELD STRENGTH/SEQUENCE: The 0-T scanner, including T1- and T2-weighted imaging, diffusion-weighted imaging, and dynamic gadopentetate dimeglumine-enhanced imaging. ASSESSMENT: Clinical characteristics and MR imaging features including apparent diffusion coefficient (ADC), as well as survival analysis of EP were evaluated. STATISTICAL TESTS: Features between EP and NEP groups were compared by univariate analyses and multivariate logistic regression analysis. Diagnostic performance was analyzed by receiver operating characteristic curve. Univariate and multivariate Cox regression models were applied for survival analysis of EP. The progression-free survival (PFS) rates were estimated using the Kaplan-Meier analysis and compared by the log-rank test. The significance threshold was set at P < 0.05. RESULTS: Tumor number, tumor margin, arterial peritumoral enhancement, lymphatic metastasis, and apparent diffusion coefficient (ADC) value were significantly different between EP and NEP groups. At multivariate logistic regression analysis, ADC was the only independent variable associated with EP (odds ratio = 0.012), with an area under the curve of 0.774 (optimal cutoff value was 1.028 × 10-3  mm2 /sec). Multivariate Cox regression model proved that ADC value (hazard ratio = 0.140) and ill-defined margin (hazard ratio = 2.784) were independent risk factors. ICCs with low ADC values showed shorter PFS than those with high values (χ2  = 9.368). DATA CONCLUSION: Pretreatment MRI features were associated with EP for unresectable ICC treated with combined targeted-immunotherapy, and decreased ADC value was an independent variable. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 4.

Characterization of Microvascular Invasion in Hepatocellular Carcinoma Using Computational Modeling of Interstitial Fluid Pressure and Velocity.

BACKGROUND: Most solid tumors show increased interstitial fluid pressure (IFP), and this increased IFP is an obstacle to treatment. A noninvasive model for measuring IFP in hepatocellular carcinoma (HCC) is an unresolved issue. PURPOSE: To develop a noninvasive model to measure IFP and interstitial fluid velocity (IFV) in HCC and to characterize the microvascular invasion (MVI) status by using this model. STUDY TYPE: Retrospective. POPULATION: A total of 97 HCC patients (mean age 57.6 ± 10.9 years, 77.3% males), 53 of them with MVI and 44 of them without MVI. FIELD STRENGTH/SEQUENCE: A 3-T, three-dimensional spoiled gradient-recalled echo. ASSESSMENT: MVI was defined as microscopic vascular invasion of small vessels within the peritumoral liver tissue. The volumes of interest (VOIs) were manually delineated and enclosed the tumor lesion and healthy liver parenchyma, respectively. The extended Tofts model (ETM) was used to estimate permeability parameters from all the VOIs. Subsequently, the continuity partial differential equation (PDE) was implemented and IFP and IFV were acquired. STATISTICAL TESTS: Wilcoxon signed-ranks tests, histogram analysis, Mann-Whitney U test, Fisher's exact test, least absolute shrinkage and selection operator (LASSO) logistic regression, receiver operating characteristic (ROC) curve analysis with the area under the curve (AUC), Youden index, DeLong test, and Benjamini-Hochberg correction. A P value <0.05 was considered statistically significant. RESULTS: The HCC lesions exhibited elevated IFP and reduced IFV. There were no significant differences in any measured demographic and clinical features between the MVI-positive and MVI-negative groups, except for tumor size. Nine IFP histogram analysis-derived parameters and seven IFV histogram analysis-derived parameters could be used to characterize the MVI status. LASSO regression selected five features: IFP maximum, IFP 10th percentile, IFP 90th percentile, IFV SD, and IFV 10th percentile. The combination of these features showed the highest AUC (0.781) and specificity (77.3%). DATA CONCLUSION: A noninvasive IFP and IFV measurement model for HCC was developed. Specific IFP- and IFV-derived parameters exhibited significant association with the MVI status. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 2.

Assessment of an MR Elastography-Based Nomogram as a Potential Imaging Biomarker for Predicting Microvascular Invasion of Hepatocellular Carcinoma.

BACKGROUND: Microvascular invasion (MVI) is a well-established poor prognostic factor for hepatocellular carcinoma (HCC). Preoperative prediction of MVI is important for both therapeutic and prognostic purposes, but noninvasive methods are lacking. PURPOSE: To develop an MR elastography (MRE)-based nomogram for the preoperative prediction of MVI in HCC. STUDY TYPE: Prospective. SUBJECTS: A total of 111 patients with surgically resected single HCC (52 MVI-positive and 59 MVI-negative), randomly allocated to training and validation cohorts (7:3 ratio). FIELD STRENGTH/SEQUENCE: 2D-MRE and conventional sequences (T1-weighted in-phase and opposed phase gradient echo, T2-weighted fast spin echo, diffusion-weighted single-shot spin echo echo-planar, and dynamic contrast-enhanced T1-weighted gradient echo) at 3.0 T. ASSESSMENT: MRE-stiffness and conventional qualitative and quantitative MRI features were evaluated and compared between MVI-positive and MVI-negative HCCs. STATISTICAL TESTS: Univariable and multivariable logistic regression analyses were applied to identify potential predictors for MVI, and a nomogram was constructed according to the predictive model. Receiver operating characteristic (ROC) curve analysis was performed to evaluate the diagnostic performance. Harrell's C-index evaluated the discrimination performance of the nomogram, calibration curves analyzed its diagnostic performance and decision curve analysis determined its clinical usefulness. A P value <0.05 was considered statistically significant. RESULTS: Tumor stiffness >6.284 kPa (odds ratio [OR] = 24.38) and the presence of arterial peritumoral enhancement (OR = 6.36) were independent variables associated with MVI. The areas under the ROC curves for tumor stiffness were 0.81 (95% confidence interval [CI]: 0.70, 0.89) and 0.77 (95% CI: 0.60, 0.90) in the training and validation cohorts, respectively. When both predictive variables were integrated, the best nomogram performance was achieved with C-indices of 0.88 (95% CI: 0.78, 0.94) and 0.87 (95% CI: 0.71, 0.96) in the two cohorts, fitting well in calibration curves. The decision curve exhibited optimal net benefit with a wide range of threshold probabilities for the nomogram. DATA CONCLUSION: An MRE-based nomogram may be a potential noninvasive imaging biomarker for predicting MVI of HCC preoperatively. EVIDENCE LEVEL: 2. TECHNICAL EFFICACY: Stage 2.

An MRI-Based Prognostic Stratification System for Medical Decision-Making of Multinodular Hepatocellular Carcinoma Patients Beyond the Milan Criteria.

BACKGROUND: The suitability of hepatectomy among patients with multinodular hepatocellular carcinoma (MHCC) beyond the Milan criteria remains controversial. There is a need for a reliable risk stratification tool among these patients for the selection of ideal candidates of curative resection. PURPOSE: To determine the clinicoradiological prognostic factors for patients with MHCC beyond the Milan criteria to further develop a stratification system. STUDY TYPE: Retrospective. SUBJECTS: 176 patients with pathologically confirmed MHCC beyond the Milan criteria. FIELD STRENGTH/SEQUENCE: The 1.5 T scanner, including T1-, T2-, diffusion-weighted imaging, in/out-phase imaging, and dynamic contrast-enhanced imaging. ASSESSMENT: Conventional MRI features and preoperative laboratory data including aspartate aminotransferase (AST) and α-fetoprotein (AFP) were collected and analyzed. Two nomograms incorporating clinicoradiological variables were independently constructed to predict recurrence-free survival (RFS) and overall survival (OS) with Cox regression analyses and verified with 5-fold cross validation. Based on the nomograms, two prognostic stratification systems for RFS and OS were further developed. STATISTICAL TESTS: The Cohen's kappa/intraclass correlation coefficient, C-index, calibration curve, Kaplan-Meier curve, log-rank test. A P value <0.05 was considered statistically significant. RESULTS: AST > 40 U/L, increased tumor burden score, radiological liver cirrhosis and nonsmooth tumor margin were independent predictors for poor RFS, while AST > 40 U/L, AFP > 400 ng/mL and radiological liver cirrhosis were independent predictors for poor OS. The two nomograms demonstrated good discrimination performance with C-index of 0.653 (95% confidence interval [CI], 0.602-0.794) and 0.685 (95% CI, 0.623-0.747) for RFS and OS, respectively. The 5-fold cross validation further validated the discrimination capability of the nomograms. Based on the nomogram models, MHCC patients beyond the Milan criteria were stratified into low-/medium-/high-risk groups with significantly different RFS and OS. DATA CONCLUSION: The proposed MRI-based prognostic stratification system facilitates the refinement and further subclassification of patients with MHCC beyond the Milan criteria. EVIDENCE LEVEL: 4. TECHNICAL EFFICACY: 2.

Preoperative prediction of microvascular invasion in hepatocellular carcinoma using diffusion-weighted imaging-based habitat imaging.

OBJECTIVES: Habitat imaging allows for the quantification and visualization of various subregions within the tumor. We aim to develop an approach using diffusion-weighted imaging (DWI)-based habitat imaging for preoperatively predicting the microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS: Sixty-five patients were prospectively included and underwent multi-b DWI examinations. Based on the true diffusion coefficient (Dt), perfusion fraction (f), and mean kurtosis coefficient (MK), which respectively characterize cellular density, perfusion, and heterogeneity, the HCCs were divided into four habitats. The volume fraction of each habitat was quantified. The logistic regression was used to explore the risk factors from habitat fraction and clinical variables. Clinical, habitat, and nomogram models were constructed using the identified risk factors from clinical characteristics, habitat fraction, and their combination, respectively. The diagnostic accuracy was evaluated using the area under the receiver operating characteristic curves (AUCs). RESULTS: MVI-positive HCC exhibited a significantly higher fraction of habitat 4 (f4) and a significantly lower fraction of habitat 2 (f2) (p < 0.001), which were selected as risk factors. Additionally, tumor size and elevated alpha-fetoprotein (AFP) were also included as risk factors for MVI. The nomogram model demonstrated the highest diagnostic performance (AUC = 0.807), followed by the habitat model (AUC = 0.777) and the clinical model (AUC = 0.708). Decision curve analysis indicated that the nomogram model offered more net benefit in identifying MVI compared to the clinical model. CONCLUSIONS: DWI-based habitat imaging shows clinical potential for noninvasively and preoperatively determining the MVI of HCC with high accuracy. CLINICAL RELEVANCE STATEMENT: The proposed strategy, diffusion-weighted imaging-based habitat imaging, can be applied for preoperatively and noninvasively identifying microvascular invasion in hepatocellular carcinoma, which offers potential benefits in terms of prognostic prediction and clinical management. KEY POINTS: • This study proposed a strategy of DWI-based habitat imaging for hepatocellular carcinoma. • The habitat imaging-derived metrics can serve as diagnostic markers for identifying the microvascular invasion. • Integrating the habitat-based metric and clinical variable, a predictive nomogram was constructed and displayed high accuracy for predicting microvascular invasion.

An improved diagnostic algorithm for subcentimeter hepatocellular carcinoma on gadoxetic acid-enhanced MRI.

OBJECTIVES: Accurate diagnosis of subcentimeter hepatocellular carcinoma (HCC) is a challenge also with gadoxetic acid-enhanced MRI (EOB-MRI). This study aimed to assess the diagnostic accuracy of the Liver Imaging Reporting and Data System (LI-RADS) for subcentimeter HCC and to determine whether new diagnostic criteria (washout either on portal venous phase (PVP) or transitional phase (TP)) would improve the diagnostic performance. METHODS: We evaluated 240 subcentimeter observations in 225 consecutive treatment-naïve patients at risk of HCC. Final diagnoses were 132 HCCs (all by pathology) and 108 non-HCC (41 by pathology and 67 by follow-up). Two radiologists assessed MR imaging features and assigned LI-RADS categories. A variety of diagnostic criteria were developed by combining significant MRI features based on washout on PVP or TP. Diagnostic performance was compared. RESULTS: Non-rim arterial phase hyperenhancement (non-rim APHE), washout on PVP or TP, and hepatobiliary-phase hypointensity were significant predictors for subcentimeter HCC diagnosis according to multivariable analysis. One criterion (non-rim APHE and washout on PVP or TP) yielded higher sensitivity (68.2% vs. 56.8%, p = 0.011) with comparable specificity (91.7% vs. 92.6%, p > 0.999) compared to the LR-4 category. This criterion had improved sensitivity (68.2% vs. 49.2%, p < 0.001) and slightly decreased specificity (91.7% vs. 94.4%, p = 0.250) compared to non-rim APHE with washout on PVP. CONCLUSIONS: LI-RADS exhibits modest diagnostic performance for subcentimeter HCC. Our new criterion (non-rim APHE and non-peripheral washout on PVP or TP) may increase the diagnostic sensitivity without compromised specificity compared to the LR-4 category. KEY POINTS: • The LR-4 category shows modest diagnostic performance for the diagnosis of subcentimeter HCC on EOB-MRI with a sensitivity and specificity of 56.8% and 92.6%, respectively. • Non-rim APHE, non-peripheral washout on PVP or TP, and HBP hypointensity were independent predictors for the diagnosis of subcentimeter HCC. • The combination of non-rim APHE and non-peripheral washout on PVP or TP improves the sensitivity from 56.8 to 68.2% (p = 0.011) with comparable specificity (91.7 vs. 92.6%, p > 0.999).

Combined hepatocellular carcinoma-cholangiocarcinoma with a predominant HCC component: better survival and MRI-based prediction.

OBJECTIVES: To determine the optimal cutoff value of HCC% for predicting the outcome of patients with combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA) and to investigate how preoperative MR features based on the Liver Imaging Reporting and Data System (LI-RADS ver. 2018) are related to the HCC% in cHCC-CCA. METHODS: The study enrolled 107 patients pathologically confirmed to have single cHCC-CCA according to the 2019 WHO classification. A receiver operating characteristic (ROC) curve was used to find the optimal cutoff value of HCC% based on overall survival (OS). The preoperative MR imaging features and clinicopathological findings were retrospectively evaluated and compared between the high HCC% and low HCC% groups. RESULTS: In total, 107 patients (mean age, males vs. females: 56.6 ± 10.7 years vs. 54.2 ± 12.8 years) were evaluated. Analysis of the relationship between HCC% and OS by ROC curve suggested that the optimal cutoff value was 65%, by which 51 (47.7%) patients were assigned to the high HCC% group. LI-RADS categorization (OR = 3.657, p = 0.006 vs. OR = 4.075, p = 0.004) and serum carcinoembryonic antigen (CEA) >5 ng/mL (OR = 0.348, p = 0.089 vs. OR = 0.298, p = 0.040) were significant predictors for HCC% in cHCC-CCA in both univariate and multivariate analysis. CONCLUSIONS: cHCC-CCA patients with HCC components higher than 65% tend to exhibit better overall survival, and MRI-based LI-RADS categorization and serum CEA level are valuable for identifying HCC% in cHCC-CCA preoperatively. KEY POINTS: • cHCC-CCA patients with HCC components higher than 65% tend to exhibit better overall survival. • MRI-based LI-RADS categorization and serum CEA level were significant predictors for HCC% in cHCC-CCA in both univariate and multivariate analyses and valuable for identifying HCC% in cHCC-CCA preoperatively.

Prognostic factors for long-term outcome in bifocal hepatocellular carcinoma after resection.

OBJECTIVES: This study aimed to evaluate whether the radiological similarity and clinicopathological factors determine the prognosis in bifocal hepatocellular carcinoma (bHCC) stratified by the Milan criteria. METHODS: Consecutive patients with pathologically confirmed bHCC examined between January 2016 and December 2018 were retrospectively enrolled and grouped based on the Milan criteria. Two radiologists independently evaluated whether the imaging features of both tumors were consistent or not, which was defined as the radiological similarity. The clinicopathological data were also collected. The multivariable Cox regression was applied to separately identify the independent factors for recurrence-free survival (RFS) and overall survival (OS) in bHCC within and beyond the Milan criteria. RESULTS: A total of 193 patients were evaluated and divided into the within the Milan criteria group (n = 72) and the beyond the Milan criteria group (n = 121). bHCC within the Milan criteria showed a significantly better prognosis than those beyond the criteria. In the within the Milan criteria group, HBV-DNA load >104 IU/mL, microvascular invasion (MVI), and different enhancement patterns were independently associated with poor RFS. MVI was an independent prognostic factor for poor OS. In the beyond the Milan criteria group, HBV infection, MVI, increased ratio of the larger to the smaller tumor diameter (RLSD) value, and low comprehensive similarity were associated with shorter RFS, whereas MVI and increased RLSD value were independent predictors for poor OS. CONCLUSIONS: Our study revealed that in addition to MVI- and HBV-related factors, similarity in imaging features between lesions of bHCC is associated with the long-term prognosis. KEY POINTS: • The prognosis of bifocal HCC patients within the Milan criteria is significantly better than those beyond the criteria. • The similarity in imaging features between lesions of bHCC was an independent prognostic factor. • The more similar the bifocal lesions are in imaging features, the better the prognosis is.