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.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2023.

The 2023 update of the Chinese Society of Clinical Oncology (CSCO) Clinical Guidelines for Gastric Cancer focuses on standardizing cancer diagnosis and treatment in China, reflecting the latest advancements in evidence-based medicine, healthcare resource availability, and precision medicine. These updates address the differences in epidemiological characteristics, clinicopathological features, tumor biology, treatment patterns, and drug selections between Eastern and Western gastric cancer patients. Key revisions include a structured template for imaging diagnosis reports, updated standards for molecular marker testing in pathological diagnosis, and an elevated recommendation for neoadjuvant chemotherapy in stage III gastric cancer. For advanced metastatic gastric cancer, the guidelines introduce new recommendations for immunotherapy, anti-angiogenic therapy and targeted drugs, along with updated management strategies for human epidermal growth factor receptor 2 (HER2)-positive and deficient DNA mismatch repair (dMMR)/microsatellite instability-high (MSI-H) patients. Additionally, the guidelines offer detailed screening recommendations for hereditary gastric cancer and an appendix listing drug treatment regimens for various stages of gastric cancer. The 2023 CSCO Clinical Guidelines for Gastric Cancer updates are based on both Chinese and international clinical research and expert consensus to enhance their applicability and relevance in clinical practice, particularly in the heterogeneous healthcare landscape of China, while maintaining a commitment to scientific rigor, impartiality, and timely revisions.

A novel role of the splenic volume in Crohn's disease: evaluating the efficacy of infliximab.

Background: A number of patients with Crohn's disease (CD) suffer from loss of response to infliximab (IFX) therapy. Splenic volume is reported to be enlarged in patients with CD compared to normal individuals. The association between splenic volume and IFX efficacy in CD remains unclear. Methods: We performed a retrospective study of patients with CD who received regular IFX treatment at Zhongshan Hospital, Fudan University, between August 2015 and December 2021. We collected baseline characteristics and clinical features from medical records in the CD database of Zhongshan Hospital. We accurately measured the splenic volume using semi-auto spleen segmentation software, followed by the analysis of splenic volume and IFX efficacy. Results: We included 49 patients with CD receiving IFX treatment, of whom 41 responded to IFX and 8 failed to respond to IFX. Splenic volume, as well as volume adjusted for body mass index (SV/BMI) and body weight (SV/W), was significantly decreased after IFX treatment in responders but increased in non-responders compared to the volume before the treatment. Accordingly, the levels of leukocyte count, platelet count, C-reactive protein (CRP), and erythrocyte sedimentation rate (ESR) were decreased after IFX treatment in responders. Contrarily, the levels of hemoglobin, albumin, and tumor necrosis factor (TNF)-α were elevated in responders. Moreover, both CRP and TNF-α levels were significantly positively correlated with SV/BMI in all patients. Conclusion: Splenic volume, especially SV/BMI and SV/W, was reduced after IFX treatment in CD patients responsive to IFX. SV/BMI was positively correlated with disease activity. Splenic volume is a promising indicator to evaluate IFX efficacy in CD.

Diagnostic performance of gadoxetic acid-enhanced abbreviated magnetic resonance imaging protocol in small hepatocellular carcinoma (≤2 cm) in high-risk patients.

BACKGROUND: Biannual Ultrasound showed insufficient sensitivity in detecting small or early-stage hepatocellular carcinoma (HCC). Abbreviated magnetic resonance imaging (A-MRI) protocols with fewer sequences demonstrated higher HCC detection sensitivity than ultrasound with acceptable cost and examination time. PURPOSE: To compare the diagnostic performance of gadoxetic acid-enhanced A-MRI with a full sequence MRI (F-MRI) protocol for small HCC (≤2 cm) in cirrhotic or hepatitis B virus-infected high-risk patients. MATERIAL AND METHODS: Two hundred and four consecutive patients with 166 pathologically confirmed small HCC who underwent preoperative gadoxetic acid-enhanced MRI were retrospectively included. A-MRI set comprised T1-weighted hepatobiliary phase imaging, T2-weighted imaging, diffusion-weighted imaging and apparent diffusion coefficient mapping. Two independent radiologists blinded to clinical data assessed the A-MRI set and F-MRI set. Per-patient HCC and per-lesion HCC diagnostic performance were compared. RESULTS: Per-patient HCC detection sensitivity of A-MRI set was 93.8% and 91.2% for observer 1 and observer 2, and, for the F-MRI set, the per-patient HCC detection sensitivity was 96.6% and 95.2%, respectively. There was no significant difference in per-patient sensitivity, specificity and per-lesion HCC detection sensitivity between the two imaging sets for both readers. (P = 0.06-0.25) The A-MRI set showed higher sensitivity on HCC without arterial phase hyperenhancement, and the F-MRI set demonstrated with higher sensitivity on HCC with arterial phase hyperenhancement (P < 0.05). CONCLUSION: A-MRI using diagnostic criteria including hypointensity on hepatobiliary phase plus mild to moderate hyperintensity on T2-weighted imaging or restricted diffusion demonstrated comparable sensitivity and specificity for small HCC compared to the F-MRI protocol in high-risk patients.

Tumor Radiomic Features on Pretreatment MRI to Predict Response to Lenvatinib plus an Anti-PD-1 Antibody in Advanced Hepatocellular Carcinoma: A Multicenter Study.

Introduction: Lenvatinib plus an anti-PD-1 antibody has shown promising antitumor effects in patients with advanced hepatocellular carcinoma (HCC), but with clinical benefit limited to a subset of patients. We developed and validated a radiomic-based model to predict objective response to this combination therapy in advanced HCC patients. Methods: Patients (N = 170) who received first-line combination therapy with lenvatinib plus an anti-PD-1 antibody were retrospectively enrolled from 9 Chinese centers; 124 and 46 into the training and validation cohorts, respectively. Radiomic features were extracted from pretreatment contrast-enhanced MRI. After feature selection, clinicopathologic, radiomic, and clinicopathologic-radiomic models were built using a neural network. The performance of models, incremental predictive value of radiomic features compared with clinicopathologic features and relationship between radiomic features and survivals were assessed. Results: The clinicopathologic model modestly predicted objective response with an AUC of 0.748 (95% CI: 0.656-0.840) and 0.702 (95% CI: 0.547-0.884) in the training and validation cohorts, respectively. The radiomic model predicted response with an AUC of 0.886 (95% CI: 0.815-0.957) and 0.820 (95% CI: 0.648-0.984), respectively, with good calibration and clinical utility. The incremental predictive value of radiomic features to clinicopathologic features was confirmed with a net reclassification index of 47.9% (p < 0.001) and 41.5% (p = 0.025) in the training and validation cohorts, respectively. Furthermore, radiomic features were associated with overall survival and progression-free survival both in the training and validation cohorts, but modified albumin-bilirubin grade and neutrophil-to-lymphocyte ratio were not. Conclusion: Radiomic features extracted from pretreatment MRI can predict individualized objective response to combination therapy with lenvatinib plus an anti-PD-1 antibody in patients with unresectable or advanced HCC, provide incremental predictive value over clinicopathologic features, and are associated with overall survival and progression-free survival after initiation of this combination regimen.

Circulating immune index predicting the prognosis of patients with hepatocellular carcinoma treated with lenvatinib and immunotherapy.

Background: Immune checkpoint inhibitor (ICI)-based combination therapy has opened a new avenue for the treatment of multiple malignancies including hepatocellular carcinoma (HCC). However, considering the unsatisfactory efficacy, biomarkers are urgently needed to identify the patients most likely to benefit from ICI-based combination therapy. Methods: A total of 194 patients undergoing ICI-based combination therapy for unresectable HCC were retrospectively enrolled and divided into a training cohort (n = 129) and a validation cohort (n = 65) randomly. A novel circulating immune index (CII) defined as the ratio of white blood cell count (×109/L) to lymphocyte proportion (%) was constructed and its prognostic value was determined and validated. Results: Patients with CII ≤ 43.1 reported prolonged overall survival (OS) compared to those with CII > 43.1 (median OS: 24.7 vs 15.1 months; 6-, 12-, 18-month OS: 94.2%, 76.7%, 66.1% vs 86.4%, 68.2%, 22.8%, P = 0.019), and CII was identified as an independent prognostic factor for OS (hazard ratio, 2.24; 95% confidence interval, 1.17-4.31; P = 0.015). These results were subsequently verified in the validation cohort. Additionally, patients with low CII levels had improved best radiological tumor response (complete response, partial response, stable disease, progressive disease: 3%, 36%, 50%, 11% vs 0%, 27%, 46%, 27%; P = 0.037) and disease control rate (89% vs 73%; P = 0.031) in the pooled cohort and better pathologic response (pathologic complete response, major pathologic response, partial pathologic response, no pathologic response: 20%, 44%, 28%, 8% vs 0%, 0%, 40%, 60%; P = 0.005) in the neoadjuvant cohort. Detection of lymphocyte subsets revealed that an elevated proportion of CD4+ T cells was related to better OS, while the proportion of CD8+ T cells was not. Conclusions: We constructed a novel circulating immune biomarker that was capable of predicting OS and therapeutic efficacy for HCC patients undergoing ICI and lenvatinib combination therapy.

Prognostic model for predicting outcome and guiding treatment decision for unresectable hepatocellular carcinoma treated with lenvatinib monotherapy or lenvatinib plus immunotherapy.

Background: Lenvatinib monotherapy and combination therapy with immune checkpoint inhibitors (ICI) were widely applied for unresectable hepatocellular carcinoma (uHCC). However, many patients failed to benefit from the treatments. A prognostic model was needed to predict the treatment outcomes and guide clinical decisions. Methods: 304 patients receiving lenvatinib monotherapy or lenvatinib plus ICI for uHCC were retrospectively included. The risk factors derived from the multivariate analysis were used to construct the predictive model. The C-index and area under the receiver-operating characteristic curve (AUC) were calculated to assess the predictive efficiency. Results: Multivariate analysis revealed that protein induced by vitamin K absence or antagonist-II (PIVKA-II) (HR, 2.05; P=0.001) and metastasis (HR, 2.07; P<0.001) were independent risk factors of overall survival (OS) in the training cohort. Herein, we constructed a prognostic model called PIMET score and stratified patients into the PIMET-low group (without metastasis and PIVKA-II<600 mAU/mL), PIMET-int group (with metastasis or PIVKA-II>600 mAU/mL) and PIMET-high group (with metastasis and PIVKA-II>600 mAU/mL). The C-index of PIMET score for the survival prediction was 0.63 and 0.67 in the training and validation cohort, respectively. In the training cohort, the AUC of 12-, 18-, and 24-month OS was 0.661, 0.682, and 0.744, respectively. The prognostic performances of the model were subsequently validated. The AUC of 12-, 18-, and 24-month OS was 0.724, 0.726, and 0.762 in the validation cohort. Subgroup analyses showed consistent predictive value for patients receiving lenvatinib monotherapy and patients receiving lenvatinib plus ICI. The PIMET score could also distinguish patients with different treatment responses. Notably, the combination of lenvatinib and ICI conferred survival benefits to patients with PIMET-int or PIMET-high, instead of patients with PIMET-low. Conclusion: The PIMET score comprising metastasis and PIVKA-II could serve as a helpful prognostic model for uHCC receiving lenvatinib monotherapy or lenvatinib plus ICI. The PIMET score could guide the treatment decision and facilitate precision medicine for uHCC patients.

Prognostic value of preoperative CT features for disease-free survival in patients with primary gastric gastrointestinal stromal tumors after resection.

PURPOSE: Tumor size is an important prognostic factor without consideration of the necrotic and cystic components within tumor for patients with gastrointestinal stromal tumors (GISTs). We aimed to extract the enhancing viable component from the tumor using computed tomography (CT) post-processing software and evaluate the value of preoperative CT features for predicting the disease-free survival (DFS) after curative resection for patients with primary gastric GISTs. METHODS: 132 Patients with primary gastric GISTs who underwent preoperative contrast-enhanced CT and curative resection were retrospectively analyzed. We used a certain CT attenuation of 30 HU to extract the enhancing tissue component from the tumor. Enhancing tissue volume and other CT features were assessed on venous-phase images. We evaluated the value of preoperative CT features for predicting the DFS after surgery. Univariate and multivariate Cox regression analyses were performed to find the independent risk factor for predicting the DFS. RESULTS: Of the 132 patients, 68 were males and 64 were females, with a mean age of 61 years. The median follow-up duration was 60 months, and 28 patients experienced disease recurrence and distant metastasis during the follow-up period. Serosal invasion (p < 0.001; HR = 5.277) and enhancing tissue volume (p = 0.005; HR = 1.447) were the independent risk factors for predicting the DFS after curative resection for patients with primary gastric GISTs. CONCLUSION: Preoperative contrast-enhanced CT could be useful for predicting the DFS after the surgery of gastric GISTs, and serosal invasion and enhancing tissue volume were the independent risk factors.

Diagnostic Performance of Contrast Enhanced CT Alone or in Combination with (Non-)Enhanced MRI for Colorectal Liver Metastasis.

RATIONALE AND OBJECTIVES: To compare the diagnostic performance of contrast enhanced CT (CE-CT), CE-CT combined with non-enhanced MRI (NE-MRI) or contrast enhanced MRI (CE-MRI) for colorectal liver metastasis (CRLM). MATERIALS AND METHODS: Sixty-six colorectal cancer patients with 198 focal liver lesions who underwent preoperative abdominal CE-CT and MRI examinations were included respectively. The images were assessed independently by two readers in three protocols (1: CE-CT, 2: CE-CT+NE-MRI, 3: CE-CT+CE-MRI). The diagnostic performance of each protocol was analyzed by receiver operating characteristic (ROC) curve and the areas under ROC (AUCs) were calculated and compared. RESULTS: The detection rates of protocol 2 were 90.9%-92.9% for liver lesions and 86.4%-89.6% for CRLM, and both significantly higher than protocol 1 of 82.8%-85.4% and 76.8%-80.8% (p<0.001-0.001), whereas similar to protocol 3 of 91.9%-94.4% and 87.2%-91.2% (p 0.250-1.000). The AUCs of protocol 2 were greater than protocol 1 for all lesions (0.914-0.934 vs. 0.779-0.799, p<0.001) and lesions < 10mm (0.726-0.776 vs. 0.528-0.561, p<0.001), and were not inferior to that of protocol 3 (0.929-0.949 in all lesions and 0.754-0.821 in lesion < 10mm, p 0.053-0.162). CONCLUSION: CE-CT combined with NE-MRI offered superior diagnostic performance for CRLM compared to CE-CT alone and showed comparable performance to CE-CT combined with CE-MRI.

Ultrashort time-to-echo T2* and T2* relaxometry for evaluation of lumbar disc degeneration: a comparative study.

BACKGROUND: To compare potential of ultrashort time-to-echo (UTE) T2* mapping and T2* values from T2*-weighted imaging for assessing lumbar intervertebral disc degeneration (IVDD),with Pfirrmann grading as a reference standard. METHODS: UTE-T2* and T2* values of 366 lumbar discs (L1/2-L5/S1) in 76 subjects were measured in 3 segmented regions: anterior annulus fibrosus, nucleus pulposus (NP), and posterior annulus fibrosus. Lumbar intervertebral discs were divided into 3 categories based on 5-level Pfirrmann grading: normal (Pfirrmann grade I),early disc degeneration (Pfirrmann grades II-III), and advanced disc degeneration (Pfirrmann grades IV-V). Regional differences between UTE-T2* and T2* relaxometry and correlation with degeneration were statistically analyzed. RESULTS: UTE-T2* and T2*value correlated negatively with Pfirrmann grades (P < 0.001). In NP, correlations with Pfirrmann grade were high with UTE-T2* values (r = - 0.733; P < 0.001) and moderate with T2* values (r = -0.654; P < 0.001). Diagnostic accuracy of detecting early IVDD was better with UTE-T2* mapping than T2* mapping (P < 0.05),with receiver operating characteristic analysis area under the curve of 0.715-0.876. CONCLUSIONS: UTE-T2* relaxometry provides another promising magnetic resonance imaging sequence for quantitatively evaluate lumbar IVDD and was more accurate than T2*mapping in the earlier stage degenerative process.

MR quantitative 3D shape analysis helps to distinguish mucinous cystic neoplasm from serous oligocystic adenoma.

PURPOSE We aimed to assess the performance of quantitative 3D shape analysis in the differential diagno- sis of pancreatic serous oligocystic adenoma (SOA) and mucinous cystic neoplasm (MCN). METHODS Four hundred thirty-two patients diagnosed with serous cystic neoplasms (SCNs) or MCNs were retrospectively reviewed from August 2014 to July 2019 and finally 87 patients with MCNs (n = 45) and SOAs (n = 42) were included. Clinical data and magnetic resonance morphologic fea- tures with 3D shape analysis of lesions (shape sphericity, compacity, and volume) were recorded and compared between MCNs and SOAs according to the pathology. Univariable and multivari- able regression analyses were used to identify independent impact factors for differentiating MCN from SOA. RESULTS The age of MCN patients was younger than SOAs (43.02 ± 10.83 years vs. 52.78 ± 12.31 years; OR = 0.275; 95% CI: 0.098-0.768; P = .014). MCN has a higher female/male ratio than SOA (43/2 vs. 27/15; OR = 40.418; 95% CI: 2.704-604.171; P = .007) and was more often located in the distal of pancreas (OR = 31.403; 95% CI: 2.985-330.342; P = .004). Shape_Sphericity derived from 3D shape analysis was a significant independent factor in the multivariable analysis and the value of MCN was closer to 1 than SOA (OR = 35.153; 95% CI: 5.301-237.585; P < .001). Area under the receiver operating characteristic curve (AUC) of Shape_Sphericity was 0.923 (optimal cutoff value was 0.964876). CONCLUSION Shape_Sphericity in combination with age, sex, and location could help to distinguish MCN from SOA.

A Multiparametric Fusion Deep Learning Model Based on DCE-MRI for Preoperative Prediction of Microvascular Invasion in Intrahepatic Cholangiocarcinoma.

BACKGROUND: Assessment of microvascular invasion (MVI) in intrahepatic cholangiocarcinoma (ICC) by using a noninvasive method is an unresolved issue. Deep learning (DL) methods based on multiparametric fusion of MR images have the potential of preoperative assessment of MVI. PURPOSE: To investigate whether a multiparametric fusion DL model based on MR images can be used for preoperative assessment of MVI in ICC. STUDY TYPE: Retrospective. POPULATION: A total of 519 patients (200 females and 319 males) with a single ICC were categorized as a training (n = 361), validation (n = 90), and an external test cohort (n = 68). FIELD STRENGTH/SEQUENCE: A 1.5 T and 3.0 T; axial T2-weighted turbo spin-echo sequence, diffusion-weighted imaging with a single-shot spin-echo planar sequence, and dynamic contrast-enhanced (DCE) imaging with T1-weighted three-dimensional quick spoiled gradient echo sequence. ASSESSMENT: DL models of multiparametric fusion convolutional neural network (CNN) and late fusion CNN were both constructed for evaluating MVI in ICC. Gradient-weighted class activation mapping was used for visual interpretation of MVI status in ICC. STATISTICAL TESTS: The DL model performance was assessed through the receiver operating characteristic curve (ROC) analysis, and the area under the ROC curve (AUC) with the accuracy, sensitivity, and specificity were measured. P value < 0.05 was considered as statistical significance. RESULTS: In the external test cohort, the proposed multiparametric fusion DL model achieved an AUC of 0.888 with an accuracy of 86.8%, sensitivity of 85.7%, and specificity of 87.0% for evaluating MVI in ICC, and the positive predictive value and negative predictive value were 63.2% and 95.9%, respectively. The late fusion DL model achieved a lower AUC of 0.866, with an accuracy of 83.8%, sensitivity of 78.6%, specificity of 85.2% for evaluating MVI in ICC. DATA CONCLUSION: Our DL model based on multiparametric fusion of MRI achieved a good diagnostic performance in the evaluation of MVI in ICC. LEVEL OF EVIDENCE: 3 TECHNICAL EFFICACY: Stage 2.

A predictive model integrating deep and radiomics features based on gadobenate dimeglumine-enhanced MRI for postoperative early recurrence of hepatocellular carcinoma.

PURPOSE: Hepatocellular carcinoma (HCC) is the most common liver cancer worldwide, and early recurrence of HCC after curative hepatic resection is indicative of poor prognoses. We aim to develop a predictive model for postoperative early recurrence of HCC based on deep and radiomics features from multi-phasic magnetic resonance imaging (MRI). MATERIALS AND METHODS: A total of 472 HCC patients were included and divided into the training (n = 378) and validation (n = 94) cohorts in the retrospective study. We separately extracted radiomics features and deep features from eight phases of gadoxetic acid-enhanced MRI and utilized the least absolute shrinkage and selection operator logistic regression algorithm for feature selection and model construction. We integrated the selected two types of features into a combined model and established a radiomics model as well as a deep learning (DL) model for comparison. RESULTS: In the training and validation cohorts, the combined model demonstrated better performance for stratifying patients at high risk of early recurrence (AUC of 0.911 and 0.840, accuracy of 0.779 and 0.777, sensitivity of 0.927 and 0.769, specificity 0.720 and 0.779) than the radiomics model (AUC of 0.740 and 0.780) and the DL model (AUC of 0.887 and 0.813). CONCLUSION: The combined model integrating deep and radiomics features from multi-phasic MRI is efficient for noninvasively stratifying patients at high risk of early HCC recurrence after resection.

Microvascular invasion of small hepatocellular carcinoma can be preoperatively predicted by the 3D quantification of MRI.

OBJECTIVES: To explore the importance of three-dimensional (3D) quantitative analysis during gadoxetic acid-enhanced magnetic resonance imaging (MRI) of microvascular invasion (MVI) and early recurrence (< 2 years) after surgery of single hepatocellular carcinoma (HCC) ≤ 3 cm. METHODS: Two hundred fourteen patients with pathologically confirmed HCC (training cohort: n = 169; validation cohort: n = 45) were included retrospectively. The 3D quantitative parameters (volume, sphericity, and compacity) and conventional MRI features were analyzed. The significant predictors for MVI were identified using univariate and multivariate logistic regression analyses. Nomograms were constructed from the prediction model, and the relationship between the significant predictors and early recurrence rates was evaluated using the Kaplan-Meier method. RESULTS: Tumor sphericity (odds ratio [OR] = 0.000; p < 0.001), non-smooth tumor margin (OR = 3.353; p = 0.015), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR = 14.067; p = 0.003) were independent significant factors for MVI. When these three factors were combined, the diagnostic specificity of the training and validation cohorts was 97.0 (128/132) and 87.9 (29/33), respectively. The nomogram based on the predictive model performed satisfactorily in the training (C-index: 0.885) and validation (C-index: 0.869) cohorts. Early recurrence rates of patients with two or three significant factors were significantly higher than those with none in the training (29.1% vs. 10.2%, p = 0.007) and validation (36.4% vs. 6.7%, p = 0.037) cohorts. CONCLUSIONS: Lower sphericity combined with non-smooth tumor margin and peritumoral hypointensity on HBP are potential predictive factors for MVI and associated with early recurrence after surgery of HCC ≤ 3 cm. KEY POINTS: • Lower sphericity, non-smooth tumor margin, and peritumoral hypointensity on HBP were important indicators of the occurrence of MVI in HCC. • The combinational model prepared from these findings satisfactorily predicted MVI, and the presence of these predictors was associated with an early recurrence rate after surgical resection in HCC patients. • This model could help clinicians in the preoperative management of small HCC ≤ 3 cm.

Hepatobiliary phase images of gadoxetic acid-enhanced MRI may improve accuracy of predicting the size of hepatocellular carcinoma at pathology.

BACKGROUND: Gadoxetic acid-enhanced magnetic resonance imaging (MRI) has been widely used in clinical practice. However, scientific evidence is lacking for recommending a particular sequence for measuring tumor size. PURPOSE: To retrospectively compare the size of hepatocellular carcinoma (HCC) measured on different gadoxetic acid-enhanced MRI sequences using pathology as a reference. MATERIAL AND METHODS: A total of 217 patients with single HCC who underwent gadoxetic acid-enhanced MRI before surgery were included. The size of the HCC was measured by two abdominal radiologists independently on the following sequences: T1-weighted; T2-weighted; b-500 diffusion-weighted imaging (DWI); and arterial, portal venous, transitional, and hepatobiliary phases. Tumor size measured on MRI was compared with pathological size by using Pearson correlation coefficient, independent-sample t test, and Bland-Altman plot. Agreement between two readers was evaluated with intraclass correlation coefficient (ICC). RESULTS: Correlation between the MR images and pathology was high for both readers (0.899-0.955). Absolute error between MRI and pathologic assessment was lowest on hepatobiliary phase images for both readers (reader 1, 2.8±4.2 mm; reader 2, 3.2±3.4 mm) and highest on arterial phase images for reader 1 (4.9±4.4 mm) and DWI phase images for reader 2 (5.1±4.9 mm). Absolute errors were significantly different for hepatobiliary phase compared with other sequences for both readers (reader 1, P≤0.012; reader 2, P≤0.037). Inter-reader agreements for all sequence measurements were strong (0.971-0.997). CONCLUSION: The performance of gadoxetic acid-enhanced MRI sequences varied with HCC size, and the hepatobiliary phase may be optimal among these sequences.

The Chinese Society of Clinical Oncology (CSCO): Clinical guidelines for the diagnosis and treatment of gastric cancer, 2021.

There exist differences in the epidemiological characteristics, clinicopathological features, tumor biological characteristics, treatment patterns, and drug selections between gastric cancer patients from the Eastern and Western countries. The Chinese Society of Clinical Oncology (CSCO) has organized a panel of senior experts specializing in all sub-specialties of gastric cancer to compile a clinical guideline for the diagnosis and treatment of gastric cancer since 2016 and renews it annually. Taking into account regional differences, giving full consideration to the accessibility of diagnosis and treatment resources, these experts have conducted expert consensus judgment on relevant evidence and made various grades of recommendations for the clinical diagnosis and treatment of gastric cancer to reflect the value of cancer treatment and meeting health economic indexes in China. The 2021 CSCO Clinical Practice Guidelines for Gastric Cancer covers the diagnosis, treatment, follow-up, and screening of gastric cancer. Based on the 2020 version of the CSCO Chinese Gastric Cancer guidelines, this updated guideline integrates the results of major clinical studies from China and overseas for the past year, focused on the inclusion of research data from the Chinese population for more personalized and clinically relevant recommendations. For the comprehensive treatment of non-metastatic gastric cancer, attentions were paid to neoadjuvant treatment. The value of perioperative chemotherapy is gradually becoming clearer and its recommendation level has been updated. For the comprehensive treatment of metastatic gastric cancer, recommendations for immunotherapy were included, and immune checkpoint inhibitors from third-line to the first-line of treatment for different patient groups with detailed notes are provided.

Utility of preoperative computed tomography features in predicting the Ki-67 labeling index of gastric gastrointestinal stromal tumors.

PURPOSE: To evaluate the value of preoperative computed tomography (CT) features including morphologic and quantitative features for predicting the Ki-67 labeling index (Ki-67LI) of gastric gastrointestinal stromal tumors (GISTs). METHODS: We retrospectively included 167 patients with gastric GISTs who underwent preoperative contrast-enhanced CT. We assessed the morphologic features of preoperative CT images and the quantitative features including the maximum diameter of tumor, total tumor volume, mean total tumor CT value, necrosis volume, necrosis volume ratio, enhanced tissue volume, and mean CT value of enhanced tissue. Potential predictive parameters to distinguish the high-level Ki-67LI group (>4%, n = 125) from the low-level Ki-67LI group (≤4%, n = 42) were compared and subsequently determined in multivariable logistic regression analysis. RESULTS: Growth pattern (p = 0.036), shape (p = 0.000), maximum diameter (p = 0.018), total tumor volume (p = 0.021), mean total tumor CT value (p = 0.009), necrosis volume (p = 0.006), necrosis volume ratio (p = 0.000), enhanced tissue volume (p = 0.027), and mean CT value of enhanced tissue (p = 0.004) were significantly different between the two groups. Multivariate logistic regression analysis indicated that lobulated/irregular shape (odds ratio [OR] = 3.817; p = 0.000) and high necrosis volume ratio (OR = 1.935; p = 0.024) were independent factors of high-level Ki-67LI. CONCLUSIONS: Higher necrosis volume ratio in combination with lobulated/irregular shape could potentially predict high expression of Ki-67LI for gastric GISTs.

A magnetic resonance imaging modality for non-invasively distinguishing progression of liver fibrosis by visualizing hepatic platelet-derived growth factor receptor-beta expression in mice.

BACKGROUND AND AIM: Activated hepatic stellate cells (HSCs) are the most critical cells responsible for liver fibrosis, and platelet-derived growth factor (PDGF) is the most prominent mitogen for HSCs in fibrogenesis. This study aimed to explore the potential of gadolinium (Gd)-labeled cyclic peptides (pPB) targeting PDGF receptor-ß (PDGFR-ß) as a magnetic resonance imaging (MRI) radiotracer to identify the progression of liver fibrosis by imaging hepatic PDGFR-ß expression. METHODS: Mice treated with carbon tetrachloride (CCl4 ) were used to mimic hepatic fibrosis in vivo. The binding activity of FITC-labeled pPB to PDGFR-ß was assessed in cultured human HSCs (HSC-LX2). MRI was performed to visualize hepatic PDGFR-ß expression in mice with different degrees of liver fibrosis after Gd-labeled pPB was injected. RESULTS: Hepatic PDGFR-ß expression level was correlated with the severity of liver fibrosis, and the majority of cells expressing PDGFR-ß were found to be activated HSCs in fibrotic livers. Culture-activated human HSCs expressed abundant PDGFR-ß, and FITC-labeled pPB could bind to these cells in a concentration-dependent and time-dependent manner. With Gd-labeled pPB as a tracer, an MRI modality demonstrated that the relative hepatic T1-weighted MRI signal value progressively increased with the severity of hepatic fibrosis and reduced with remission. CONCLUSIONS: Hepatic PDGFR-ß expression reflects the progression of hepatic fibrosis, and MRI using Gd-labeled pPB as a tracer exhibits potential for distinguishing liver fibrosis staging in mice.

Feasibility of compressed sensing technique for isotropic dynamic contrast-enhanced liver magnetic resonance imaging.

PURPOSE: To investigate whether an isotropic T1-weighted gradient echo (T1-GRE) sequence using a compressed sensing (CS) technique during liver magnetic resonance imaging (MRI) can improve the image quality compared to that using a standard parallel imaging (PI) technique in patients with hepatocellular carcinoma (HCC). METHODS: Forty-nine patients with single pathologically confirmed HCC were included in the prospective study, who underwent a 3.0 T MRI including the two T1-GRE sequences (CS and PI). Qualitative analysis including the relative contrast (RC) of liver-to-lesion, liver-to-portal vein and liver-to-hepatic vein on pre-contrast and postcontrast (delayed phase) images were calculated. Respiratory motion artifact, gastrointestinal motion artifact and overall image quality were scored by using a 4-point scale. RESULTS: RC of liver-to-lesion, liver-to-portal vein and liver-to-hepatic vein measured on both pre-contrast and postcontrast phase images were significantly higher for CS than for PI. The scores of overall image quality was comparable between PI and CS (3.98 ±â€¯0.10vs 3.96 ±â€¯0.13, P = 0.083 for pre-contrast; 3.96 ±â€¯0.16 vs 3.93 ±â€¯0.17, P = 0.132 for postcontrast, respectively). The scores of gastrointestinal motion artifact was significantly higher for PI than for CS (3.92 ±â€¯0.21 vs 3.69 ±â€¯0.33 for pre-contrast; 3.86 ±â€¯0.21 vs 3.59 ±â€¯0.30 for postcontrast, P < 0.001 for both). The scores of respiratory motion artifact was significantly higher for PI only in pre-contrast sequence (3.97±0.11 vs 3.89 ±â€¯0.22, P = 0.002 for pre-contrast; 3.95 ±â€¯0.18 vs 3.90 ±â€¯0.22, P = 0.083 for postcontrast, respectively). CONCLUSIONS: Compared to the standard PI sequence, the CS technique can provide greater contrast in displaying HCCs and hepatic vessels in MRI without compromise of overall image quality.

Multi-scale and multi-parametric radiomics of gadoxetate disodium-enhanced MRI predicts microvascular invasion and outcome in patients with solitary hepatocellular carcinoma ≤ 5 cm.

OBJECTIVES: To develop radiomics-based nomograms for preoperative microvascular invasion (MVI) and recurrence-free survival (RFS) prediction in patients with solitary hepatocellular carcinoma (HCC) ≤ 5 cm. METHODS: Between March 2012 and September 2019, 356 patients with pathologically confirmed solitary HCC ≤ 5 cm who underwent preoperative gadoxetate disodium-enhanced MRI were retrospectively enrolled. MVI was graded as M0, M1, or M2 according to the number and distribution of invaded vessels. Radiomics features were extracted from DWI, arterial, portal venous, and hepatobiliary phase images in regions of the entire tumor, peritumoral area ≤ 10 mm, and randomly selected liver tissue. Multivariate analysis identified the independent predictors for MVI and RFS, with nomogram visualized the ultimately predictive models. RESULTS: Elevated alpha-fetoprotein, total bilirubin and radiomics values, peritumoral enhancement, and incomplete or absent capsule enhancement were independent risk factors for MVI. The AUCs of MVI nomogram reached 0.920 (95% CI: 0.861-0.979) using random forest and 0.879 (95% CI: 0.820-0.938) using logistic regression analysis in validation cohort (n = 106). With the 5-year RFS rate of 68.4%, the median RFS of MVI-positive (M2 and M1) and MVI-negative (M0) patients were 30.5 (11.9 and 40.9) and > 96.9 months (p < 0.001), respectively. Age, histologic MVI, alkaline phosphatase, and alanine aminotransferase independently predicted recurrence, yielding AUC of 0.654 (95% CI: 0.538-0.769, n = 99) in RFS validation cohort. Instead of histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest achieved comparable accuracy in MVI stratification and RFS prediction. CONCLUSIONS: Preoperative radiomics-based nomogram using random forest is a potential biomarker of MVI and RFS prediction for solitary HCC ≤ 5 cm. KEY POINTS: • The radiomics score was the predominant independent predictor of MVI which was the primary independent risk factor for postoperative recurrence. • The radiomics-based nomogram using either random forest or logistic regression analysis has obtained the best preoperative prediction of MVI in HCC patients so far. • As an excellent substitute for the invasive histologic MVI, the preoperatively predicted MVI by MVI nomogram using random forest (MVI-RF) achieved comparable accuracy in MVI stratification and outcome, reinforcing the radiologic understanding of HCC angioinvasion and progression.