A radiomics-based interpretable model to predict the pathological grade of pancreatic neuroendocrine tumors.

OBJECTIVES: To develop a computed tomography (CT) radiomics-based interpretable machine learning (ML) model to predict the pathological grade of pancreatic neuroendocrine tumors (pNETs) in a non-invasive manner. METHODS: Patients with pNETs who underwent contrast-enhanced abdominal CT between 2010 and 2022 were included in this retrospective study. Radiomics features were extracted, and five radiomics-based ML models, namely logistic regression (LR), random forest (RF), support vector machine (SVM), XGBoost, and GaussianNB, were developed. The performance of these models was evaluated using a time-independent testing set, and metrics such as sensitivity, specificity, accuracy, and the area under the receiver operating characteristic curve (AUC) were calculated. The accuracy of the radiomics model was compared to that of needle biopsy. The Shapley Additive Explanation (SHAP) tool and the correlation between radiomics and biological features were employed to explore the interpretability of the model. RESULTS: A total of 122 patients (mean age: 50 ± 14 years; 53 male) were included in the training set, whereas 100 patients (mean age: 48 ± 13 years; 50 male) were included in the testing set. The AUCs for LR, SVM, RF, XGBoost, and GaussianNB were 0.758, 0.742, 0.779, 0.744, and 0.745, respectively, with corresponding accuracies of 73.0%, 70.0%, 77.0%, 71.9%, and 72.9%. The SHAP tool identified two features of the venous phase as the most significant, which showed significant differences among the Ki-67 index or mitotic count subgroups (p < 0.001). CONCLUSIONS: An interpretable radiomics-based RF model can effectively differentiate between G1 and G2/3 of pNETs, demonstrating favorable interpretability. CLINICAL RELEVANCE STATEMENT: The radiomics-based interpretable model developed in this study has significant clinical relevance as it offers a non-invasive method for assessing the pathological grade of pancreatic neuroendocrine tumors and holds promise as an important complementary tool to traditional tissue biopsy. KEY POINTS: • A radiomics-based interpretable model was developed to predict the pathological grade of pNETs and compared with preoperative needle biopsy in terms of accuracy. • The model, based on CT radiomics, demonstrated favorable interpretability. • The radiomics model holds potential as a valuable complementary technique to preoperative needle biopsy; however, it should not be considered a replacement for biopsy.

Dual-energy CT improves differentiation of non-hypervascular pancreatic neuroendocrine neoplasms from CA 19-9-negative pancreatic ductal adenocarcinomas.

PURPOSE: To evaluate the utility of dual-energy CT (DECT) in differentiating non-hypervascular pancreatic neuroendocrine neoplasms (PNENs) from pancreatic ductal adenocarcinomas (PDACs) with negative carbohydrate antigen 19-9 (CA 19-9). METHODS: This retrospective study included 26 and 39 patients with pathologically confirmed non-hypervascular PNENs and CA 19-9-negative PDACs, respectively, who underwent contrast-enhanced DECT before treatment between June 2019 and December 2021. The clinical, conventional CT qualitative, conventional CT quantitative, and DECT quantitative parameters of the two groups were compared using univariate analysis and selected by least absolute shrinkage and selection operator regression (LASSO) analysis. Multivariate logistic regression analyses were performed to build qualitative, conventional CT quantitative, DECT quantitative, and comprehensive models. The areas under the receiver operating characteristic curve (AUCs) of the models were compared using DeLong's test. RESULTS: The AUCs of the DECT quantitative (based on normalized iodine concentrations [nICs] in the arterial and portal venous phases: 0.918; 95% confidence interval [CI] 0.852-0.985) and comprehensive (based on tumour location and nICs in the arterial and portal venous phases: 0.966; 95% CI 0.889-0.995) models were higher than those of the qualitative (based on tumour location: 0.782; 95% CI 0.665-0.899) and conventional CT quantitative (based on normalized conventional CT attenuation in the arterial phase: 0.665; 95% CI 0.533-0.797; all P < 0.05) models. The DECT quantitative and comprehensive models had comparable performances (P = 0.076). CONCLUSIONS: Higher nICs in the arterial and portal venous phases were associated with higher blood supply improving the identification of non-hypervascular PNENs.

Evaluation of Hypoxia in Hepatocellular Carcinoma Using Quantitative MRI: Significances, Challenges, and Advances.

This review aimed to perform a scoping review of promising MRI methods in assessing tumor hypoxia in hepatocellular carcinoma (HCC). The hypoxic microenvironment and upregulated hypoxic metabolism in HCC are determining factors of poor prognosis, increased metastatic potential, and resistance to chemotherapy and radiotherapy. Assessing hypoxia in HCC is essential for personalized therapy and predicting prognoses. Oxygen electrodes, protein markers, optical imaging, and positron emission tomography can evaluate tumor hypoxia. These methods lack clinical applicability because of invasiveness, tissue depth, and radiation exposure. MRI methods, including blood oxygenation level-dependent, dynamic contrast-enhanced MRI, diffusion-weighted imaging, MRI spectroscopy, chemical exchange saturation transfer MRI, and multinuclear MRI, are promising noninvasive methods that evaluate the hypoxic microenvironment by observing biochemical processes in vivo, which may inform on therapeutic options. This review summarizes the recent challenges and advances in MRI techniques for assessing hypoxia in HCC and highlights the potential of MRI methods for examining the hypoxic microenvironment via specific metabolic substrates and pathways. Although the utilization of MRI methods for evaluating hypoxia in patients with HCC is increasing, rigorous validation is needed in order to translate these MRI methods into clinical use. Due to the limited sensitivity and specificity of current quantitative MRI methods, their acquisition and analysis protocols require further improvement. EVIDENCE LEVEL: 3. TECHNICAL EFFICACY: Stage 4.

Clinical outcome is distinct between radiological stricture and endoscopic stricture in ileal Crohn's disease.

OBJECTIVES: Differences in clinical adverse outcomes (CAO) based on different intestinal stricturing definitions in Crohn's disease (CD) are poorly documented. This study aims to compare CAO between radiological strictures (RS) and endoscopic strictures (ES) in ileal CD and explore the significance of upstream dilatation in RS. METHODS: This retrospective double-center study included 199 patients (derivation cohort, n = 157; validation cohort, n = 42) with bowel strictures who simultaneously underwent endoscopic and radiologic examinations. RS was defined as a luminal narrowing with wall thickening relative to the normal gut on cross-sectional imaging (group 1 (G1)), which further divided into G1a (without upstream dilatation) and G1b (with upstream dilatation). ES was defined as an endoscopic non-passable stricture (group 2 (G2)). Strictures met the definitions of RS (with or without upstream dilatation) and ES were categorized as group 3 (G3). CAO referred to stricture-related surgery or penetrating disease. RESULTS: In the derivation cohort, G1b (93.3%) had the highest CAO occurrence rate, followed by G3 (32.6%), G1a (3.2%), and G2 (0%) (p < 0.0001); the same order was found in the validation cohort. The CAO-free survival time was significantly different among the four groups (p < 0.0001). Upstream dilatation (hazard ratio, 1.126) was a risk factor for predicting CAO in RS. Furthermore, when upstream dilatation was added to diagnose RS, 17.6% of high-risk strictures were neglected. CONCLUSIONS: CAO differs significantly between RS and ES, and clinicians should pay more attention to strictures in G1b and G3. Upstream dilatation has an important impact on the clinical outcome of RS but may not be an essential factor for RS diagnosis. CLINICAL RELEVANCE STATEMENT: This study explored the definition of intestinal stricture with the greatest significance for the clinical diagnosis and prognosis of patients with CD, and consequently provided effective auxiliary information for clinicians to formulate strategies for the treatment of CD intestinal strictures. KEY POINTS: • The retrospective double-center study showed that clinical adverse outcome is different between radiological strictures and endoscopic strictures in CD. • Upstream dilatation has an important impact on the clinical outcome of radiological strictures but may not be an essential factor for diagnosis of radiological strictures. • Radiological stricture with upstream dilatation and simultaneous radiological and endoscopic stricture were at increased risk for clinical adverse outcomes; thus, closer monitoring should be considered.

Non-invasive diagnosis strategy of hepatocellular carcinoma in low-risk population.

AIMS: With prevalence of hepatocellular carcinoma (HCC) in low-risk population (LRP), establishing a non-invasive diagnostic strategy becomes increasingly urgent to spare unnecessary biopsies in this population. The purposes of this study were to find characterisics of HCC and to establish a proper non-invasive method to diagnose HCC in LRP. METHODS: A total of 681 patients in LRP (defined as the population without cirrhosis, chronic HBV infection or HCC history) were collected from 2 institutions. The images of computed tomography (CT) and magnetic resonance imaging (MRI) were manually analysed. We divided the patients into the training cohort (n = 324) and the internal validating cohort (n = 139) by admission time in the first institution. The cohort in the second institution was viewed as the external validation (n = 218). A multivariate logistic regression model incorporating both imaging and clinical independent risk predictors was developed. C-statistics was used to evaluate the diagnostic performance. RESULTS: Besides the major imaging features of HCC (non-rim enhancement, washout and enhancing capsule), tumor necrosis or severe ischemia (TNSI) on imaging and two clinical characteristics (gender and alpha fetoprotein) were also independently associated with HCC diagnosis (all P < 0.01). A clinical model (including 3 major features, TNSI, gender and AFP) was built to diagnose HCC and achieved good diagnostic performance (area under curve values were 0.954 in the training cohort, 0.931 in the internal validation cohort and 0.902 in the external cohort). CONCLUSIONS: The clinical model in this study developed a satisfied non-invasive diagnostic performance for HCC in LRP.

Tumor fibrosis correlates with the survival of patients with pancreatic adenocarcinoma and is predictable using clinicoradiological features.

OBJECTIVES: To evaluate the prognostic value of fibrosis for patients with pancreatic adenocarcinoma (PDAC) and preoperatively predict fibrosis using clinicoradiological features. Tumor fibrosis plays an important role in the chemoresistance of PDAC. However, the prognostic value of tumor fibrosis remains contradiction and accurate prediction of tumor fibrosis is required. METHODS: The study included 131 patients with PDAC who underwent first-line surgery. The prognostic value of fibrosis and rounded cutoff fibrosis points for median overall survival (OS) and disease-free survival (DFS) were determined using Cox regression and receiver operating characteristic (ROC) analyses. Then the whole cohort was randomly divided into training (n = 88) and validation (n = 43) sets. Binary logistic regression analysis was performed to select independent risk factors for fibrosis in the training set, and a nomogram was constructed. Nomogram performance was assessed using a calibration curve and decision curve analysis (DCA). RESULTS: Hazard ratios of fibrosis for OS and DFS were 1.121 (95% confidence interval [CI]: 1.082-1.161) and 1.110 (95% CI: 1.067-1.155). ROC analysis identified 40% as the rounded cutoff fibrosis point for median OS and DFS. Tumor diameter, carbohydrate antigen 19-9 level, and peripancreatic tumor infiltration were independent risk factors; areas under the nomogram curve were 0.810 and 0.804 in the training and validation sets, respectively. The calibration curve indicated good agreement of the nomogram, and DCA demonstrated good clinical usefulness. CONCLUSIONS: Tumor fibrosis was associated with poor OS and DFS in patients with PDAC. The nomogram incorporating clinicoradiological features was useful for preoperatively predicting tumor fibrosis. KEY POINTS: • Tumor fibrosis is correlated with poor prognosis in patients with pancreatic adenocarcinoma. • Tumor fibrosis can be categorized according to its association with overall survival and disease-free survival. • A nomogram incorporating carbohydrate antigen 19-9 level, tumor diameter, and peripancreatic tumor infiltration is useful for preoperatively predicting tumor fibrosis.

Regional liver function analysis with gadoxetic acid-enhanced MRI and virtual hepatectomy: prediction of postoperative short-term outcomes for HCC.

OBJECTIVES: To explore the role of quantitative regional liver function assessed by preoperative gadoxetic acid-enhanced MRI with computer-aided virtual hepatectomy to predict short-term outcomes after major hepatectomy for HCC. METHODS: We retrospectively reviewed the records of 133 consecutive patients with HCC who underwent preoperative gadoxetic acid-enhanced MRI and indocyanine green (ICG) test. Forty-five patients received open major hepatectomy. Liver function reserve and the future liver remnant were evaluated by computer-aided virtual hepatectomy. Global liver functional parameters included the T1 relaxation time reduction rate (T1ratio) and functional liver volume (FV), whereas regional parameters included the rT1pos, rT1ratio, remnant FV (rFV), and remnant FV ratio (rFVratio) of the remnant liver. The functional parameters of the MRI and ICG were used to predict the short-term outcomes (liver failure and major complications) after major hepatectomy. RESULTS: The T1ratio and FV were correlated with the ICG test (rho = - 0.304 and - 0.449, p < 0.05). FV < 682.8 ml indicated preoperative ICG-R15 ≥ 14% with 0.765 value of the area under the curve (AUC). No patient who underwent major resection with good liver functional reserve (ICG < 14%) and enough future remnant volume (> 30% standard LV) developed liver failure. Low rT1ratio (< 66.5%) and high rT1pos (> 217.5 ms) may predict major complications (AUC = 0.831 and 0.756, respectively; p < 0.05). The rT1ratio was an independent risk factor for postoperative major complications (odds ratio [OR] = 0.845, 95% CI, 0.736-0.966; p < 0.05). CONCLUSION: Preoperative gadoxetic acid-enhanced MRI with computer-aided virtual hepatectomy may facilitate optimal assessment of regional liver functional reserve to predict short-term outcomes after major hepatectomy for HCC. KEY POINTS: • Preoperative gadoxetic acid-enhanced MRI with virtual hepatectomy and volumetric analysis can provide precise liver volume and regional functional assessment. • Quantitative regional liver function assessed by gadoxetic acid-enhanced MRI can predict the short-term outcomes after major hepatectomy in patients with HCC. • The regional liver function assessed by gadoxetic acid-enhanced MRI is an independent risk factor for postoperative major complications.

Hepatocellular carcinoma with hilar bile duct tumor thrombus versus hilar Cholangiocarcinoma on enhanced computed tomography: a diagnostic challenge.

BACKGROUND: Hepatocellular carcinoma (HCC) with hilar bile duct tumor thrombus (HBDTT) often mimic hilar cholangiocarcinoma (hilar CC). The purpose of this study is to analyze the Computed Tomography (CT) characteristics of HCC with HBDTT and to identify imaging features to aid its differentiation from hilar CC on enhanced CT. METHODS: We retrospectively identified 58 cases with pathologically proved HCC with HBDTT between 2011 and 2018. Seventy-seven cases of pathologically proven hilar CCs were selected during the same period. The clinical features and CT findings of the two groups were reviewed and compared. RESULTS: HCC with HBDTTs are more commonly found in men (87.9% vs 63.6%, p = 0.001) with lower age of onset (49.84 vs 58.61 years; p < 0.001) in comparison to hilar CCs. Positive correlation were identified between HCC with HBDTTs and chronic HBV infection (72.4% vs 11.7%; p <  0.001), increased serum AFP (67.2% vs 1.3%; p <  0.001), CA19-9 level (58.6% vs 85.7%; p <  0.001) and CEA level (3.4% vs 29.9%; p = 0.001), parenchymal lesion with intraductal lesion (100% vs 18.2%; p <  0.001), washout during the portal venous phase (84.5% vs 6.5%; p <  0.001), thickened bile duct wall (8.6% vs 93.5%; p <  0.001), intrahepatic vascular embolus (44.8% vs 7.8%; p <  0.001), splenomegaly (34.5% vs 2.6%, p <  0.001). A scoring system consisting of the five parameters obtained from characteristics mentioned above was trialed. The sensitivity and specificity for diagnosing HCC with HBDTT were 96.39, 100 and 92.5% respectively when the total score was 2 or more. CONCLUSIONS: HCC with HBDTTs are often distinguishable from hilar CCs based on washout during portal venous phase without thickened bile duct wall. HBV infection and serum AFP level facilitate the differentiation.

Imaging biomarkers for well and moderate hepatocellular carcinoma: preoperative magnetic resonance image and histopathological correlation.

BACKGROUND: Our aim of the study is to investigate the feasibility of preoperative prediction for hepatocellular carcinoma (HCC) histological grading using gadoxetic acid-enhanced magnetic resonance imaging (MRI). METHODS: This study included one hundred and fifty-six patients with solitary HCC. Preoperative gadoxetic acid-enhanced MRI findings were retrospectively analyzed. MRI qualitative features such as tumor size, margin, capsule status, signal homogeneity, intratumoral vessels, peritumoral enhancement during mid-arterial phase, peritumoral hypointensity during the hepatobiliary phase (HBP) were investigated. Apparent diffusion coefficients (ADCs), T1 reduction ratio of pre- and post-contrast enhanced images of the tumors were calculated. HCC histological grading in surgical specimens were confirmed by Edmonson's criteria. Correlations between these MRI features and HCC histological grading were analyzed using multivariate logistic regression. The receiver operating characteristic (ROC) curve was used to assess the predictive efficacy of the model. RESULTS: Univariate analysis showed that maximum tumor diameter (p = 0.004), tumor margin (p = 0.006), intratumoral vessels (p = 0.001) and peritumoral hypointensity during HBP (p = 0.000), were significantly correlated with HCC histological grading. There was no relationship between capsule, tumor signal, venous thrombosis, peritumoral enhancement during mid-arterial phase, ADC value, T1 reduction ratio, and HCC histological grading. Multivariate logistic regression analysis demonstrated that the maximum tumor diameter (p = 0.012, odds ratio = 1.002, 95% confidence interval: 1.007-1.046)) was an independent risk factor for high grade HCC. CONCLUSIONS: Greater tumor size, a more irregular margin, presence of intratumoral vessels, and peritumoral hypointensity during HBP were indicators for high grade HCC. The maximum tumor diameter was an independent risk factor for high grade HCC.

Systemic Venous Drainage Is Associated with an Unfavorable Prenatal Behavior in Fetal Bronchopulmonary Sequestration.

OBJECTIVE: This study aimed to determine the significance of the venous drainage pattern of bronchopulmonary sequestration (BPS) in the prenatal course. METHODS: The venous drainage pattern of fetuses with BPS was determined with high-definition flow and confirmed by postnatal three-dimensional computed tomography angiography scan or autopsy. The volume of BPS lesions during gestation was recorded by the three-dimensional ultrasonographic Virtual Organ Computer-Aided Analysis software. The relationship between venous drainage pattern and prenatal characteristics was determined. RESULTS: Seventy-one fetuses were enrolled: 35 with systemic venous drainage (SVD) and 36 with pulmonary venous drainage (PVD). The volumes of BPS lesions significantly increased from the middle second trimester to the later second trimester in the SVD group. A marked decrease from the later second trimester to the third trimester was observed in the PVD group. The incidences of associated anomalies, hydrops, and polyhydramnios in the SVD group were 14.2, 23.3, and 33.3%, respectively, significantly higher than those in the PVD group (0, 0, and 5.6%, respectively). CONCLUSIONS: Our data indicate that SVD is correlated with a higher risk of associated anomalies and an unfavorable prenatal course in fetal BPS. Identification of the venous drainage pattern is of clinical significance in predicting the prenatal behavior of fetal BPS.

Comparison of Echocardiography and 64-Multislice Spiral Computed Tomography for the Diagnosis of Pediatric Congenital Heart Disease.

BACKGROUND The goals of this study were: to compare echocardiogram and 64-multislice spiral computed tomography (64-MSCT) in diagnosing pediatric congenital heart disease; to determine the significance of ECHO for diagnosing congenital heart disease; and to identify the appropriate diagnosis for congenital heart disease through combined use of 64-MSCT and ECHO. MATERIAL AND METHODS Thirty patients underwent both ECHO and 64-MSCT diagnoses before their surgeries. Imaging from ECHO and 64-MSCT were analyzed by 4 specialists. The diagnostic accuracy and kappa value of ECHO and 64-MSCT were evaluated based on the operation results. The accuracy of the 2 methods was evaluated using the McNemar χ² test. RESULTS We confirmed 138 malformations in 30 children by surgery. The diagnostic accuracy of ECHO and 64-MSCT was 98.40% and 96.20%, respectively, with a significant difference between the 2 results (χ²=6.404, P=0.011). We compared prognosis accuracy and uniformity on 3 types of congenital heart disease (cardiac malformation, heart-large vascular connecting malformation, and large vascular malformation): 56 cardiac malformations were confirmed by surgery, in which the diagnostic accuracy of ECHO and 64-MSCT was 99.50% and 94.80%, respectively. (χ²=8.578, P=0.034); 31 heart-large vascular connecting malformations were confirmed by surgery, in which the diagnostic accuracy of ECHO and 64-MSCT was 99.00% and 95.42% (χ²=6.779, P=0.009); and 51 vascular malformations were confirmed, in which the diagnostic accuracy of ECHO and 64-MSCT was 96.30% and 98.30% (χ²=1.806, P=0.179). CONCLUSIONS ECHO is more effective than 64-MSCT in preoperative diagnosis of congenital heart disease, especially for children.

Benign mixed epithelial and stromal tumor of the kidney with inferior vena cava tumor thrombus: A rare case report and review of literature.

Mixed epithelial and stromal tumor of the kidney (MESTK) is a rare renal tumor composed of epithelial and stromal cells. In this study, we report a rare case of MESTK, which was pathologically benign but complicated with renal vein and inferior vena cava tumor thrombus. The 50-year-old female patient was admitted to hospital for a mass on the left kidney. Computed tomography showed a 32 mm×18 mm mass with slight delayed enhancement in the left renal sinus, and neoplastic thrombus was detected in left renal vein and inferior vena cava. A preoperative diagnosis of renal leiomyoma was made by needle biopsy and a laparoscopic radical nephrectomy with thrombectomy was performed. Histologically, the tumor and thrombus were composed of proliferative spindle cells and a small amount of tubular structures. Both kinds of the cells were well differentiated with no atypia or mitosis of nuclei. Immunohistochemical staining showed positive for CK, Ki-67 in the tubular cells and desmin, actin, estrogen receptors, progesterone receptors in the spindle cells. Finally, the diagnosis of MESTK was established. No recurrence or metastasis was found in the patient with a followed-up period of 12 months after the surgery. Due to the difficulty in diagnosis of MESTK, documentation with more cases of MESTK is needed to further understand its pathogenesis, biological behavior, preoperative diagnosis and optimal management of patient treatment.

Gd-EOB-DTPA-enhanced magnetic resonance imaging combined with T1 mapping predicts the degree of differentiation in hepatocellular carcinoma.

BACKGROUND: Variable degrees of differentiation in hepatocellular carcinoma(HCC)under Edmondson-Steiner grading system has been proven to be an independent prognostic indicator for HCC. Up till now, there has been no effective radiological method that can reveal the degree of differentiation in HCC before surgery. This paper aims to evaluate the use of Gd-EOB-DTPA-Enhanced Magnetic Resonance Imaging combined with T1 mapping for the diagnosis of HCC and assessing its degree of differentiation. METHODS: Forty-four patients with 53 pathologically proven HCC had undergone Gd-EOB-DTPA enhanced MRI with T1 mapping before surgery. Out of the 53 lesions,13 were grade I, 27 were gradeII, and 13 were grade III. The T1 values of each lesion were measured before and at 20 min after Gd-EOB-DTPA administration (T1p and T1e). The absolute reduction in T1 value (T1d) and the percentage reduction (T1d %) were calculated. The one-way ANOVA and Pearson correlation were used for comparisons between the T1 mapping values. RESULTS: The T1d and T1d % of grade I, II and III of HCC was 660.5 ± 422.8ms、295.0 ± 99.6ms、276.2 ± 95.0ms and 54.0 ± 12.2 %、31.5 ± 6.9 %、27.7 ± 6.7 % respectively. The differences between grade Iand II, grade Iand III were statistically significant (p < 0.05), but there was no statically significant difference between grade II and III. The T1d % was the best marker for grading of HCC, with a Spearman correlation coefficient of -0.676. CONCLUSIONS: T1 mapping before and after Gd-EOB-DTPA administration can predict degree of differentiation in HCC.

CT evaluation of gastroenteric neuroendocrine tumors: relationship between ct features and the pathologic classification.

OBJECTIVE: The objective of our study was to compare the CT features of gastroenteric neuroendocrine neoplasms (GE-NENs) with the pathologic classification and to analyze the correlation between the CT features and classification of GE-NENs. MATERIALS AND METHODS: Fifty-six cases of pathologically and immunohisto-chemically proven GE-NENs, including 25 cases of neuroendocrine tumors (NETs) (i.e., G1 and G2 tumors) and 31 cases of neuroendocrine carcinomas (NECs) (i.e., G3 tumors and mixed adenoneuroendocrine carcinomas) were studied. We analyzed various CT features of the primary tumor, nodal status, and metastasis and compared these features with pathologic grading. RESULTS: The CT features that favor NEC over NET include larger tumor size (> 4.0 cm), transmural invasion, circumscribed tumor with both intra- and extraluminal involvement, circumferential growth, areas of cystic change or necrosis, ulceration, mesenteric fat infiltration, and lymphadenopathy, with p values of 0.044, 0.002, 0.024, 0.008, 0.002, 0.007, 0.002, and < 0.001, respectively. The CT features that do not distinguish between the two types of GE-NENs include tumor boundary, growth pattern, degree of enhancement, adjacent organ invasion, distant organ metastasis, and peritoneal seeding, with p values of 0.277, 0.153, 0.672, 1.000, 0.159, and 0.877, respectively. CONCLUSION: CT can be useful in the classification of GE-NENs.

Diagnostic and post-treatment CT appearance of biopsy proven mixed Cryptococcus and Candida cholangitis.

Cryptococcus neoformans and Candida are common opportunistic pathogens of human. There is very limited literature on Cryptococcus neoformans cholangitis or Candida cholangitis in immunocompetent patient while mixed Cryptococcus neoformans and Candida cholangitis has not been reported in the literature ever before. We hereby report the imaging findings of a case of mixed Cryptococcus neoformans and Candida cholangitis in an immunocompetent boy. The CT features included nodules in the cystic duct and common bile duct, dilatation of the intra- and extrahepatic bile ducts with mural thickening, irregular hypodense mass-like lesion extending along the bile ducts from the liver hilum to the periphery which was confirmed by the presence of enlarged and confluent lymph nodes. CT characteristics can contribute to timely diagnosis and treatment of this disease.

Prediction of immunocyte infiltration and prognosis in postoperative hepatitis B virus-related hepatocellular carcinoma patients using magnetic resonance imaging.

Background: The immune microenvironment (IME) is closely associated with prognosis and therapeutic response of hepatitis B virus-related hepatocellular carcinoma (HBV-HCC). Multi-parametric magnetic resonance imaging (MRI) enables non-invasive assessment of IME and predicts prognosis in HBV-HCC. We aimed to construct an MRI prediction model of the immunocyte-infiltration subtypes and explore its prognostic significance. Methods: HBV-HCC patients at the First Affiliated Hospital of Sun Yat-sen University (Guangzhou, China) with radical surgery (between 1 October and 30 December 2021) were prospectively enrolled. Patients with pathologically proven HCC (between 1 December 2013 and 30 October 2019) were retrospectively enrolled. Pearson correlation analysis was used to examine the relationship between the immunocyte-infiltration counts and MRI parameters. An MRI prediction model of immunocyte-infiltration subtypes was constructed in prospective cohort. Kaplan-Meier survival analysis was used to analyse its prognostic significance in the retrospective cohort. Results: Twenty-four patients were prospectively enrolled to construct the MRI prediction model. Eighty-nine patients were retrospectively enrolled to determine its prognostic significance. MRI parameters (relative enhancement, ratio of the apparent diffusion coefficient value of tumoral region to peritumoral region [rADC], T1 value) correlated significantly with the immunocyte-infiltration counts (leukocytes, T help cells, PD1+Tc cells, B lymphocytes). rADC differed significantly between high and low immunocyte-infiltration groups (1.47 ± 0.36 vs 1.09 ± 0.25, P = 0.009). The area under the curve of the MRI model was 0.787 (95% confidence interval 0.587-0.987). Based on the MRI model, the recurrence-free time was longer in the high immunocyte-infiltration group than in the low immunocyte-infiltration group (P = 0.026). Conclusions: MRI is a non-invasive method for assessing the IME and immunocyte-infiltration subtypes, and predicting prognosis in post-operative HBV-HCC patients.

Predicting One-year Recurrence of HCC based on Gadoxetic Acid-enhanced MRI by Machine Learning Models.

OBJECTIVE: Accurate prediction of recurrence risk after resction in patients with Hepatocellular Carcinoma (HCC) may help to individualize therapy strategies. This study aimed to develop machine learning models based on preoperative clinical factors and multiparameter Magnetic Resonance Imaging (MRI) characteristics to predict the 1-year recurrence after HCC resection. METHODS: Eighty-two patients with single HCC who underwent surgery were retrospectively analyzed. All patients underwent preoperative gadoxetic acidenhanced MRI examination. Preoperative clinical factors and MRI characteristics were collected for feature selection. Least Absolute Shrinkage and Selection Operator (LASSO) was applied to select the optimal features for predicting postoperative 1-year recurrence of HCC. Four machine learning algorithms, Multilayer Perception (MLP), random forest, support vector machine, and k-nearest neighbor, were used to construct the predictive models based on the selected features. A Receiver Operating Characteristic (ROC) curve was used to assess the performance of each model. RESULTS: Among the enrolled patients, 32 patients experienced recurrences within one year, while 50 did not. Tumor size, peritumoral hypointensity, decreasing ratio of liver parenchyma T1 value (ΔT1), and α-fetoprotein (AFP) levels were selected by using LASSO to develop the machine learning models. The area under the curve (AUC) of each model exceeded 0.72. Among the models, the MLP model showed the best performance with an AUC, accuracy, sensitivity, and specificity of 0.813, 0.742, 0.570, and 0.853, respectively. CONCLUSION: Machine learning models can accurately predict postoperative 1-year recurrence in patients with HCC, which may help to provide individualized treatment.

Deep Learning Combined with Radiologist's Intervention Achieves Accurate Segmentation of Hepatocellular Carcinoma in Dual-Phase Magnetic Resonance Images.

Purpose: Segmentation of hepatocellular carcinoma (HCC) is crucial; however, manual segmentation is subjective and time-consuming. Accurate and automatic lesion contouring for HCC is desirable in clinical practice. In response to this need, our study introduced a segmentation approach for HCC combining deep convolutional neural networks (DCNNs) and radiologist intervention in magnetic resonance imaging (MRI). We sought to design a segmentation method with a deep learning method that automatically segments using manual location information for moderately experienced radiologists. In addition, we verified the viability of this method to assist radiologists in accurate and fast lesion segmentation. Method: In our study, we developed a semiautomatic approach for segmenting HCC using DCNN in conjunction with radiologist intervention in dual-phase gadolinium-ethoxybenzyl-diethylenetriamine penta-acetic acid- (Gd-EOB-DTPA-) enhanced MRI. We developed a DCNN and deep fusion network (DFN) trained on full-size images, namely, DCNN-F and DFN-F. Furthermore, DFN was applied to the image blocks containing tumor lesions that were roughly contoured by a radiologist with 10 years of experience in abdominal MRI, and this method was named DFN-R. Another radiologist with five years of experience (moderate experience) performed tumor lesion contouring for comparison with our proposed methods. The ground truth image was contoured by an experienced radiologist and reviewed by an independent experienced radiologist. Results: The mean DSC of DCNN-F, DFN-F, and DFN-R was 0.69 ± 0.20 (median, 0.72), 0.74 ± 0.21 (median, 0.77), and 0.83 ± 0.13 (median, 0.88), respectively. The mean DSC of the segmentation by the radiologist with moderate experience was 0.79 ± 0.11 (median, 0.83), which was lower than the performance of DFN-R. Conclusions: Deep learning using dual-phase MRI shows great potential for HCC lesion segmentation. The radiologist-aided semiautomated method (DFN-R) achieved improved performance compared to manual contouring by the radiologist with moderate experience, although the difference was not statistically significant.

Sixty-four-slice computed tomography angiography of perigastric veins with image fusion.

OBJECTIVE: The objective of this study was to assess the efficacy and clinical value of 64-slice computed tomography angiography (CTA) with image fusion for demonstrating the perigastric venous anatomy. METHODS: Twenty-six patients with gastric cancer underwent abdominal CTA examinations. Computed tomography angiography of stomach and perigastric veins and arteries were reconstructed and fused using volume-rendering technique. The inflow and courses of perigastric veins as well as the spatial relationship among the perigastric veins, arteries, and stomach were compared with surgery. RESULTS: Compared with surgical findings, the visualization rate of the 7 perigastric veins on CTA was 90.9% to 100%. There was a statistically significant decrease in number of short gastric veins identified on CTA compared with surgery (P = 0.004). There was no statistically significant difference between the 2 modalities in detecting other perigastric veins including the left gastric vein, right gastric vein, right gastroepiploic vein, left gastroepiploic vein, posterior gastric vein, and gastrocolic trunk (P = 0.317, P = 0.157, P = 1, P = 1, P = 0.317, P = 1, respectively). CONCLUSIONS: Sixty-four-slice CTA with image fusion clearly depicts most of perigastric veins and their relationship with the stomach and perigastric arteries. It can facilitate gastrectomy.

Harnessing dual-energy CT for glycogen quantification: a phantom analysis.

Background: Non-invasive glycogen quantification in vivo could provide crucial information on biological processes for glycogen storage disorder. Using dual-energy computed tomography (DECT), this study aimed to assess the viability of quantifying glycogen content in vitro. Methods: A fast kilovolt-peak switching DECT was used to scan a phantom containing 33 cylinders with different proportions of glycogen and iodine mixture at varying doses. The virtual glycogen concentration (VGC) was then measured using material composition images. Additionally, the correlations between VGC and nominal glycogen concentration (NGC) were evaluated using least-square linear regression, then the calibration curve was constructed. Quantitative estimation was performed by calculating the linearity, conversion factor (inverse of curve slope), stability, sensitivity (limit of detection/limit of quantification), repeatability (inter-class correlation coefficient), and variability (coefficient of variation). Results: In all conditions, excellent linear relationship between VGC and NGC were observed (P<0.001, coefficient of determination: 0.989-0.997; residual root-mean-square error of glycogen: 1.862-3.267 mg/mL). The estimated conversion factor from VGC to NGC was 3.068-3.222. In addition, no significant differences in curve slope were observed among different dose levels and iodine densities. The limit of detection and limit of quantification had respective ranges of 6.421-15.315 and 10.95-16.46 mg/mL. The data demonstrated excellent scan-repeat scan agreement (inter-class correlation coefficient, 0.977-0.991) and small variation (coefficient of variation, 0.1-0.2%). Conclusions: The pilot phantom analysis demonstrated the feasibility and efficacy of detecting and quantifying glycogen using DECT and provided good quantitative performance with significant stability and reproducibility/variability. Thus, in the future, DECT could be used as a convenient method for glycogen quantification to provide more reliable information for clinical decision-making.