Computed tomography radiogenomics: A potential tool for prediction of molecular subtypes in gastric stromal tumor.

BACKGROUND: Preoperative knowledge of mutational status of gastrointestinal stromal tumors (GISTs) is essential to guide the individualized precision therapy. AIM: To develop a combined model that integrates clinical and contrast-enhanced computed tomography (CE-CT) features to predict gastric GISTs with specific genetic mutations, namely KIT exon 11 mutations or KIT exon 11 codons 557-558 deletions. METHODS: A total of 231 GIST patients with definitive genetic phenotypes were divided into a training dataset and a validation dataset in a 7:3 ratio. The models were constructed using selected clinical features, conventional CT features, and radiomics features extracted from abdominal CE-CT images. Three models were developed: ModelCT sign, modelCT sign + rad, and model CTsign + rad + clinic. The diagnostic performance of these models was evaluated using receiver operating characteristic (ROC) curve analysis and the Delong test. RESULTS: The ROC analyses revealed that in the training cohort, the area under the curve (AUC) values for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic for predicting KIT exon 11 mutation were 0.743, 0.818, and 0.915, respectively. In the validation cohort, the AUC values for the same models were 0.670, 0.781, and 0.811, respectively. For predicting KIT exon 11 codons 557-558 deletions, the AUC values in the training cohort were 0.667, 0.842, and 0.720 for modelCT sign, modelCT sign + rad, and modelCT sign + rad + clinic, respectively. In the validation cohort, the AUC values for the same models were 0.610, 0.782, and 0.795, respectively. Based on the decision curve analysis, it was determined that the modelCT sign + rad + clinic had clinical significance and utility. CONCLUSION: Our findings demonstrate that the combined modelCT sign + rad + clinic effectively distinguishes GISTs with KIT exon 11 mutation and KIT exon 11 codons 557-558 deletions. This combined model has the potential to be valuable in assessing the genotype of GISTs.

Multi-nuclear magnetic resonance spectroscopy: state of the art and future directions.

With the development of heteronuclear fluorine, sodium, phosphorus, and other probes and imaging technologies as well as the optimization of magnetic resonance imaging (MRI) equipment and sequences, multi-nuclear magnetic resonance (multi-NMR) has enabled localize molecular activities in vivo that are central to a variety of diseases, including cardiovascular disease, neurodegenerative pathologies, metabolic diseases, kidney, and tumor, to shift from the traditional morphological imaging to the molecular imaging, precision diagnosis, and treatment mode. However, due to the low natural abundance and low gyromagnetic ratios, the clinical application of multi-NMR has been hampered. Several techniques have been developed to amplify the NMR sensitivity such as the dynamic nuclear polarization, spin-exchange optical pumping, and brute-force polarization. Meanwhile, a wide range of nuclei can be hyperpolarized, such as 2H, 3He, 13C, 15 N, 31P, and 129Xe. The signal can be increased and allows real-time observation of biological perfusion, metabolite transport, and metabolic reactions in vivo, overcoming the disadvantages of conventional magnetic resonance of low sensitivity. HP-NMR imaging of different nuclear substrates provides a unique opportunity and invention to map the metabolic changes in various organs without invasive procedures. This review aims to focus on the recent applications of multi-NMR technology not only in a range of preliminary animal experiments but also in various disease spectrum in human. Furthermore, we will discuss the future challenges and opportunities of this multi-NMR from a clinical perspective, in the hope of truly bridging the gap between cutting-edge molecular biology and clinical applications.

Radiomics signature: A potential biomarker for ß-arrestin1 phosphorylation prediction in hepatocellular carcinoma.

BACKGROUND: The phosphorylation status of ß-arrestin1 influences its function as a signal strongly related to sorafenib resistance. This retrospective study aimed to develop and validate radiomics-based models for predicting ß-arrestin1 phosphorylation in hepatocellular carcinoma (HCC) using whole-lesion radiomics and visual imaging features on preoperative contrast-enhanced computed tomography (CT) images. AIM: To develop and validate radiomics-based models for predicting ß-arrestin1 phosphorylation in HCC using radiomics with contrast-enhanced CT. METHODS: Ninety-nine HCC patients (training cohort: n = 69; validation cohort: n = 30) receiving systemic sorafenib treatment after surgery were enrolled in this retrospective study. Three-dimensional whole-lesion regions of interest were manually delineated along the tumor margins on portal venous CT images. Radiomics features were generated and selected to build a radiomics score using logistic regression analysis. Imaging features were evaluated by two radiologists independently. All these features were combined to establish clinico-radiological (CR) and clinico-radiological-radiomics (CRR) models by using multivariable logistic regression analysis. The diagnostic performance and clinical usefulness of the models were measured by receiver operating characteristic and decision curves, and the area under the curve (AUC) was determined. Their association with prognosis was evaluated using the Kaplan-Meier method. RESULTS: Four radiomics features were selected to construct the radiomics score. In the multivariate analysis, alanine aminotransferase level, tumor size and tumor margin on portal venous phase images were found to be significant independent factors for predicting ß-arrestin1 phosphorylation-positive HCC and were included in the CR model. The CRR model integrating the radiomics score with clinico-radiological risk factors showed better discriminative performance (AUC = 0.898, 95%CI, 0.820 to 0.977) than the CR model (AUC = 0.794, 95%CI, 0.686 to 0.901; P = 0.011), with increased clinical usefulness confirmed in both the training and validation cohorts using decision curve analysis. The risk of ß-arrestin1 phosphorylation predicted by the CRR model was significantly associated with overall survival in the training and validation cohorts (log-rank test, P < 0.05). CONCLUSION: The radiomics signature is a reliable tool for evaluating ß-arrestin1 phosphorylation which has prognostic significance for HCC patients, providing the potential to better identify patients who would benefit from sorafenib treatment.

Computed Tomography-Based Texture Features for the Risk Stratification of Portal Hypertension and Prediction of Survival in Patients With Cirrhosis: A Preliminary Study.

Objective: Clinical evidence suggests that the risk stratification of portal hypertension (PH) plays a vital role in disease progression and patient outcomes. However, the gold standard for stratifying PH [portal vein pressure (PVP) measurement] is invasive and therefore not suitable for routine clinical practice. This study is aimed to stratify PH and predict patient outcomes using liver or spleen texture features based on computed tomography (CT) images non-invasively. Methods: A total of 114 patients with PH were included in this retrospective study and divided into high-risk PH (PVP ≥ 20 mm Hg, n = 57) or low-risk PH (PVP < 20 mm Hg, n = 57), a progression-free survival (PFS) group (n = 14), or a non-PFS group (n = 51) based on patients with rebleeding or death after the transjugular intrahepatic portosystemic shunt (TIPS) procedure. All patients underwent contrast-enhanced CT, and the laboratory data were recorded. Texture features of the liver or spleen were obtained by a manual drawing of the region of interest (ROI) and were performed in the portal venous phase. Logistic regression analysis was applied to select the significant features related to high-risk PH, and PFS-related features were determined by the Cox proportional hazards model and Kaplan-Meier analysis. Receiver operating characteristic (ROC) curves were used to test the diagnostic capacity of each feature. Results: Five texture features (one first-order feature from the liver and four wavelet features from the spleen) and the international normalized ratio (INR) were identified as statistically significant for stratifying PH (p < 0.05). The best performance was achieved by the spleen-derived feature of wavelet.LLH_ngtdm_Busyness, with an AUC of 0.72. The only log.sigma.3.0.mm.3D_firstorder_RobustMeanAbsoluteDeviation feature from the liver was associated with PFS with a C-index of 0.72 (95% CI 0.566-0.885), which could stratify patients with PH into high- or low-risk groups. The 1-, 2-, and 3-year survival probabilities were 66.7, 50, and 33.3% for the high-risk group and 93.2, 91.5, and 84.4% for the low-risk group, respectively (p < 0.05). Conclusion: CT-based texture features from the liver or spleen may have the potential to stratify PH and predict patient survival.

Preoperative prediction of gastrointestinal stromal tumors with high Ki-67 proliferation index based on CT features.

BACKGROUND: To determine whether preoperative computed tomography (CT) features can be used for the prediction of gastrointestinal stromal tumors (GISTs) with a high Ki-67 proliferation index (Ki-67 PI). METHODS: A total of 198 patients with surgically and pathologically proven GISTs were retrospectively included. All GISTs were divided into a low Ki-67 PI group (<10%) and a high Ki-67 PI group (≥10%). All imaging features were blindly interpreted by two radiologists. Receiver operating characteristic (ROC) curve analyses were conducted to evaluate the predictive performance of the imaging features. RESULTS: Imaging features were found to be significantly different between the low and the high Ki-67 PI groups (P<0.05). Wall thickness of necrosis showed the highest predictive ability, with an area under the curve (AUC) of 0.838 [95% confidence interval (CI): 0.627-0.957], followed by necrosis, necrosis degree, hyperenhancement of the overlying mucosa (HYOM), and long diameter (LD) (AUC >0.7, P<0.05). HYOM was the strongest predictive feature for the high Ki-67 PI GISTs group, with an odds ratio (OR) value of 30.037 (95% CI: 5.707-158.106). CONCLUSIONS: Imaging features, including the presence of necrosis, high necrosis degree, thick wall of necrosis, and HYOM were significant predictive indicators for the high Ki-67 PI GISTs group.

Gastrointestinal stromal tumors: associations between contrast-enhanced CT images and KIT exon 11 gene mutation.

BACKGROUND: Mutation screening for gastrointestinal stromal tumor (GIST) is crucial and the c kit gene (KIT) exon 11 mutation is the most common type. This study aimed to explore the associations between GIST with KIT exon 11 mutation and contrast-enhanced computed tomography (CT) images. METHODS: Pathologically proven GISTs with definitive genotype testing results in our hospital were retrospectively included. Abdominal contrast-enhanced CT images were analyzed. Conventional CT image features and radiomic features were recorded and extracted to build the following models: model [CT], model [radiomic + clinic] and model [CT + radiomic + clinic]. The diagnostic performances of GISTs with KIT exon 11 mutation and KIT exon 11 deletion involving codons 557-558 were evaluated. RESULTS: In total, 327 GISTs (255 with KIT exon 11 mutation, and 73 with KIT exon 11 mutation deletion involving codons 557-558) were included. Significant CT features were found for GISTs with KIT exon 11 mutation. The area under curves (AUCs) of the models for KIT exon 11 mutation were 0.7158, 0.7530, and 0.8375 in the training cohort, and 0.6777, 0.7349, and 0.8105 in validation cohort, respectively. The AUCs of the models for KIT exon 11 mutation deletion involving codons 557-558 were 0.7155, 8621, and 0.8691 in the training cohort, and 0.7099, 0.8355, and 0.8488 in the validation cohort, respectively. The model [CT + radiomic + clinic] demonstrated the highest AUCs for prediction of KIT exon 11 mutation and those with deletion involving codons 557-558 (P<0.05), respectively. The model [radiomic + clinic] showed higher diagnostic performance than model [CT] significantly. CONCLUSIONS: Our results demonstrated the associations between GIST with KIT exon 11 mutation and contrast-enhanced CT images. We found combing conventional image analysis and texture analysis is a useful tool to distinguish GIST with KIT exon 11 mutation. CT radiogenomics exhibited good application potential in predict the KIT exon 11 mutation of GIST.

CT-derived quantitative liver volumetric parameters for prediction of severe esophageal varices and the risk of first variceal hemorrhage.

PURPOSE: To assess whether CT (computed tomography)-derived quantitative parameters of liver lobe volume can predict severe esophageal varices (EV) and the risk of first varicealhemorrhage (FVH) in patients with liver cirrhosis. METHODS: A total of 217 endoscopically confirmed EV patients were included in this retrospective study and were divided into a low-risk EV group (mild-to-moderate EV, n = 83) and a high-risk EV group (severe EV, n = 134), a FVH group (n = 17) and a non-FVH group (n = 27), patients' clinical findings were recorded. The left, right, caudate lobe, total liver volume and the corresponding functional volume were measured respectively, and the ratio of caudate volume/total volume (CV/TV), caudate functional volume/total functional volume (CFV/TFV) were calculated. Univariate and multivariate logistic analysis were used to determine the independent factors and the receiver operating characteristic (ROC) curves were performed to evaluate the diagnostic performance. RESULTS: CV, CFV, CV/TV, CFV/TFV were significantly different in the EV severity study and FVH study (p < 0.05). Multivariate analysis indicated that CV/TV and ascites were independent predictive factors for severe EV, a predictive model combing those two factors revealed a satisfactory diagnostic performance (area under the curve (AUC), 0.853, 95 %CI 0.797-0.905). Furthermore, CV/TV and the presence of red color sign under endoscopy were found to be independent predictive factors for FVH, and the former showed a better discriminative performance than the latter (AUC, 0.851 vs 0.779). CONCLUSIONS: CT-derived quantitative parameters of CV, CFV, CV/TV, CFV/TFV may be used as an alternative to endoscopy in predicting severe varices and the risk of bleeding.

Insight into gastrointestinal heterotopic pancreas: imaging evaluation and differential diagnosis.

Heterotopic pancreas (HP) is an uncommon congenital abnormality in the developmental process of the pancreas, with gastrointestinal heterotopic pancreas (GHP) being the most common HP. The clinical manifestations of GHP may have variable patterns of presentation, dictated by both the anatomic location and the functional ability of the lesion. The most common imaging modality in detecting GHP is computed tomography (CT), while gastrointestinal barium fluoroscopy, endoscopic ultrasonography, and magnetic resonance imaging (MRI) are also applied. The density and enhancement patterns of GHP are consistent with histological classifications. GHP with a predominantly acinar tissue component manifests homogeneous and marked enhancement on CT images, whereas a predominantly ductal GHP presents heterogeneous and mild enhancement. On MRI, the appearance and signal intensity of GHP were paralleled to the normal pancreas on all sequences and were characterized by T1-weighted high signal and early marked enhancement. This article provides a comprehensive review of the histopathology, clinical manifestations, imaging features of various modalities, and differential diagnosis of GHP. It is hoped that this review will improve clinicians' knowledge of GHP and aid in accurate preoperative diagnosis, thereby reducing the misdiagnosis rate.

LI-RADS category 5 hepatocellular carcinoma: preoperative gadoxetic acid-enhanced MRI for early recurrence risk stratification after curative resection.

OBJECTIVES: To explore the role of preoperative gadoxetic acid-enhanced MRI in stratifying the risk of early recurrence in patients with LR-5 hepatocellular carcinoma (HCC) by LI-RADS v2018 after curative resection. METHODS: Between July 2015 and August 2018, this study evaluated consecutive treatment-naïve at-risk LR-5 HCC patients who underwent gadoxetic acid-enhanced MRI examination within 2 weeks before curative resection. The Cox regression analysis was performed to identify potential predictors of early recurrence. Disease-free survival (DFS) rates were analyzed and compared by using the Kaplan-Meier method and log-rank tests. RESULTS: Fifty-three of 103 (51.5%) patients experienced early recurrence. Three MRI findings were significantly associated with early recurrence: corona enhancement (hazard ratio [HR]: 2.116; p = 0.013), peritumoral hypointensity on hepatobiliary phase (HBP) (HR: 2.262; p = 0.007), and satellite nodule (HR: 2.777; p = 0.005). An additional risk factor was AFP level > 400 ng/mL (HR: 1.975; p = 0.016). Based on the number of MRI predictors, LR-5 HCC patients were stratified into three subgroups: LR-5a (60/103; no predictor), LR-5b (26/103; one predictor), and LR-5c (17/103; two or three predictors), with low, medium, and high risk of early recurrence, respectively. The 2-year DFS rate of LR-5a, LR-5b, and LR-5c patients was 65.0%, 38.5%, and 5.9%, respectively, while the corresponding median DFS was undefined, 17.1 months, and 5.1 months, respectively (p < 0.001). CONCLUSIONS: In at-risk LR-5 HCC patients, corona enhancement, peritumoral hypointensity on HBP, and satellite nodule could be used to preoperatively stratify the risk of early recurrence after hepatectomy. KEY POINTS: • Corona enhancement, peritumoral hypointensity on HBP, satellite nodule, and serum AFP level > 400 ng/mL were significant predictors of early recurrence in patients with LR-5 HCC after hepatectomy. • Based on the number of predictive MRI findings, LR-5 HCC patients could be preoperatively stratified into three subgroups: LR-5a, LR-5b, and LR-5c, with significantly different risk of early recurrence and disease-free survival. • Preoperative risk stratification is essential for the identification of patients at increased risk of postoperative early recurrence, which may contribute to risk-based personalized management for LR-5 HCC patients.

Use of computed tomography for distinguishing heterotopic pancreas from gastrointestinal stromal tumor and leiomyoma.

PURPOSE: To determine whether morphologic features and semiquantitative parameters of computed tomography (CT) could be used to distinguish heterotopic pancreas from gastrointestinal stromal tumor (GIST) and leiomyoma. METHODS: This retrospective study evaluated CT images of heterotopic pancreases (n = 28), GISTs (n = 57), and leiomyomas (n = 26) located in the upper gastrointestinal tract. Morphologic imaging features of lesions were analyzed, including location, contour, margin, attenuation, growth pattern, enhancement type, enhancement degree, enlarged vessels feeding or draining the mass, hyperenhancement of the overlying mucosa, low intralesional attenuation, calcification, and a duct-like structure. Semiquantitative parameters included long diameter (LD), short diameter (SD), LD/SD ratio, and lesion and aorta CT values during plain CT (Lp and Ap), arterial phase (La and Aa), and venous phase (Lv and Av). Diagnostic performance of these findings and parameters were evaluated by receiver operating characteristic (ROC) analysis. RESULTS: Morphologic CT findings (including lesion contour, margin, attenuation, growth pattern, enhancement type, and enhancement degree) and semiquantitative parameters except for LD/SD were demonstrated to be significant for differentiating heterotopic pancreas from GIST and leiomyoma (all P < 0.01). Of these, location, low intralesional attenuation, duct-like structure and LD, SD, Lv, and Sv values showed good diagnostic performance with the areas under curve (AUC) higher than 0.70. The presence of a duct-like structure demonstrated the best diagnostic ability with AUC of 0.929 [95% confidence interval (CI) 0.864-0.969], sensitivity of 5.7% (95% CI 67.3-96.0), and specificity of 100% (95% CI 95.7-100), respectively. When the three morphologic features (location, low intralesional attenuation, duct-like structure) were used in combination, the AUC was improved to 0.980 (95% CI 0.952-1). CONCLUSION: CT features, especially the morphologic features, could be used to differentiate heterotopic pancreas from GIST and leiomyoma in the upper gastrointestinal tract and, thus, provide a more accurate method for non-invasive preoperative diagnosis. Additionally, the presence of a duct-like structure demonstrated to be a reliable indicator for heterotopic pancreas among the morphologic and semiquantitative CT features.

Current and Potential Applications of Artificial Intelligence in Gastrointestinal Stromal Tumor Imaging.

The most common mesenchymal tumors are gastrointestinal stromal tumors (GISTs), which have malignant potential and can occur anywhere along the gastrointestinal system. Imaging methods are important and indispensable of GISTs in diagnosis, risk staging, therapy, and follow-up. The recommended imaging method for staging and follow-up is computed tomography (CT) according to current guidelines. Artificial intelligence (AI) applies and elaborates theses, procedures, modes, and utilization systems for simulating, enlarging, and stretching the intellectual capacity of humans. Recently, researchers have done a few studies to explore AI applications in GIST imaging. This article reviews the present AI studies in GISTs imaging, including preoperative diagnosis, risk stratification and prediction of prognosis, gene mutation, and targeted therapy response.

Primary isolated hepatic tuberculosis mimicking small hepatocellular carcinoma: A case report.

RATIONALE: Mycobacterium tuberculosis (TB) remains a serious threat in developing countries. Primary isolated hepatic tuberculosis is extremely rare. Because of its non-specific imaging features, noninvasive preoperative imaging diagnosis of isolated hepatic tuberculoma remains challenging. PATIENT CONCERNS: A 48-year-old man was admitted to our hospital due for suspected liver neoplasm during health examination. DIAGNOSES: The tests for blood, liver function, and tumor markers were within normal range. Preoperative ultrasonography (US) showed a hypoechoic lesion with a longitudinal diameter of 2.5 cm in segment six of liver. It exhibited early arterial phase hyperenhancement and late arterial phase rapid washout in contrast-enhanced US. It demonstrated hyperintensity in T2-weighted magnetic resonance imaging and partly restricted diffusion in diffusion-weighted imaging. For this nodule, the preoperative diagnosis was small hepatocellular carcinoma (HCC). INTERVENTIONS: Laparoscopic hepatectomy was performed. Intraoperative extensive adhesion in the abdominal cavity and liver was found. The lesion had undergone expansive growth. OUTCOMES: Microscopically, a granuloma with some necrosis was detected. With both acid-fast staining and TB fragment polymerase chain reaction showing positive results, TB was the final histology diagnosis. After surgery, the patient declined any anti-TB medication. During the follow-up, he had no symptoms. In the sixth month after surgery, he underwent an upper abdominal US. It showed no lesions in the liver. LESSONS: Because of non-specific imaging findings and non-specific symptoms, a diagnosis of isolated hepatic TB is difficult to make, especially for small lesions. A diagnosis of HCC should be made cautiously when small isolated lesions in the liver are encountered, especially in patients without a history of hepatitis and with negative tumor markers.

CT Manifestations and Clinical Characteristics of 1115 Patients with Coronavirus Disease 2019 (COVID-19): A Systematic Review and Meta-analysis.

RATIONALE AND OBJECTIVES: We aimed to assess the prevalence of significant computed tomographic(CT) manifestations and describe some notable features based on chest CT images, as well as the main clinical features of patients with coronavirus disease 2019(COVID-19). MATERIALS AND METHODS: A systematic literature search of PubMed, EMBASE, the Cochrane Library, and Web of Science was performed to identify studies assessing CT features, clinical, and laboratory results of COVID-19 patients. A single-arm meta-analysis was conducted to obtain the pooled prevalence and 95% confidence interval (95% CI). RESULTS: A total of 14 articles (including 1115 patients) based on chest CT images were retrieved. In the lesion patterns on chest CTs, we found that pure ground-glass opacities (GGO) (69%, 95% CI 58-80%), consolidation (47%, 35-60%) and "air bronchogram sign" (46%, 25-66%) were more common than the atypical lesion of "crazy-paving pattern" (15%, 8-22%). With regard to disease extent and involvement, 70% (95% CI 46-95%) of cases showed a location preference for the right lower lobe, 65% (58-73%) of patients presented with ≥3 lobes involvement, and meanwhile, 42% (32-53%) of patients had involvement of all five lobes, while 67% (55-78%) of patients showed a predominant peripheral distribution. An understanding of some important CT features might be helpful for medical surveillance and management. In terms of clinical features, muscle soreness (21%, 95% CI 15-26%) and diarrhea (7%, 4-10%) were minor symptoms compared to fever (80%, 74-87%) and cough (53%, 33-72%). CONCLUSION: Chest CT manifestations in patients with COVID-19, as well as its main clinical characteristics, might be helpful in disease evolution and management.

Identification of gastrointestinal stromal tumors from leiomyomas in the esophagogastric junction: A single-center review of 136 cases.

To identify significant clinical and CT features for the differentiation of gastrointestinal stromal tumors (GISTs) from leiomyomas in the esophagogastric junction (EGJ).One hundred thirty six patients with pathologically proven GISTs (n = 87) and leiomyomas (n = 49) in the EGJ were enrolled. And preoperative CT images were available in 73 GISTs cases and 34 leiomyoma cases. Two radiologists reviewed the CT images by consensus with regard to tumor size, shape, growth pattern, surface, enhancement pattern, enhancement degree, attention at each phasic image and the presence of surface ulcer, calcification, and intralesional low attention.Eight significant clinical and CT features were identified for differentiating GISTs from leiomyomas: older age (>46.5 years), tumor long diameter >4.5 cm, heterogeneous enhancement, high degree enhancement, mean CT attenuation >69.2 HU, presences of intralesional low attenuation and surface ulcer, absences of calcification (P < .05). On the receiver operating characteristic curve analysis, an optimal cutoff score of 3.5 was achieved for differentiating GISTs from leiomyomas with an AUC of 0.844 (sensitivity: 76.7%, specificity: 76.5%).older age (>46.5 years), tumor long diameter >4.5 cm, heterogeneous enhancement, high degree enhancement, mean CT attenuation >69.2 HU, presences of intralesional low attenuation and surface ulcer, absence of calcification are significant features highly suggestive of GISTs in differentiation from leiomyomas in the EGJ.

Gadobutrol Precedes Gd-DTPA in Abdominal Contrast-Enhanced MRA and MRI: A Prospective, Multicenter, Intraindividual Study.

Objective: To qualitatively and quantitatively compare the contrast-enhanced magnetic resonance angiography (MRA) and magnetic resonance imaging (MRI) in one-stop shop of abdominal imaging with Gadobutrol and Gd-DTPA at equimolar doses of gadolinium. Materials and Methods: This was a prospective designed, multiple center, intraindividual comparison study. All volunteers underwent Gadobutrol- and Gd-DTPA-enhanced MRA and MRI in one-stop shop. Qualitative analysis for large vessels and small vessels was performed by a three-point scale, while for minute small vessels, by a five-point scale. Quantitative analysis was performed for large vessels by signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). Visceral organ enhancements on the equilibrium phase were also analyzed. Wilcoxon matched-pair signed-rank tests were used to evaluate the qualitative and quantitative results. Results: 40 volunteers were enrolled. Qualitative analyses results for large vessels, small vessels, and minute small vessels of Gadobutrol and Gd-DTPA were 20.98 ± 2.11, 6.03 ± 1.03, and 3.41 ± 1.18 and 20.01 ± 2.18, 5.28 ± 1.67, and 2.61 ± 1.40, respectively. Wilcoxon signed-rank tests revealed Gadobutrol-enhanced MRA was superior to that of Gd-DTPA significantly for small vessels (p=0.028) and minute small vessels (p=0.007). For quantitative analysis of large vessels, no statistic difference was found. Gadobutrol-enhanced MRI had higher CNR of the liver (p=0.003), spleen (p=0.001), and pancreas (p=0.001) and higher SNR of spleen (p=0.009) than those of Gd-DTPA statistically. Conclusion: Our study proved Gadobutrol was superior to Gd-DTPA in qualitative analysis of CE-MRA and quantitative analysis of visceral organ enhancement on CE-MRI in abdomen of healthy volunteers. Gadobutrol may be more suitable for abdominal one-stop examination for CE-MRA and CE-MRI.