A clinical-radiomics nomogram based on dual-layer spectral detector CT to predict cancer stage in pancreatic ductal adenocarcinoma.

BACKGROUND: This study aimed to evaluate the efficacy of radiomics signatures derived from polyenergetic images (PEIs) and virtual monoenergetic images (VMIs) obtained through dual-layer spectral detector CT (DLCT). Moreover, it sought to develop a clinical-radiomics nomogram based on DLCT for predicting cancer stage (early stage: stage I-II, advanced stage: stage III-IV) in pancreatic ductal adenocarcinoma (PDAC). METHODS: A total of 173 patients histopathologically diagnosed with PDAC and who underwent contrast-enhanced DLCT were enrolled in this study. Among them, 49 were in the early stage, and 124 were in the advanced stage. Patients were randomly categorized into training (n = 122) and test (n = 51) cohorts at a 7:3 ratio. Radiomics features were extracted from PEIs and 40-keV VMIs were reconstructed at both arterial and portal venous phases. Radiomics signatures were constructed based on both PEIs and 40-keV VMIs. A radiomics nomogram was developed by integrating the 40-keV VMI-based radiomics signature with selected clinical predictors. The performance of the nomogram was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curves analysis (DCA). RESULTS: The PEI-based radiomics signature demonstrated satisfactory diagnostic efficacy, with the areas under the ROC curves (AUCs) of 0.92 in both the training and test cohorts. The optimal radiomics signature was based on 40-keV VMIs, with AUCs of 0.96 and 0.94 in the training and test cohorts. The nomogram, which integrated a 40-keV VMI-based radiomics signature with two clinical parameters (tumour diameter and normalized iodine density at the portal venous phase), demonstrated promising calibration and discrimination in both the training and test cohorts (0.97 and 0.91, respectively). DCA indicated that the clinical-radiomics nomogram provided the most significant clinical benefit. CONCLUSIONS: The radiomics signature derived from 40-keV VMI and the clinical-radiomics nomogram based on DLCT both exhibited exceptional performance in distinguishing early from advanced stages in PDAC, aiding clinical decision-making for patients with this condition.

Is disease activity associated with social support and psychological distress in Crohn's disease patients? Results of a cross-sectional study in a Chinese hospital population.

OBJECTIVES: This study aims to assess the relative of social support and psychological distress in disease activity among patients with Crohn's disease (CD) in China, and explore whether sex moderates the relationship between disease activity and social support and psychological distress in CD. DESIGN: Our study has a cross-sectional design. SETTING: This was a single-centre study, which was conducted in Wuhan, China. PARTICIPANTS: A total of 184 patients with CD at Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were enrolled in this study; of these,162 patients were included in the final analysis. PRIMARY AND SECONDARY OUTCOME MEASURES: The main study outcome was the CD patients' clinical and questionnaire data. The association of disease activity, social support and psychological distress with patients with CD was also evaluated based on the collected data. RESULTS: A total of 162 patients with CD were enrolled. Compared with patients with CD in remission (CD-R), the patients with CD in activity (CD-A) had higher C reactive protein (CRP) (p=0.001), anaemia (p<0.001) and relapse rates in the last year (p<0.001). Independent samples t-tests indicated that the CD-A group reported lower Social Support Rating Scale scores and higher Symptom Checklist-90 scores than the CD-R group. Moreover, men with CD had lower somatisation (p=0.030) and anxiety (p=0.050) scores than women. In binary logistic regression models, the subjective support (beta=0.903, p=0.013), the clinical factors of CRP (beta=1.038, p=0.001) and psychological distress factors of anxiety (beta=1.443, p=0.008) and other (beta=1.235, p=0.042) were disease activity predictors. CONCLUSION: The findings highlight the importance of the psychological distress and social support factors that may play a role in CD patients' health. Interventions to address these issues should be part of management in CD.

Clinical-radiomics-based treatment decision support for KIT Exon 11 deletion in gastrointestinal stromal tumors: a multi-institutional retrospective study.

Objective: gastrointestinal stromal tumors (GISTs) with KIT exon 11 deletions have more malignant clinical outcomes. A radiomics model was constructed for the preoperative prediction of KIT exon 11 deletion in GISTs. Methods: Overall, 126 patients with GISTs who underwent preoperative enhanced CT were included. GISTs were manually segmented using ITK-SNAP in the arterial phase (AP) and portal venous phase (PVP) images of enhanced CT. Features were extracted using Anaconda (version 4.2.0) with PyRadiomics. Radiomics models were constructed by LASSO. The clinical-radiomics model (combined model) was constructed by combining the clinical model with the best diagnostic effective radiomics model. ROC curves were used to compare the diagnostic effectiveness of radiomics model, clinical model, and combined model. Diagnostic effectiveness among radiomics model, clinical model and combine model were analyzed in external cohort (n=57). Statistics were carried out using R 3.6.1. Results: The Radscore showed favorable diagnostic efficacy. Among all radiomics models, the AP-PVP radiomics model exhibited excellent performance in the training cohort, with an AUC of 0.787 (95% CI: 0.687-0.866), which was verified in the test cohort (AUC=0.775, 95% CI: 0.608-0.895). Clinical features were also analyzed. Among the radiomics, clinical and combined models, the combined model showed favorable diagnostic efficacy in the training (AUC=0.863) and test cohorts (AUC=0.851). The combined model yielded the largest AUC of 0.829 (95% CI, 0.621-0.950) for the external validation of the combined model. GIST patients could be divided into high or low risk subgroups of recurrence and mortality by the Radscore. Conclusion: The radiomics models based on enhanced CT for predicting KIT exon 11 deletion mutations have good diagnostic performance.

Differential diagnosis of adrenal adenomas and metastases using spectral parameters in dual-layer detector spectral CT.

OBJECTIVE: To assess the diagnostic value of spectral parameters in differentiating adrenal adenomas from metastases based on dual-layer detector spectral CT (DLSCT). MATERIALS AND METHODS: Patients with adenomas or metastases who underwent enhanced DLSCT of the adrenals were enrolled. The CT values of virtual non-contrast images (CTVNC), iodine density (ID) values, and Z-effective (Z-eff) values, the normalized iodine density (NID) values, slopes of spectral HU curves (s-SHC), and iodine-to-CTVNC ratios of the tumors were measured in each phase. Receiver operating characteristic (ROC) curves were used to compare the diagnostic values. RESULTS: Ninety-nine patients with 106 adrenal lesions (63 adenomas, 43 metastases) were included. In the venous phase, all spectral parameters were significantly different between adenomas and metastases (all p < 0.05). The combined spectral parameters showed a better diagnostic performance in the venous phase than in other phase (p < 0.05). The iodine-to-CTVNC value had a larger area under the ROC curve (AUC) than the other spectral parameters in the differential diagnosis of adenomas and metastases, with a diagnostic sensitivity and specificity of 74.4% and 91.9%, respectively. In the differential diagnosis of lipid-rich adenomas, lipid-poor adenomas and metastases, the CTVNC value and s-SHC value also had a larger AUC than the other spectral parameters, with a diagnostic sensitivity of 97.7%, 79.1% and specificity of 91.2%, 93.1%, respectively. CONCLUSION: On DLSCT, the combined spectral parameters in the venous phase could help better distinguish adrenal adenomas from metastases. The iodine-to-CTVNC, CTVNC and s-SHC values had the highest AUC values in differentiating adenomas, lipid-rich adenomas and lipid-poor adenomas from metastases, respectively.

Application of Intravoxel Incoherent Motion in the Evaluation of Hepatocellular Carcinoma after Transarterial Chemoembolization.

(1) Background: To assess the efficacy of the quantitative parameters of intravoxel incoherent motion (IVIM) diffusion-weighted imaging for hepatocellular carcinoma (HCC) diagnosis after transarterial chemoembolization (TACE). (2) Methods: Fifty HCC patients after TACE were included and underwent MRI. All of the patients were scanned with the IVIM-DWI sequence and underwent TACE retreatment within 1 week. Referring to digital subtraction angiography (DSA) and MR enhanced images, two readers measured the f, D, and D* values of the tumor active area (TAA), tumor necrotic area (TNA), and adjacent normal hepatic parenchyma (ANHP). Then, the distinctions of the TAA, TNA, and ANHP were compared and we analyzed the differential diagnosis of the parameters in three tissues. (3) Results: For values of f and D, there were significant differences between any of the TAA, TNA, and ANHP (p < 0.05). The values of f and D were the best indicators for identifying the TAA and TNA, with AUC values of 0.959 and 0.955, respectively. The values of f and D performed well for distinguishing TAA from ANHP, with AUC values of 0.835 and 0.753, respectively. (4) Conclusions: Quantitative IVIM-DWI was effective for evaluating tumor viability in HCC patients treated with TACE and may be helpful for non-invasive monitoring of the tumor viability.

The Effects of Radiotherapy on Pancreatic Ductal Adenocarcinoma in Patients with Liver Metastases.

BACKGROUND: While radiotherapy has been studied in the treatment of locally advanced pancreatic ductal adenocarcinoma (PDAC), few studies have analyzed the effects of radiotherapy on PDAC in patients with liver metastases. This study aimed to determine whether PDAC patients with liver metastases have improved survival after radiotherapy treatment. METHODS: The data of 8535 patients who were diagnosed with PDAC with liver metastases between 2010 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Survival analysis and Cox proportional hazards regression analysis of cancer-specific mortality and overall survival were performed, and propensity score matching (PSM) was used to reduce selection bias. RESULTS: After PSM, the median overall survival (mOS) and median cancer-specific survival (mCSS) in the radiotherapy group were longer than those in the nonradiotherapy group (OS: 6 months vs. 4 months; mCSS: 6 months vs. 5 months, both p < 0.05), respectively. The multivariate analysis showed that cancer-specific mortality rates were higher in the nonradiotherapy group than in the radiotherapy group (HR: 1.174, 95% CI: 1.035-1.333, p = 0.013). The Cox regression analysis according to subgroups showed that the survival benefits (OS and CSS) of radiotherapy were more significant in patients with tumor sizes greater than 4 cm (both p < 0.05). CONCLUSIONS: PDAC patients with liver metastases, particularly those with tumor sizes greater than 4 cm, have improved cancer-specific survival (CSS) rates after receiving radiotherapy.

The role of gadoxetic acid-enhanced MRI features for predicting microvascular invasion in patients with hepatocellular carcinoma.

OBJECTIVE: To evaluate the predictive value of gadoxetic acid-enhanced MRI features (focused on Liver Imaging Reporting and Data System (LI-RADS) v2018 features and non-LI-RADS imaging features) for microvascular invasion (MVI) of hepatocellular carcinoma (HCC). METHODS: From October 2018 to December 2020, 134 patients who underwent gadoxetic acid-enhanced MRI with a pathological diagnosis of HCC after hepatectomy were enrolled in this retrospective study. Two radiologists assessed the pre-hepatectomy LI-RADS v2018 imaging features and non-LI-RADS features to identify independent predictors of MVI of HCC with a logistic regression model. RESULTS: Four MRI features were found to be independent predictors of MVI: corona enhancement [odds ratio (OR) 5.787; 95% confidence interval (CI) 1.180, 28.369; p = 0.030], mosaic architecture (OR 7.097; 95% CI 1.299, 38.783; p = 0.024), nonsmooth tumor margin (OR 13.131; 95% CI 3.950, 43.649; p < 0.001), and peritumoral hypointensity on hepatobiliary phase (HBP) (OR 33.123; 95% CI 2.897, 378.688; p = 0.005). When one of four imaging features was present, the sensitivity was 93.2% (41/44), and the specificity was 71.1% (64/90). CONCLUSION: The four imaging features including corona enhancement, mosaic architecture, nonsmooth tumor margin, and peritumoral hypointensity on HBP can be used as preoperative imaging biomarkers for predicting MVI in patients at high risk for HCC. When one of the four imaging features is present, MVI can be predicted with a sensitivity > 90%.

Early Assessment of Response to Radiofrequency Ablation With CT Perfusion Imaging in Rabbit VX2 Liver Tumor Model.

OBJECTIVES: To discriminate viable tumors from benign periablational enhancement (BPE) in early stage after radiofrequency ablation (RFA) is a major confounding problem. The goal of this study is to evaluate quantitative assessment and diagnostic value of CT perfusion between viable tumors and BPE after RFA in the rabbit liver VX2 tumor model, with pathological results as the standard. METHODS: Twenty-eight VX2 liver tumors were treated with RFA, on days 1, 3, 7, and 14, seven rabbits were randomly chosen for CT perfusion and performed pathology examinations immediately. The perfusion parameters along with the profile of time-density curves (TDCs) and pseudo-color images of the parameters were observed in both BPE and viable tumors, then compared with the pathology results. The perfusion parameters included blood flow (BF), blood volume (BV), time to peak (TTP), permeability (P), arterial liver perfusion (ALP), portal venous perfusion (PVP) and hepatic perfusion index (HPI). RESULTS: A total of 26/28 rabbits successfully underwent CT perfusion, while 6/26 lesions were confirmed to be viable tumors. The TDCs of BPE were mainly speed-up platform curves (15/26), while the viable tumors showed mainly speed-up speed-down (3/6) and speed-up platform (2/6) curves. The PVP values were significantly higher, and the HPI values were significantly lower for BPE at all time points than viable tumors (P < 0.05). Both of PVP value and HPI value have high efficiency for the differential diagnosis of the viable tumors and BPE at each time point. These characteristics of CT perfusion parameters were consistent with pathological changes. CONCLUSIONS: The TDCs, PVP and HPI have the potential to indicate BPE and viable tumors effectively early after RFA treatment, the results were highly consistent with pathology. CT perfusion has advantages with great efficacy in monitoring the therapeutic effect early after RFA treatment.

Quantitative dual-energy CT for evaluating hepatocellular carcinoma after transarterial chemoembolization.

We aimed to investigate the role of the quantitative parameters of dual-energy computed tomography (DECT) in evaluating patients with hepatocellular carcinoma (HCC) treated by transarterial chemoembolization (TACE). We retrospectively identified 80 HCC patients (mean age, 56 years; 61 men) treated by TACE who received contrast-enhanced DECT and were retreated by TACE within 7 days between November 2018 and December 2019. Taking digital subtraction angiography (DSA) and CT images as reference standard, two readers measured and calculated the values of normalized iodine concentration at arterial phase (NICAP), normalized iodine concentration at portal venous phase (NICPP), iodine concentration difference (ICD), arterial iodine fraction (AIF) and slope of the spectral Hounsfield unit curve (λHu) by placing matched regions of interests (ROIs) within the tumor active area (TAA), adjacent normal hepatic parenchyma (ANHP) and tumor necrotic area (TNA). Differences between the parameters were analyzed by the Kruskal-Wallis H test. Receiver operating characteristic analysis of the parameters performance in differentiating the three tissues types was performed. AIF exhibited a good performance in distinguishing TAA (0.93 ± 0.31) and ANHP (0.18 ± 0.14), the areas under the receiver operating characteristic curve (AUC) was 0.989, while the λHu exhibited an excellent performance in distinguishing TAA (3.32 ± 1.24) and TNA (0.29 ± 0.27), with an AUC of 1.000. In conclusion, quantitative DECT can be effectively used to evaluate the tumor viability in HCC patients treated by TACE.

Relationship between pancreatic parenchyma loss and early postoperative hyperglycemia in patients with benign pancreatic diseases.

OBJECTIVE: To evaluate the relationship between pancreatic parenchyma loss and early postoperative hyperglycemia in patients with benign pancreatic diseases. METHODS: A total of 171 patients with benign pancreatic tumors or chronic pancreatitis, whose preoperative fasting blood glucose (FBG) was normal and who underwent partial pancreatectomy were reviewed. The pancreatic volume was measured by CT imaging before and after the operation. According to their different pancreatic resection volume (PRV), 171 patients were divided into five groups: < 30%, 30%-39%, 40%-49%, 50%-59%, and ≥ 60%. The correlation between the PRV and postoperative FBG was investigated. According to the postoperative FBG value, the patients were divided into a hyperglycemia group (HG) and nonhyperglycemia group (non-HG) to explore the best cutoff value of the PRV between the two groups. RESULTS: There were significant differences in the postoperative FBG among the five groups (PRV < 30%, 30%-39%, 40%-49%, 50%-59%, and ≥ 60%). The PRV was positively correlated with postoperative FBG in the benign tumor group and chronic pancreatitis group (R = 0.727 and 0.651, respectively). ROC curve analysis showed that the best cutoff value of the PRV between the HG (n = 84) and non-HG (n = 87) was 39.95% with an AUC = 0.898; the sensitivity was 89.29%, and the specificity was 82.76%. CONCLUSION: There was a linear positive correlation between the postoperative FBG level and PRV. Patients with a PRV ≥ 40% are more likely to develop early postoperative hyperglycemia.

Development of a high-coverage metabolome relative quantitative method for large-scale sample analysis.

The development of quantitative metabolomics approaches for future standardized and translational applications has become increasingly important. Data-independent targeted quantitative metabolomics (DITQM) is a newly proposed method providing ion pair information on 1324 metabolites. However, the quantification of more than 1000 metabolites in large sample sizes has still not been implemented. In this study, on the basis of the DITQM concept, scheduled multiple reaction monitoring (MRM) methods for both high-abundant and low-abundant metabolites were established to broaden the quantification coverage, and an open-source program "Quanter_1.0" was coded to facilitate efficient data handling. Our results demonstrated that 1015 metabolites in human plasma met the quantitative requirements and could be relatively determined in an effective manner. The method was then applied to a large-scale sample study of lung cancer consisting of three distinct analytical batches. It was obvious that data quality that originated from quantitative metabolomics was improved, with substantially lower intra- and inter-batch data variation, resulting in a more effective multivariate statistical model. Finally, 26 potential biomarkers of lung cancer were discovered. Collectively, our approach provides a promising tool for quantitative metabolomics research involving large-scale sample sizes and clinical application.

Biotransformation-based metabolomics profiling method for determining and quantitating cancer-related metabolites.

The discovery and identification of reliable disease biomarkers and relevant disrupted metabolic pathways is still a major challenge in metabolomics. Here, we proposed a biotransformation-based metabolomics profiling method to identify reliable disease biomarkers by simultaneous quantitation and qualification of cancer-related metabolites and their metabolic pathways via liquid chromatography-tandem mass spectrometry (LC-MS/MS). The approach was based on selecting a subset of known cancer-related metabolites from our previous metabolomics work, cancer research literature and biological significance. The metabolic profiling of pathway-related metabolites was developed by predicted multiple reaction monitoring (MRM) of ion pairs based on their chemical structures and biotransformation. Then, a high-throughput quantitative method was established. Overall, this approach enables the sensitive and accurate detection of cancer-related metabolites and the identification of other relevant metabolites, which facilitates better data quality and in-depth investigation of dysregulated metabolic pathways. As a proof of concept, the approach was applied to a small-cell lung cancer (SCLC) study. The results showed that 43 metabolites were significantly changed, and arginine metabolism was apparently disturbed, which proved the proposed approach could be a powerful tool for discovering reliable disease biomarkers and aberrant metabolic pathways.

Development of simultaneous targeted metabolite quantification and untargeted metabolomics strategy using dual-column liquid chromatography coupled with tandem mass spectrometry.

Targeted quantification and untargeted global profiling are the two mainstream approaches, a merging of which could provide enhanced analytical potential in metabolomics research. Here, a simultaneous targeted quantification and untargeted metabolomics (STQUM) strategy was developed for more efficient, accurate and comprehensive metabolomics research by using ultra-high-performance liquid chromatography coupled with high-resolution tandem mass spectrometry (UPLC-HRMS/MS). First, we selected 110 cancer-related metabolites as targets and established a dual LC sequential separation method for simultaneous analysis of strong and weak polar metabolites. In order to achieve efficient acquisition for synchronous qualitative and quantitative analysis, high-resolution, data-dependent parallel reaction monitoring (PRM) method and data-independent all ion fragmentation (AIF) method were established. Their performance in targeted confirmation and quantification, and untargeted analysis were systematically investigated and assessed. In total, 78 metabolites were confidently confirmed in positive ion mode in both PRM and AIF assays, in which 73 metabolites can be accurately quantified. In addition, simultaneously untargeted profiling of 4651 features of high reliability and validity were achieved. Both AIF and PRM methods revealed high confidence, sensitivity and accuracy. In the STQUM approach, another 15 metabolites could be accurately quantified in negative ion mode. The method offers a new perspective for merging the hypothesis-based targeted quantitative validation and untargeted biomarkers discovery in one run for improved analysis efficiency and integrity.

A sensitive and rapid HPLC-MS/MS method for the quantitative determination of trace amount of bromocriptine in small clinical prolactinoma tissue.

Usually, insufficient intratumoral concentration of therapeutic drugs is one of the reasons for tumor treatment failure. However, little is known about intratumoral distribution of bromocriptine in non-responding prolactinomas because of extremely low drug concentration and small prolactinoma tissue samples. In this study, a sensitive, rapid and high-throughput quantitative bioanalytical method has been established by using high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) for the determination of bromocriptine at trace level in human prolactinoma tissue. As little as 20 mg (wet weight) tissue sample was required and total analysis time was 6 min in this method. The assay quantifies over a linear range of 50 fg/mg to 5 pg/mg, and has a 25 fg/mg limit of detection at a signal/noise ratio of 3. This validated method was successfully used to quantitatively determine bromocriptine in clinical post-operative bromocriptine-sensitive and -resistant prolactinomas. The results revealed bromocriptine concentration in resistant prolactinomas (0.49-1.25 pg/mg) was significantly higher than that in sensitive prolactinomas (0.057-0.47 pg/mg). These results provided direct evidence to demonstrate the reseaon for failure of bromocriptine treatment in some patients with prolactinoma was "intrinsic" tumor (cell) resistence, rather than insufficient drug concentration in tumor tissue. Additionaly, this HPLC-MS/MS method has been shown to be suitable for bromocriptine analysis in small amount tissue sample and could be adapted for therapeutic drug monitoring of other clinical medicine.