Dual-Energy CT Iodine Concentration to Evaluate Postoperative Pancreatic Fistula after Pancreatoduodenectomy

Prediction of postoperative pancreatic fistula based on multi-sequence MR imaging

OBJECTIVE

To investigate the value of conventional MRI sequences in predicting the occurrence of postoperative pancreatic fistula (POPF) in patients undergoing pancreaticoduodenectomy (PD).

METHODS

A total of 122 patients from August 2019 to April 2023 were enrolled. All patients underwent pancreatic histological evaluation, including fibrosis, fat deposition, and acinar cell atrophy. The preoperative image features of pancreas were obtained, including morphological features, pancreas-muscle signal intensity ratio, pancreatic fat fraction and multi-phase enhancement features. The patients were divided into two groups according to whether pancreatic fistula occurred after operation. The related risk factors of pancreatic fistula, the correlation between imaging and pathological changes were analyzed, and the value of preoperative imaging in predicting pancreatic fistula was evaluated.

RESULTS

Of the 122 patients, 23(18.9 %) developed POPF. Pathological score showed that there was a significant difference in pancreatic fat deposition between the two groups (P = 0.006), the fat deposition score was higher in the POPF group. Pancreatic fat deposition was the only independent risk factor for POPF(OR,1.933; P = 0.018). MRI showed that proton density fat fraction(PDFF) (P = 0.001), pancreas-to-aorta signal intensity ratio(P-A SI ratio) of equilibrium phase(P = 0.023) and delay phase(P = 0.020) had significant differences. PDFF was positively correlated with fat deposition(r = 0.404, P < 0.001), P-A SI ratio of equilibrium phase and delay phase were positively correlated with fibrosis(r = 0.313, P = 0.002; r = 0.315, P = 0.002, respectively). ROC analysis showed that PDFF had the best efficacy in predicting postoperative pancreatic fistula (AUROC = 0.810), better than P-A SI ratio of equilibrium phase(AUROC = 0.752) and delayed phase(AUROC = 0.766).

CONCLUSIONS

Pancreatic fat deposition is a high risk factor for POPF, PDFF can reflect fat deposition and predict POPF.

Dual-energy CT for predicting progression-free survival of locally advanced gastric cancer after gastrectomy: Insights into tumor angiogenesis

OBJECTIVES

To investigate preoperative dual-energy CT (DECT)-derived independent risk factors affecting progression-free survival (PFS) in patients with locally advanced gastric cancer (LAGC) undergoing gastrectomy, and to reveal the underlying histopathologic changes.

METHODS

This prospective study included patients who underwent preoperative DECT scan and gastrectomy. Clinical data, DECT-derived morphological characteristics and iodine-related parameters were comprehensively collected. Univariate and multivariate analyses were carried out to identify independent risk factors associated with PFS. The prognostic performance of various parameters was evaluated using the bootstrap-based consistency index (C-index) and time-dependent receiver operating characteristic (ROC) analysis. Kaplan-Meier curves were used to assess the differences in survival analysis. The histopathologic underpinnings of the DECT-based combined parameter for evaluating PFS were explored.

RESULTS

120 LAGC patients (63.3 ± 10.9 years; 94 men) were analyzed. Age, arterial enhancement fraction (AEF), serosal invasion, and tumor thickness were identified as preoperative independent risk factors affecting PFS (all p < 0.05). The combined parameters based on these risk factors achieved a C-index of 0.75, significantly or slightly superior to that of any single risk factor (all p < 0.05) or postoperative pathological staging (C-index, 0.67; p > 0.05). For predicting the 0.5-, 1- and 2-year PFS, the combined parameter had an area-under-the-curve (AUC) of 0.72, 0.77, and 0.74, respectively. PFS significantly differed between patients of high- and low-risks assessed with the combined parameter (p < 0.001). Histopathologically, the combined parameter was associated with tumor microvessel density (r = 0.31, p < 0.001).

CONCLUSION

The combination of DECT-derived morphological characteristics, iodine-related parameters, and clinical data helped accurately stratify PFS in LAGC before surgery and is associated with tumor angiogenesis.

CLINICAL RELEVANCE STATEMENT

Dual-energy CT was promising in the preoperative evaluation of the progression-free survival in LAGC patients after gastrectomy.

Thrombus iodine-based perviousness is associated with recanalisation and functional outcomes in endovascular thrombectomy

BACKGROUND

Dual-energy CT (DECT) provides several novel methods to assess thrombus perviousness. We aimed to evaluate whether the novel thrombus perviousness measured with DECT is associated with improved recanalisation and better functional outcomes in acute ischaemic stroke (AIS) patients with endovascular thrombectomy (EVT).

METHODS

108 AIS patients with middle cerebral artery occlusion who underwent DECT angiography on admission and received EVT treatment between April 2020 and September 2023 were retrospectively analysed. Thrombus attenuation increase (TAI) was evaluated on routine CT angiography and non-contrast CT, and DECT quantitative parameters of thrombus, including iodine concentration (IC) and normalised IC (NIC) were measured. Multivariable logistic regression analysis was used to evaluate the association of thrombus characteristics with arterial occlusive lesion scale and 90-day modified Rankin Scale.

RESULTS

NIC was significantly associated with successful recanalisation (OR 1.372 (95% CI 1.194 to 1.625); p<0.001) and good functional outcome (OR 1.252 (95% CI 1.114 to 1.446); p<0.001). NIC yielded higher performance, with area under curve (AUC) of 0.789 and 0.740, in the prediction of recanalisation and functional outcome than TAI (AUCs=0.635 and 0.592). Compared with low-level NIC thrombus, high-level NIC was associated with 11.4 and 15.4 times higher likelihood of successful recanalisation and good functional outcome. Moreover, NIC was a significant indicator to differentiate large artery atherosclerosis from cardioembolism stroke with high specificity and positive predictive value.

CONCLUSIONS

Higher DECT-derived NIC is associated with increased odds of successful recanalisation and good functional outcome for EVT patients, and it yielded higher prediction performance than TAI.

Prediction of the wall-invasion pattern of advanced gallbladder carcinoma using extracellular volume fraction

PURPOSE

This study aimed to evaluate the utility of extracellular volume (ECV) fraction for predicting wall-invasion patterns in advanced gallbladder carcinoma (GBCA).

MATERIALS AND METHODS

Patients who had surgically resected GBCA at a single institution were retrospectively evaluated. All patients underwent computed tomography (CT) before the surgery. Based on pathological examinations, the wall-invasion pattern of GBCA was classified into two groups: infiltrative growth (IG, n = 19) and destructive growth (DG, n = 11). ECV map was generated by inputting the patients' hematocrit values and subtraction algorithms using pre-contrast and equilibrium phase images. CT parameters were evaluated by two radiologists (Rad1 and Rad2). The Mann-Whitney U test was performed to identify significant CT parameters for differentiating between the two groups. The diagnostic ability was measured using receiver operating characteristic (ROC) curve analysis. Recurrence-free survival (RFS) was estimated using the Kaplan-Meier method, and differences between the two groups were compared using the log-rank test.

RESULTS

Thirty patients (mean age, 75.5 years; 20 men) were evaluated. Mean ECV fraction of the DG-type (Rad1, 34.5%; Rad2, 34.1%) was significantly higher than that of the IG-type (Rad1, 28.5%; Rad2, 28.8%) (p < 0.05). The ECV values of the two radiologists indicated that the areas under the ROC curves for differentiation between the two groups were Rad1, 0.91 and Rad2, 0.84 (p < 0.05). Medium RFS of the DG-type (970 days) was significantly shorter than that of the IG-type (2200 days) (p < 0.05).

CONCLUSION

ECV fraction demonstrates potential as the most valuable predictor of the DG type of GBCA, which has a higher recurrence rate compared with the IG type. However, further large-scale multi-center studies are required to validate these findings.

Dual-energy CT extracellular volume fraction predicts tumor collagen ratio and possibly survival for inoperable pancreatic cancer patients

OBJECTIVES

Tumor collagen is vital in chemotherapy resistance of pancreatic cancer (PC), but its non-invasive evaluation remains challenging. This study aims to investigate the association of variables derived from dual-energy CT with the collagen ratio (CR) of PC and to determine the prognostic value of CR in unresectable diseases.

MATERIALS AND METHODS

A total of 83 patients with resected PC and 71 patients with unresectable PC were enrolled. In the resected group, the correlation between the tumor CR and variables of dual-energy CT was analyzed. In the unresectable group, Cox regression analyses were conducted to investigate the prognostic value of dual-energy CT-predicted CR and other clinicoradiological indicators.

RESULTS

The patients with resected PC were divided into low and high-CR sets with a threshold of 55%. In the resected group, the extracellular volume fraction calculated by the iodine concentration (ECV_IC) was the only predictor of tumor CR according to univariate and multivariate analysis (hazard ratio [HR] (95% confidence interval [CI]):1.19 [1.03-1.37]). The correlation coefficient r was 0.26 (p = 0.02) between ECV_IC and specific CR values. In the training set of unresectable PC group, ECV_IC (HR (95% CI): 0.94 (0.89-0.99), p = 0.03) and contrast-enhanced pattern (CEP) (HR (95% CI): 3.20 (1.41-7.27), p = 0.01) were independent prognostic factors for overall survival. The nomogram model was constructed and showed a good performance.

CONCLUSION

The ECV_IC is a non-invasive indicator of tumor CR in PC. The ECV_IC and CEP have the potential to predict the prognosis of unresectable PC.

KEY POINTS

Question Non-invasive evaluation of tumor collagen, a vital determinant of chemotherapy resistance of pancreatic cancer, remains challenging. Findings Tumor collagen ratio can be noninvasively predicted by extracellular volume fraction based on iodine concentration. Clinical relevance The nomogram model composed of extracellular volume fraction and contrast-enhanced pattern can serve as an effective and convenient tool for stratifying the prognosis of patients with unresectable pancreatic cancer.

Evaluation of pancreatic iodine uptake and related influential factors in multiphase dual-energy CT

OBJECTIVES

To establish normative values and identify potential factors influencing pancreatic iodine uptake using dual-energy CT (DECT).

MATERIALS AND METHODS

This retrospective study included participants without pancreatic diseases undergoing DECT at two institutions with different platforms. Their protocols both included arterial phase (AP), portal venous phase (PP), and equilibrium phase (EP), defined as 35 s-40 s, 60 s-70 s, and 150 s-180 s after injection of contrast agent, respectively. Both iodine concentration (IC) and normalised IC (NIC) were measured. Demographic features, local measurements of the pancreas and visceral fat area (VFA) were considered as potential factors influencing iodine uptake using multivariate linear regression analyses.

RESULTS

A total of 562 participants (median age 58 years [interquartile range: 47-67], with 282 men) were evaluated. The mean IC differed significantly between two institutions (all p < 0.001) across three contrast-enhanced phases, while the mean NIC showed no significant differences (all p > 0.05). The mean values of NIC were 0.22 at AP, 0.43 at PP and 0.45 at EP. NICAP was independently affected by VFA (β = 0.362, p < 0.001), smoking (β = -0.240, p = 0.001), and type-II diabetes (β = -0.449, p < 0.001); NICPP by VFA (β = -0.301, p = 0.017) and smoking (β = -0.291, p < 0.001); and NICEP by smoking (β = -0.154, p = 0.10) and alcohol consumption (β = -0.350, p < 0.001) with statistical power values over 0.81.

CONCLUSION

NIC values were consistent across institutions. Abdominal obesity, smoking, alcohol consumption, and diabetes are independent factors influencing pancreatic iodine uptake.

CLINICAL RELEVANCE STATEMENT

This study has provided reference normative values, influential factors and effective normalisation methods of pancreatic iodine uptake in multiphase dual-energy CT for future studies in this area as a new biological marker.

KEY POINTS

Evaluation of pancreatic iodine uptake measured by dual-energy CT is a promising method for future studies. Abdominal obesity, smoking, alcohol consumption, diabetes, and sex are independent factors influencing pancreatic iodine uptake. Utility of normalised iodine concentration is necessary to ensure the consistency across different institutions.

Extracellular volume fraction derived from dual-energy CT: a potential predictor for acute pancreatitis after pancreatoduodenectomy

OBJECTIVES

To investigate the value of extracellular volume (ECV) fraction and fat fraction (FF) derived from dual- energy CT (DECT) for predicting postpancreatectomy acute pancreatitis (PPAP) after pancreatoduodenectomy (PD).

METHODS

This retrospective study included patients who underwent DECT and PD between April 2022 and September 2022. PPAP was determined according to the International Study Group for Pancreatic Surgery (ISGPS) definition. Iodine concentration (IC) and FF of the pancreatic parenchyma were measured on preoperative DECT. The ECV fraction was calculated from iodine map images of the equilibrium phase. The independent predictors for PPAP were assessed by univariate and multivariable logistic regression analysis and receiver operating characteristic (ROC) curve analysis.

RESULTS

Sixty-nine patients were retrospectively enrolled (median age, 60 years; interquartile range, 55-70 years; 47 men). Of these, nine patients (13.0%) developed PPAP. These patients had lower portal venous phase IC, equilibrium phase IC, FF, and ECV fraction, and higher pancreatic parenchymal-to-portal venous phase IC ratio and pancreatic parenchymal-to-equilibrium phase IC ratio, compared with patients without PPAP. After multivariable analysis, ECV fraction was independently associated with PPAP (odd ratio [OR], 0.87; 95% confidence interval [CI]: 0.79, 0.96; p < 0.001), with an area under the curve (AUC) of 0.839 (sensitivity 100.0%, specificity 58.3%).

CONCLUSIONS

A lower ECV fraction is independently associated with the occurrence of PPAP after PD. ECV fraction may serve as a potential predictor for PPAP after PD.

CLINICAL RELEVANCE STATEMENT

DECT-derived ECV fraction of pancreatic parenchyma is a promising biomarker for surgeons to preoperatively identify patients with higher risk for postpancreatectomy acute pancreatitis after PD and offer selective perioperative management.

KEY POINTS

PPAP is a complication of pancreatic surgery, early identification of higher-risk patients allows for risk mitigation. Lower DECT-derived ECV fraction was independently associated with the occurrence of PPAP after PD. DECT aids in preoperative PAPP risk stratification, allowing for appropriate treatment to minimize complications.

Computed tomography numbers obtained for varying iodine contrast concentrations by different-generation dual-energy computed tomography scanners

We compared the computed tomography (CT) numbers from monochromatic images obtained using the first-generation (Discovery CT750 HD: GE Healthcare, Milwaukee, WI) and second-generation (Revolution CT: GE HealthCare) dual-energy CT (first and second DECT) scanners in phantom and clinical studies. In a polypropylene phantom, eight polypropylene tubes containing iodine at various concentrations (0.5, 1, 2, 5, 10, 12, 20, 30 mg I per ml) were arranged in an outer circle. The iodine densities and CT numbers obtained after imaging with different-generation DECT scanners were analyzed. The CT numbers from images obtained from 61 consecutive patients with aortic disease who underwent CT with different-generation DECT scanners were compared during the arterial and delayed phases. The iodine concentration obtained from second DECT was more accurate than that from the first DECT in the phantom study. A significantly higher contrast enhancement was observed with the second DECT compared with the first DECT during the arterial phase in the clinical study. Contrast enhancement was higher with the second DECT than with the first DECT, and the second DECT was effective in minimizing the use of contrast materials.

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.

Dual-layer spectral detector CT: A noninvasive preoperative tool for predicting histopathological differentiation in pancreatic ductal adenocarcinoma

PURPOSE

To predict histopathological differentiation grades in patients with pancreatic ductal adenocarcinoma (PDAC) before surgery with quantitative and qualitative variables obtained from dual-layer spectral detector CT (DLCT).

METHODS

Totally 128 patients with histopathologically confirmed PDAC and preoperative DLCT were retrospectively enrolled and categorized into the low-grade (LG) (well and moderately differentiated, n = 82) and high-grade (HG) (poorly differentiated, n = 46) subgroups. Both conventional and spectral variables for PDAC were measured. The ratio of iodine concentration (IC) values in arterial phase(AP) and venous phase (VP) was defined as iodine enhancement fraction_AP/VP (IEF_AP/VP). Necrosis was visually assessed on both conventional CT images (necrosis_con) and virtual mono-energetic images (VMIs) at 40 keV (necrosis_40keV). Forward stepwise logistic regression method was conducted to perform univariable and multivariable analysis. Receiver operating characteristic (ROC) curves and the DeLong method were used to evaluate and compare the efficiencies of variables in predicting tumor grade.

RESULTS

Necrosis_con (odds ratio [OR] = 2.84, 95% confidence interval [CI]: 1.13-7.13; p < 0.001) was an independent predictor among conventional variables, and necrosis_40keV (OR = 5.82, 95% CI: 1.98-17.11; p = 0.001) and IEF_AP/VP (OR = 1.12, 95% CI:1.07-1.17; p < 0.001) were independent predictors among spectral variables for distinguishing LG PDAC from HG PDAC. IEF_AP/VP (AUC = 0.754, p = 0.016) and combination model (AUC = 0.812, p < 0.001) had better predictive performances than necrosis_con (AUC = 0.580). The combination model yielded the highest sensitivity (72%) and accuracy (79%), while IEF_AP/VP exhibited the highest specificity (89%).

CONCLUSION

Variables derived from DLCT have the potential to preoperatively evaluate PDAC tumor grade. Furthermore, spectral variables and their combination exhibited superior predictive performances than conventional CT variables.

Tomoelastography and Pancreatic Extracellular Volume Fraction Derived From MRI for Predicting Clinically Relevant Postoperative Pancreatic Fistula

BACKGROUND

Pancreatic stiffness and extracellular volume fraction (ECV) are potential imaging biomarkers for pancreatic fibrosis. Clinically relevant postoperative fistula (CR-POPF) is one of the most severe complications after pancreaticoduodenectomy. Which imaging biomarker performs better for predicting the risk of CR-POPF remains unknown.

PURPOSE

To evaluate the diagnostic performance of ECV and tomoelastography-derived pancreatic stiffness for predicting the risk of CR-POPF in patients undergoing pancreaticoduodenectomy.

STUDY TYPE

Prospective.

POPULATION

Eighty patients who underwent multiparametric pancreatic MRI before pancreaticoduodenectomy, among whom 16 developed CR-POPF and 64 did not.

FIELD STRENGTH/SEQUENCE

3 T/tomoelastography and precontrast and postcontrast T1 mapping of the pancreas.

ASSESSMENT

Pancreatic stiffness was measured on the tomographic c-map, and pancreatic ECV was calculated from precontrast and postcontrast T1 maps. Pancreatic stiffness and ECV were compared with histological fibrosis grading (F0-F3). The optimal cutoff values for predicting CR-POPF were determined, and the correlation between CR-POPF and imaging parameters was evaluated.

STATISTICAL TESTS

The Spearman's rank correlation and multivariate linear regression analysis was conducted. The receiver operating characteristic curve analysis and logistic regression analysis was performed. A double-sided P < 0.05 indicated a statistically significant difference.

RESULTS

Pancreatic stiffness and ECV both showed a significantly positive correlation with histological pancreatic fibrosis (r = 0.73 and 0.56, respectively). Patients with advanced pancreatic fibrosis had significantly higher pancreatic stiffness and ECV compared to those with no/mild fibrosis. Pancreatic stiffness and ECV were also correlated with each other (r = 0.58). Lower pancreatic stiffness (<1.38 m/sec), lower ECV (<0.28), nondilated main pancreatic duct (<3 mm) and pathological diagnosis other than pancreatic ductal adenocarcinoma were associated with higher risk of CR-POPF at univariate analysis, and pancreatic stiffness was independently associated with CR-POPF at multivariate analysis (odds ratio: 18.59, 95% confidence interval: 4.45, 77.69).

DATA CONCLUSION

Pancreatic stiffness and ECV were associated with histological fibrosis grading, and pancreatic stiffness was an independent predictor for CR-POPF.

LEVEL OF EVIDENCE

1 TECHNICAL EFFICACY STAGE: 5.

Deep learning-based prediction of post-pancreaticoduodenectomy pancreatic fistula

Postoperative pancreatic fistula is a life-threatening complication with an unmet need for accurate prediction. This study was aimed to develop preoperative artificial intelligence-based prediction models. Patients who underwent pancreaticoduodenectomy were enrolled and stratified into model development and validation sets by surgery between 2016 and 2017 or in 2018, respectively. Machine learning models based on clinical and body composition data, and deep learning models based on computed tomographic data, were developed, combined by ensemble voting, and final models were selected comparison with earlier model. Among the 1333 participants (training, n = 881; test, n = 452), postoperative pancreatic fistula occurred in 421 (47.8%) and 134 (31.8%) and clinically relevant postoperative pancreatic fistula occurred in 59 (6.7%) and 27 (6.0%) participants in the training and test datasets, respectively. In the test dataset, the area under the receiver operating curve [AUC (95% confidence interval)] of the selected preoperative model for predicting all and clinically relevant postoperative pancreatic fistula was 0.75 (0.71-0.80) and 0.68 (0.58-0.78). The ensemble model showed better predictive performance than the individual ML and DL models.

Prediction of pancreatic fibrosis by dual-energy CT-derived extracellular volume fraction: Comparison with MRI

OBJECTIVES

To investigate the correlation between dual-energy CT (DECT) and MRI measurements of the extracellular volume fraction (ECV) and to assess the accuracy of both methods in predicting pancreatic fibrosis (PF).

METHODS

We retrospectively analyzed 43 patients who underwent pancreatectomy and preoperative pancreatic DECT and MRI between November 2018 and May 2022. The ECV was calculated using the T1 relaxation time (for MR-ECV) or absolute enhancement (for DECT-ECV) at equilibrium phase (180 s after contrast injection in our study). Pearson coefficient and Bland-Altman analysis were used to compare the correlation between the two ECVs, Spearman correlations were used to investigate the association between imaging parameters and PF, Receiver operating characteristic (ROC) curves were used to assess the diagnostic performance of the ECVs for advanced fibrosis (F2-F3), and multivariate logistic regression analysis was used to examine the relationship between PF and imaging parameters.

RESULTS

There was a strong correlation between DECT- and MR-derived ECVs (r = 0.948; p < 0.001). The two ECVs were positively correlated with PF (DECT: r = 0.647, p < 0.001; MR: r = 0.614, p < 0.001), and the mean values were 0.34 ± 0.08 (range: 0.22-0.62) and 0.35 ± 0.09 (range: 0.24-0.66), respectively. The area under the operating characteristic curve (AUC) for subjects with advanced fibrosis diagnosed by ECV was 0.86 for DECT-ECV and 0.87 for MR-ECV. Multivariate logistic regression analysis showed that the DECT-ECV was an independent predictor of PF.

CONCLUSIONS

The ECV could be an effective predictor of histological fibrosis, and DECT is equivalent to MRI for characterizing pancreatic ECV changes.

Progress in the application of dual-energy CT in pancreatic diseases

Pancreatic diseases are difficult to diagnose due to their insidious onset and complex pathophysiological developmental characteristics. In recent years, dual-energy computed tomography (DECT) imaging technology has rapidly advanced. DECT can quantitatively extract and analyze medical imaging features and establish a correlation between these features and clinical results. This feature enables the adoption of more modern and accurate clinical diagnosis and treatment strategies for patients with pancreatic diseases so as to achieve the goal of non-invasive, low-cost, and personalized treatment. The purpose of this review is to elaborate on the application of DECT for the diagnosis, biological characterization, and prediction of the survival of patients with pancreatic diseases (including pancreatitis, pancreatic cancer, pancreatic cystic tumor, pancreatic neuroendocrine tumor, and pancreatic injury) and to summarize its current limitations and future research prospects.

Application of ultrasound shear wave elastography in pre-operative and quantitative prediction of clinically relevant post-operative pancreatic fistula after pancreatectomy: a prospective study for the investigation of risk evaluation model

OBJECTIVES

The aim of this study was to modify recognized clinically relevant post-operative pancreatic fistula (CR-POPF) risk evaluation models with quantitative ultrasound shear wave elastography (SWE) values and identified clinical parameters to improve the objectivity and reliability of the prediction.

METHODS

Two prospective, successive cohorts were initially designed for the establishment of CR-POPF risk evaluation model and the internal validation. Patients who scheduled to receive pancreatectomy were enrolled. Virtual touch tissue imaging and quantification (VTIQ)-SWE was used to quantify pancreatic stiffness. CR-POPF was diagnosed according to 2016 International Study Group of Pancreatic Fistula standard. Recognized peri-operative risk factors of CR-POPF were analyzed, and the independent variables selected from multivariate logistic regression were used to build the prediction model.

RESULTS

Finally, the CR-POPF risk evaluation model was built in a group of 143 patients (cohort 1). CR-POPF occurred in 52/143 (36%) patients. Constructed from SWE values and other identified clinical parameters, the model achieved an area under the receiver operating characteristic curve of 0.866, with sensitivity, specificity, and likelihood ratio of 71.2%, 80.2%, and 3.597 in predicting CR-POPF. Decision curve of modified model revealed a better clinical benefit compared to the previous clinical prediction models. The models were then examined via internal validation in a separate collection of 72 patients (cohort 2).

CONCLUSIONS

Risk evaluation model based on SWE and clinical parameters is a potential non-invasive way to pre-operatively, objectively predict CR-POPF after pancreatectomy.

CLINICAL RELEVANCE STATEMENT

Our modified model based on ultrasound shear wave elastography may provide an easy access in pre-operative and quantitative evaluating the risk of CR-POPF following pancreatectomy and improve the objectivity and reliability of the prediction compared to previous clinical models.

KEY POINTS

• Modified prediction model based on ultrasound shear wave elastography (SWE) provides an easy access for clinicians to pre-operatively, objectively evaluate the risk of clinically relevant post-operative pancreatic fistula (CR-POPF) following pancreatectomy. • Prospective study with validation showed that the modified model provides better diagnostic efficacy and clinical benefits compared to previous clinical models in predicting CR-POPF. • Peri-operative management of CR-POPF high-risk patients becomes more possible.

Early evaluation of liver metastasis using spectral CT to predict outcome in patients with colorectal cancer treated with FOLFOXIRI and bevacizumab

PURPOSE

Early evaluation of the efficacy of first-line chemotherapy combined with bevacizumab in patients with colorectal cancer liver metastasis (CRLM) remains challenging. This study used 2-month post-chemotherapy spectral computed tomography (CT) to predict the overall survival (OS) and response of CRLM patients with bevacizumab-containing therapy.

METHOD

This retrospective analysis was performed in 104 patients with pathologically confirmed CRLM between April 2017 and October 2021. Patients were treated with 5-fluorouracil, leucovorin, oxaliplatin or irinotecan with bevacizumab. Portal venous phase spectral CT was performed on the target liver lesion within 2 months of commencing chemotherapy to demonstrate the iodine concentration (IoD) of the target liver lesion. The patients were classified as responders (R +) or non-responders (R -) according to the Response Evaluation Criteria in Solid Tumors (RECIST) v1.1 at 6 months. Multivariate analysis was performed to determine the relationships of the spectral CT parameters, tumor markers, morphology of target lesions with OS and response. The differences in portal venous phase spectral CT parameters between the R + and R - groups were analyzed. Receiver operating characteristic (ROC) curves were used to evaluate the predictive power of spectral CT parameters.

RESULTS

Of the 104 patients (mean age ± standard deviation: 57.73 years ± 12.56; 60 men) evaluated, 28 (26.9%) were classified as R + . Cox multivariate analysis identified the iodine concentration (hazard ratio [HR]: 1.238; 95% confidence interval [95% CI]: 1.089-1.408; P < 0.001), baseline tumor longest diameter (BLD) (HR: 1.022; 95% CI: 1.005-1.038, P = 0.010), higher baseline CEA (HR: 1.670; 95% CI: 1.016-2.745, P = 0.043), K-RAS mutation (HR: 2.027; 95% CI: 1.192-3.449; P = 0.009), and metachronous liver metastasis (HR: 1.877; 95% CI: 1.179-2.988; P = 0.008) as independent risk factors for patient OS. Logistic multivariate analysis identified the IoD (Odds Ratio [OR]: 2.243; 95% CI: 1.405-4.098; P = 0.002) and clinical N stage of the primary tumor (OR: 4.998; 95% CI: 1.210-25.345; P = 0.035) as independent predictor of R + . Using IoD cutoff values of 4.75 (100ug/cm³) the area under the ROC curve was 0.916, sensitivity and specificity were 80.3% and 96.4%, respectively.

CONCLUSIONS

Spectral CT IoD can predict the OS and response of patients with CRLM after 2 months of treatment with bevacizumab-containing therapy.

Pancreatic fat fraction in dual-energy computed tomography as a potential quantitative parameter in the detection of type 2 diabetes mellitus

PURPOSE

To investigate the clinical value of measuring pancreatic fat fraction using dual-energy computed tomography (DECT) in association with type 2 diabetes mellitus (T2DM).

MATERIALS AND METHODS

This retrospective study included patients who underwent abdominal DECT between September 2021 and July 2022. The fat fractions in the head, body, and tail of the pancreas were calculated using fat maps generated from unenhanced DECT images, and CT values were measured at the same locations. The intraclass correlation coefficient (ICC) was used to analyze the reproducibility of measurements from two observers. Diagnostic performance was assessed using receiver operating characteristic curves.

RESULTS

Seventy-eight patients, including 45 T2DM patients and 33 controls, were enrolled. The fat fractions of the pancreas were significantly higher in the T2DM group than in the control group (pancreatic head: 8.4 ± 6.3 % vs 5.1 ± 3.9 %; pancreatic body: 4.8 ± 4.0 % vs 2.7 ± 3.9 %; and pancreatic tail: 5.3 ± 3.2 % vs 2.7 ± 2.9 %, all p < 0.05). And the CT values of the pancreas were significantly lower in the T2DM group than in the control group (pancreatic head: 41.1 ± 8.5 HU vs 45.7 ± 4.6 HU; pancreatic body: 44.4 ± 5.0 HU vs 47.4 ± 3.7 HU; and pancreatic tail: 44.5 ± 5.0 HU vs 47.6 ± 3.2 HU, all p < 0.05). The fat fraction of the pancreatic tail was the best indicator for distinguishing T2DM patients from the controls (area under the curve: 0.716 (95 % CI: 0.601, 0.832), sensitivity: 64.4 % (95 % CI: 48.7 %, 77.7 %), and specificity: 78.8 % (95 % CI: 60.6 %, 90.4 %)).

CONCLUSION

The DECT fat fractions of the pancreas could be a valuable additional parameter in the detection of T2DM.