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Updated: May 26, 2025
Dynamic Contrast Enhanced Magnetic Resonance Imaging of an Orthotopic Pancreatic Cancer Mouse Model
Published on: April 18, 2015
Contrast-enhanced photon-counting detector CT for discriminating local recurrence from postoperative changes after
Zlatan Alagic1,2, Carlos Valls Duran3,4, Anders Svensson-Marcial3,4
1Department of Diagnostic Radiology, Karolinska University Hospital, 171 76, Stockholm, Sweden. zlatan.alagic@ki.se.
Background:
We evaluated the diagnostic capability of photon-counting detector computed tomography (PCD-CT) spectral variables in late arterial phase (LAP) and portal venous phase (PVP) to discriminate between local tumor recurrence (LTR) and postoperative changes (POC) after pancreatic ductal adenocarcinoma (PDAC) resection.
Methods:
Seventy-three consecutive PCD-CT scans in 73 patients with postoperative soft-tissue lesions (PSLs) were included, 42 with POC and 31 with LTR. Regions of interest were drawn in each PSL, and spectral variables were calculated: iodine concentration (IC), normalized IC (NIC), fat fraction, attenuation at 40, 70, and 90 keV, and slope of the spectral curve between 40-90 keV. Multivariable binary logistic regression models were constructed. Diagnostic performance was assessed for LAP and PVP using receiver operating characteristic analysis.
Results:
In LAP, all variables except fat fraction showed significant differences between LTR and POC (p ≤ 0.025). In PVP, all variables except NIC and fat fraction demonstrated significant differences between LTR and POC (p ≤ 0.005). Logistic regression analysis included NIC and 70 keV in the LAP-based model and IC and 90 keV in the PVP-based model. Both models achieved a higher area under the curve (AUC) than individual spectral variables in each phase. The LAP-based model achieved an AUC of 0.919 with 94% sensitivity, 84% specificity, and 87% accuracy, while the PVP-based model reached 0.820, 71%, 88%, and 81%, respectively.
Conclusion:
Spectral variables from PCD-CT help distinguish between LTR and POC in LAP and PVP post-PDAC resection. Multivariable logistic regression improves diagnostic performance, especially in LAP.
Relevance Statement:
Measuring normalized iodine concentration and attenuation at 70 keV in late arterial phase, or iodine concentration and attenuation at 90 keV in portal venous phase, and incorporating these values into a logistic regression model can help differentiate between local tumor recurrence and postoperative changes after pancreatic ductal adenocarcinoma resection.
Key Points:
Distinguishing recurrence from postoperative changes on CT after pancreatic ductal adenocarcinoma resection is challenging. PCD-CT spectral variable values differed significantly between local tumor recurrence (LTR) and postoperative changes (POC). Logistic regression of spectral variables can help distinguish LTR from POC. The late arterial phase-based model reached an AUC of 0.919 with 94% sensitivity and 84% specificity.
