High signal intensity on diffusion-weighted magnetic resonance images is a useful finding for detecting early-stage pancreatic cancer.

Purpose: Early detection of pancreatic ductal adenocarcinoma (PDAC) may improve the prognosis. We evaluated novel imaging findings that may contribute to early detection. Methods: This single-center, retrospective study enrolled 37 patients with a localized main pancreatic duct (MPD) stricture and no obvious pancreatic mass. All patients underwent endoscopic retrograde cholangiopancreatography and brush sampling with cytology and serial pancreatic juice aspiration cytologic examination via endoscopic naso-pancreatic drainage. Patients with cytology-confirmed malignancy underwent surgical resection. The remaining patients were followed by contrast-enhanced computed tomography (CECT), magnetic resonance imaging (MRI), and endoscopic retrograde cholangiopancreatography. Results: Twenty patients had confirmed malignancy (cancer group) and 17 did not (non-cancer group). Age, MPD stricture location, and PDAC risk factors were similar, but the sex predominance and symptom rate differed between the two groups. In the cancer group, 17 patients were diagnosed by cytology and three by clinical symptoms. CECT, MRI, and endoscopic ultrasonography (EUS) revealed no solid tumors in either group. CECT revealed no significant differences between groups. Diffusion-weighted MRI revealed significant differences in the signal intensity between groups. EUS detected indistinct and small hypoechoic areas in 70% and 41.2% of patients in the cancer and non-cancer groups, respectively. In the cancer group, 11 were diagnosed with cancer at the first indication, and nine were diagnosed at follow-up; the prognosis did not differ between these two subgroups.ss Conclusions: High signal intensity in diffusion-weighted MRI may be useful for detecting early-stage PDAC and may be an indication for surgical resection even without pathologic confirmation. Clinical trial registration: The study was a registered at the University Hospital Medical Information Network (UMIN000039623). [ABSTRACT FROM AUTHOR]