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Purpose <p>To identify the microvasculomic profiles of PDAC through SR-US, study the correlation between SR-US characteristics and pathological microvascular density (pMVD), and preliminarily explore the differential diagnostic value of pancreatic SR-US.</p> Materials and methods <p>We prospectively performed SR-US examinations for PDAC patients from August 2024 to June 2025. SR-US microvascular maps were reconstructed, and SR-US microvascular parameters were measured. pMVD was calculated, and the correlation between pMVD and SR-US characteristics was validated with Spearman correlation analysis. The differential diagnostic value of SR-US was analyzed by its capacity to differentiate PDAC and pancreatic neuroendocrine tumors (PNET), another common solid tumor of the pancreas, with the area under the curve (AUC) calculated.</p> Results <p>Seventy-two PDAC patients (median age: 64.00&#xa0;years; 40 men) were enrolled for analysis, and 12 PNET patients were enrolled only for differential diagnosis. Thirty-seven (51.39%) PDAC showed a branch-type microvascular morphology. The medians of microvascular ratio, microvascular complexity, and perfusion index were 22.88% (16.74%, 27.13%), 1.60 (1.53, 1.65), and 2.93 (2.05, 3.65). PDAC patients with branch-type or dot-type microvasculature showed significantly lower pMVD than those with diffuse chaotic microvasculature (<i>p</i> = 0.010). pMVD was significantly correlated with microvascular ratio; microvascular complexity; mean, max, and min microvascular velocity; and perfusion index (all <i>p</i> &lt; 0.05). SR-US characteristics achieved effective differential diagnosis between PDAC and PNET with the highest AUC up to 0.976 for microvascular ratio.</p> Conclusion <p>SR-US enables noninvasive evaluation of the microvasculomic profile of PDAC with preliminary evidence of pathological correlation and quantitative diagnostic value to differentiate PDAC from PNET.</p>

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Super-resolution ultrasound microscopy profiles microvasculomics of pancreatic ductal adenocarcinoma with pathological association and facilitates differential diagnosis

  • 期刊论文

  • 发表日期：

    2026年7月30日

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  • Zebang Yang,
  • Tongyi Huang,
  • Xin Zheng,
  • Xiaoer Zhang,
  • Jiaping Li,
  • Jingan Zhu,
  • Yuan Lin,
  • Xiaoyan Xie,
  • Ming Xu

摘要

Purpose

To identify the microvasculomic profiles of PDAC through SR-US, study the correlation between SR-US characteristics and pathological microvascular density (pMVD), and preliminarily explore the differential diagnostic value of pancreatic SR-US.

Materials and methods

We prospectively performed SR-US examinations for PDAC patients from August 2024 to June 2025. SR-US microvascular maps were reconstructed, and SR-US microvascular parameters were measured. pMVD was calculated, and the correlation between pMVD and SR-US characteristics was validated with Spearman correlation analysis. The differential diagnostic value of SR-US was analyzed by its capacity to differentiate PDAC and pancreatic neuroendocrine tumors (PNET), another common solid tumor of the pancreas, with the area under the curve (AUC) calculated.

Results

Seventy-two PDAC patients (median age: 64.00 years; 40 men) were enrolled for analysis, and 12 PNET patients were enrolled only for differential diagnosis. Thirty-seven (51.39%) PDAC showed a branch-type microvascular morphology. The medians of microvascular ratio, microvascular complexity, and perfusion index were 22.88% (16.74%, 27.13%), 1.60 (1.53, 1.65), and 2.93 (2.05, 3.65). PDAC patients with branch-type or dot-type microvasculature showed significantly lower pMVD than those with diffuse chaotic microvasculature (p = 0.010). pMVD was significantly correlated with microvascular ratio; microvascular complexity; mean, max, and min microvascular velocity; and perfusion index (all p < 0.05). SR-US characteristics achieved effective differential diagnosis between PDAC and PNET with the highest AUC up to 0.976 for microvascular ratio.

Conclusion

SR-US enables noninvasive evaluation of the microvasculomic profile of PDAC with preliminary evidence of pathological correlation and quantitative diagnostic value to differentiate PDAC from PNET.