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Deep learning based radiomics for preoperative diagnosis of adrenal pheochromocytoma with MRI: a prospective validation study

Deep learning based radiomics for preoperative diagnosis of adrenal pheochromocytoma with MRI: a prospective validation study

Status
Recruiting
Phases
Early Phase 1
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR1900028520
Enrollment
Unknown
Registered
2019-12-25
Start date
2019-05-30
Completion date
Unknown
Last updated
2020-01-06

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Adrenal pheochromocytoma

Interventions

Gold Standard:Pathological results
Index test:MRI&#32
images&#32
of&#32
adrenal&#32
tumors

Sponsors

Sun Yat-Sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 80 Years

Inclusion criteria

Inclusion criteria: 1) patients undergoing adrenal tumor resection; 2) pathologically confirmed adrenal tumor; 3) standard MRI examination before surgery.

Exclusion criteria

Exclusion criteria: 1) poor imaging quality or artifacts in MRI; 2) adrenal hyperplasia, adrenal cyst or adrenal angiolipoma confirmed by pathology.

Design outcomes

Primary

MeasureTime frame
AUC;Sensitivity;Specificity;—

Countries

China

Contacts

Public ContactTianxin Lin

Sun Yat-Sen Memorial Hospital, Sun Yat-sen University

lintx@mail.sysu.edu.cn+86 13724008338

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026