Title | Quantitative susceptibility mapping for detection of kidney stones, hemorrhage differentiation, and cyst classification in ADPKD. |
Publication Type | Journal Article |
Year of Publication | 2024 |
Authors | Schumacher K, Prince MR, Blumenfeld JD, Rennert H, Hu Z, Dev H, Wang Y, Dimov AV |
Journal | Abdom Radiol (NY) |
Date Published | 2024 Mar 26 |
ISSN | 2366-0058 |
Abstract | BACKGROUND AND PURPOSE: The objective is to demonstrate feasibility of quantitative susceptibility mapping (QSM) in autosomal dominant polycystic kidney disease (ADPKD) patients and to compare imaging findings with traditional T1/T2w magnetic resonance imaging (MRI). METHODS: Thirty-three consecutive patients (11 male, 22 female) diagnosed with ADPKD were initially selected. QSM images were reconstructed from the multiecho gradient echo data and compared to co-registered T2w, T1w, and CT images. Complex cysts were identified and classified into distinct subclasses based on their imaging features. Prevalence of each subclass was estimated. RESULTS: QSM visualized two renal calcifications measuring 9 and 10 mm and three pelvic phleboliths measuring 2 mm but missed 24 calcifications measuring 1 mm or less and 1 larger calcification at the edge of the field of view. A total of 121 complex T1 hyperintense/T2 hypointense renal cysts were detected. 52 (43%) Cysts appeared hyperintense on QSM consistent with hemorrhage; 60 (49%) cysts were isointense with respect to simple cysts and normal kidney parenchyma, while the remaining 9 (7%) were hypointense. The presentation of the latter two complex cyst subtypes is likely indicative of proteinaceous composition without hemorrhage. CONCLUSION: Our results indicate that QSM of ADPKD kidneys is possible and uniquely suited to detect large renal calculi without ionizing radiation and able to identify properties of complex cysts unattainable with traditional approaches. |
DOI | 10.1007/s00261-024-04243-6 |
Alternate Journal | Abdom Radiol (NY) |
PubMed ID | 38530430 |
PubMed Central ID | 5103445 |
Related Lab:
Related Faculty:
Hanna Rennert, Ph.D.