Vascular Anatomy Analysis During Prostatic Artery Embolization: Retrospective Comparison of Cone-Beam CT, Augmented
Arthur Diego Dias Rocha1, André Moreira de Assis1, Airton Mota Moreira1
1Department of Radiology and Oncology, University of São Paulo Medical School, São Paulo, Brazil, Rua Dr. Ovídio Pires de Campos, 225, São Paulo, SP, Brazil 05403-010.
Purpose:
To test the hypothesis that cone-beam computed tomography (CBCT), particularly when combined with augmented planning, improves identification and classification of prostatic arteries (PAs) compared with digital subtraction angiography (DSA) during prostatic artery embolization (PAE).
Materials And Methods:
This retrospective study included 133 hemipelves from PAEs performed between 2017 and 2019 at a single academic center. PA anatomy was assessed using DSA, unprocessed CBCT (uCBCT), and CBCT processed with augmented planning (pCBCT; Embo ASSIST, GE HealthCare, Chicago, IL). Findings were compared with the intraprocedural anatomical reference based on multi-imaging analysis. Performance measures are reported relative to this reference. Primary endpoints were hemipelvis-level assessment, defined as identification and correct origin classification of all PAs, and detection of multiple PA supply.
Results:
The intraprocedural anatomical reference identified 172 PAs, including 39 secondary PAs; 38/133 hemipelves (28.6%) had multiple PA supply. Anatomical assessment was accurate in 53.4% of hemipelves [44.5%-62.1%] with DSA, 91.0% [84.8%-95.3%] with uCBCT, and 100% [97.3%-100%] with pCBCT (P<.001 for all pairwise comparisons). For multiple PA detection, sensitivity was 28.9% [15.4%-45.9%] with DSA, 84.2% [68.7%-94.0%] with uCBCT, and 100% [90.7%-100%] with pCBCT. DSA detected 28.2% [15.0%-44.9%] secondary PAs, compared with 82.1% [66.5%-92.5%] with uCBCT and 100% [91.0%-100%] with pCBCT. Compared with uCBCT and DSA, pCBCT identified 7 and 28 additional secondary PAs, corresponding to increases of 17.9% and 71.8%, respectively.
Conclusion:
CBCT, especially with augmented planning, provides superior anatomical analysis compared to DSA, allowing more accurate identification and classification of PAs, increasing the detection of multiple PA supply during PAE.
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