Gaiani S, Casali A, Serra C, Piscaglia F, Gramantieri L, Volpe L, Siringo S, Bolondi L. Assessment of vascular patterns of small liver mass lesions: value and limitation of the different Doppler ultrasound modalities.
Am J Gastroenterol 2000;
95:3537-46. [PMID:
11151890 DOI:
10.1111/j.1572-0241.2000.03372.x]
[Citation(s) in RCA: 37] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
OBJECTIVES
This study aimed to investigate the value and limitation of the different Doppler ultrasound modalities (spectral analysis, color, and power Doppler imaging) in the differential diagnosis of small liver tumors to identify the optimal diagnostic approach with the presently available Doppler technology.
METHODS
Presence and distribution of color and power Doppler signals, Doppler peak frequency, resistive index, and systolic acceleration time were examined in 133 liver nodules (< or = 4 cm).
RESULTS
Color and power Doppler did not identify specific diagnostic vascular patterns. By discriminant analysis, peak frequency (cut-off 1320 Hz) differentiates small hematocellular carcinoma (< or = 2 cm) from macroregenerative nodules and hemangiomas (accuracy 92.6%); resistive index (cut-off 0.65) differentiates malignancies from benign lesions (accuracy 83.8%); and systolic acceleration time (cut-off 105 ms) differentiates hepatocellular carcinoma from metastases (accuracy 80.9%).
CONCLUSIONS
Power Doppler imaging is able to assess vascularity in the majority of small liver nodules, but the pattern distribution of tumoral vascular signals does not provide reliable differential diagnostic criteria. Using conventional Doppler technology, power Doppler should be used to detect vascular signals and spectral analysis, and subsequently to measure quantitative parameters such as high peak frequency and resistive index (which identify malignancy) and prolonged systolic acceleration time (which identifies primary from metastatic liver tumors).
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