DIFFERENTIAL DIAGNOSTIC TECHNIQUE FOR HEPATIC GROWTHS DURING ULTRASOUND EXAMINATION Russian patent published in 2017 - IPC A61B8/08 

Abstract RU 2632768 C1

FIELD: medicine.

SUBSTANCE: invention can be used for the differential diagnostic of tumour growths in the liver. An ultrasound examination is performed in the fasted state on the scanner, which provides the possibility of carrying out shear wave elastometry. After the detection of liver parenchyma areas with the presence of focal lesions, the area of growth is enclosed in the survey window. The parameters of the shear wave elastometry mode are optimized. At least tenfold determination of the shear wave velocity (m/s) in the lesion is carried out and its minimum (Nmin) and maximum (Nmax) values are determined. The area of the unchanged liver parenchyma is enclosed in the survey window, at least tenfold determination of the shear wave velocity (m / s) in the unchanged parenchyma is carried out and it minimum (Pmin) and maximum (Pmax) values are determined. All these values are substituted into each of the four formulas for calculating the classification functions (CF): I) CF-I = 15.332× Nmax + 1.635 × Nmin + 46.502 × Pmax + 11.410 × Pmin - 76.784; II) CF-II = 11.940 × Nmax + 15.743 × Nmin + 38.718 × Pmax + 49.926 × Pmin - 125.872; III) CF-III = 9.897 × Nmax + 7.348 × Nmin + 47.042 × Pmax + 45.784 × Pmin - 110.752; IV) CF-IV = 15.731 × Nmax + 19.743 × Nmin + 35.605 × Pmax + 29.361 × pmin - 117.041. It is determined which of the four classification functions will have the maximum value in the series of obtained values. At the maximum value of CF-I, the patient is diagnosed with hepatic haemangioma. In the case of a maximum value of CF-II, the patient is diagnosed with hepatocellular adenoma. At the maximum value of CF-III, the patient is diagnosed with hepatocellular carcinoma. At the maximum value of CP-IV, the patient is diagnosed with colorectal cancer metastasis.

EFFECT: method provides high quality of differential diagnosis of malignant and benign liver growths, reduces the number of diagnostic errors.

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RU 2 632 768 C1

Authors

Agaeva Zoya Abuevna

Avkhadov Timur Sultanovich

Agaeva Madina Ilyasovna

Karanadze Elena Nikolaevna

Gorbov Leonid Valentinovich

Dates

2017-10-09Published

2016-12-16Filed