LEMPS - Liver Elastography Malignancy Prediction Score
Due to copyright issues we are not in position to present detailed science behind LEMPS, so we are presenting an abstract of the original publication with the link to paper itself:
BACKGROUND&AIMS:
To analyse elastographic characteristics of focal liver lesions (FLL)s and diagnostic performance of real-time two-dimensional shear-wave elastography (RT-2D-SWE) in order to differentiate benign and malignant FLLs.
METHODS:
Consecutive patients diagnosed with FLL by abdominal ultrasound (US) underwent RT-2D-SWE of FLL and non-infiltrated liver by intercostal approach over the right liver lobe. The nature of FLL was determined by diagnostic work-up, including at least one contrast-enhanced imaging modality (MDCT/MRI), check-up of target organs when metastatic disease was suspected and FLL biopsy in inconclusive cases.
RESULTS:
We analysed 196 patients (median age 60 [range 50-68], 50.5% males) with 259 FLLs (57 hepatocellular carcinomas, 17 cholangiocarcinomas, 94 metastases, 71 haemangiomas, 20 focal nodular hyperplasia) of which 70 (27%) were in cirrhotic liver. Malignant lesions were stiffer (P < .001) with higher variability in intralesional stiffness (P = .001). The best performing cut-off of lesion stiffness was 22.3 kPa (sensitivity 83%; specificity 86%; positive predictive value [PPV] 91.5%; negative predictive value [NPV] 73%) for malignancy. Lesion stiffness <14 kPa had NPV of 96%, while values >32.5 kPa had PPV of 96% for malignancy. Lesion stiffness, lesion/liver stiffness ratio and lesion stiffness variability significantly predicted malignancy in stepwise logistic regression (P < .05), and were used to construct a new Liver Elastography Malignancy Prediction (LEMP) score with accuracy of 96.1% in validation cohort (online calculator available at http://bit.do/lemps).
CONCLUSION:
The comprehensive approach demonstrated in this study enables correct differentiation of benign and malignant FLL in 96% of patients by using RT-2D-SWE.
Original publication describing the methodology and accuracy of LEMPS can be found here: