Anty Rodolphe, Morvan Marie, Le Corvec Maëna, Canivet Clémence M, Patouraux Stéphanie, Gugenheim Jean, Bonnafous Stéphanie, Bailly-Maitre Béatrice, Sire Olivier, Tariel Hugues, Bernard Jérôme, Piche Thierry, Loréal Olivier, Aron-Wisnewsky Judith, Clément Karine, Tran Albert, Iannelli Antonio, Gual Philippe
Université Côte d'Azur, CHU, INSERM, U1065, C3M, France.
University of Rennes, CNRS, IRMAR - UMR, 6625, Rennes, France.
JHEP Rep. 2019 Oct 23;1(5):361-368. doi: 10.1016/j.jhepr.2019.09.005. eCollection 2019 Nov.
There is an urgent medical need to develop non-invasive tests for non-alcoholic steatohepatitis (NASH). This study evaluates the diagnostic performance of an innovative model based on mid-infrared (MIR) spectroscopy for the diagnosis of NASH.
Severely obese patients who underwent a bariatric procedure at the University Hospital of Nice, France (n = 395) were prospectively recruited. The clinico-biological characteristics were measured prior to surgery. Liver biopsies were collected during the surgical procedure and assessed by a pathologist. A training group (316 patients, NASH: 16.8%) and a validation group (79 patients, NASH: 16.5%) were randomly defined. MIR spectra were acquired by fiber evanescent wave spectroscopy, using chalcogenide glass fiber optic sensors and a spectrometer. This absorption spectroscopic technique delivers a spectrum that identifies the molecular composition of a sample, defining a patient's metabolic fingerprint.
The areas under the receiver operating curve (AUROC) for the diagnosis of NASH were 0.82 and 0.77 in the training and validation groups, respectively. The best threshold was 0.15, which was associated with a sensitivity of 0.75 and 0.69, and a specificity of 0.72 and 0.76. Negative predictive values of 0.94 and 0.93 and positive predictive values of 0.35 and 0.36, as well as correctly classified patient rates of 72% and 75% were obtained in the training and validation groups, respectively. A composite model using aspartate aminotransferase level, triglyceride level and waist circumference alongside the MIR spectra led to an increase in AUROC (0.88 and 0.84 for the training and validations groups, respectively).
MIR spectroscopy provides good sensitivity and negative predictive values for NASH screening in patients with severe obesity.
There is an urgent need for tools to non-invasively diagnose and monitor non-alcoholic steatohepatitis (NASH). This study evaluates the performance of a new tool for fast NASH diagnosis based on mid-infrared (MIR) spectroscopy. Using serum samples from severely obese patients who underwent a bariatric procedure, which enabled a concomitant liver biopsy to be performed, the MIR spectroscopy model performed well in screening patients for NASH compared to a traditional, histological diagnosis.
开发非酒精性脂肪性肝炎(NASH)的非侵入性检测方法存在迫切的医学需求。本研究评估了基于中红外(MIR)光谱的创新模型对NASH的诊断性能。
前瞻性招募了在法国尼斯大学医院接受减肥手术的重度肥胖患者(n = 395)。在手术前测量临床生物学特征。在手术过程中采集肝活检组织并由病理学家进行评估。随机确定一个训练组(316例患者,NASH:16.8%)和一个验证组(79例患者,NASH:16.5%)。使用硫属化物玻璃光纤传感器和光谱仪通过光纤倏逝波光谱法获取MIR光谱。这种吸收光谱技术可提供识别样品分子组成的光谱,定义患者的代谢指纹。
训练组和验证组诊断NASH的受试者工作特征曲线下面积(AUROC)分别为0.82和0.77。最佳阈值为0.15,其敏感性分别为0.75和0.69,特异性分别为0.72和0.76。训练组和验证组的阴性预测值分别为0.94和0.93,阳性预测值分别为0.35和0.36,正确分类患者率分别为72%和75%。将天冬氨酸转氨酶水平、甘油三酯水平和腰围与MIR光谱一起使用的复合模型导致AUROC增加(训练组和验证组分别为0.88和0.84)。
MIR光谱法对重度肥胖患者的NASH筛查具有良好的敏感性和阴性预测值。
迫切需要用于非侵入性诊断和监测非酒精性脂肪性肝炎(NASH)的工具。本研究评估了一种基于中红外(MIR)光谱的快速NASH诊断新工具的性能。使用来自接受减肥手术的重度肥胖患者的血清样本,这使得能够同时进行肝活检,与传统的组织学诊断相比,MIR光谱模型在筛查NASH患者方面表现良好。