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使用手术智能刀(iKnife)进行子宫内膜癌的床旁诊断——诊断准确性的前瞻性初步研究

Point-of-Care Diagnosis of Endometrial Cancer Using the Surgical Intelligent Knife (iKnife)-A Prospective Pilot Study of Diagnostic Accuracy.

作者信息

Marcus Diana, Phelps David L, Savage Adele, Balog Julia, Kudo Hiromi, Dina Roberto, Bodai Zsolt, Rosini Francesca, Ip Jacey, Amgheib Ala, Abda Julia, Manoli Eftychios, McKenzie James, Yazbek Joseph, Takats Zoltan, Ghaem-Maghami Sadaf

机构信息

Department of Surgery and Cancer, Imperial College London, Du Cane Road, London W12 0NN, UK.

Department of Gynaecological Oncology, University Hospital Southampton, Coxford Road, Southampton SO16 5YA, UK.

出版信息

Cancers (Basel). 2022 Nov 29;14(23):5892. doi: 10.3390/cancers14235892.

Abstract

Delays in the diagnosis and treatment of endometrial cancer negatively impact patient survival. The aim of this study was to establish whether rapid evaporative ionisation mass spectrometry using the iKnife can accurately distinguish between normal and malignant endometrial biopsy tissue samples in real time, enabling point-of-care (POC) diagnoses. Pipelle biopsy samples were obtained from consecutive women needing biopsies for clinical reasons. A Waters G2-XS Xevo Q-Tof mass spectrometer was used in conjunction with a modified handheld diathermy (collectively called the 'iKnife'). Each tissue sample was processed with diathermy, and the resultant surgical aerosol containing ionic lipid species was then analysed, producing spectra. Principal component analyses and linear discriminant analyses were performed to determine variance in spectral signatures. Leave-one-patient-out cross-validation was used to test the diagnostic accuracy. One hundred and fifty patients provided Pipelle biopsy samples (85 normal, 59 malignant, 4 hyperplasia and 2 insufficient), yielding 453 spectra. The iKnife differentiated between normal and malignant endometrial tissues on the basis of differential phospholipid spectra. Cross-validation revealed a diagnostic accuracy of 89% with sensitivity, specificity, positive predictive value and negative predictive value of 85%, 93%, 94% and 85%, respectively. This study is the first to use the iKnife to identify cancer in endometrial Pipelle biopsy samples. These results are highly encouraging and suggest that the iKnife could be used in the clinic to provide a POC diagnosis.

摘要

子宫内膜癌诊断和治疗的延迟会对患者生存率产生负面影响。本研究的目的是确定使用iKnife的快速蒸发电离质谱法能否实时准确区分正常和恶性子宫内膜活检组织样本,从而实现即时诊断。从因临床原因需要进行活检的连续女性中获取Pipelle活检样本。使用沃特世G2-XS Xevo Q-Tof质谱仪与改良的手持式透热疗法设备(统称为“iKnife”)配合使用。每个组织样本都经过透热疗法处理,然后对产生的含有离子脂质种类的手术气溶胶进行分析,生成光谱。进行主成分分析和线性判别分析以确定光谱特征的差异。采用留一法交叉验证来测试诊断准确性。150名患者提供了Pipelle活检样本(85例正常、59例恶性、4例增生和2例样本不足),共产生453个光谱。iKnife根据不同的磷脂光谱区分正常和恶性子宫内膜组织。交叉验证显示诊断准确率为89%,敏感性、特异性、阳性预测值和阴性预测值分别为85%、93%、94%和85%。本研究首次使用iKnife在子宫内膜Pipelle活检样本中识别癌症。这些结果非常令人鼓舞,表明iKnife可用于临床提供即时诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cafc/9736036/34c2769bca77/cancers-14-05892-g001.jpg

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