Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.
Utility of mass spectrometry and artificial intelligence for differentiating primary lung adenocarcinoma and colorectal metastatic pulmonary tumor.
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DOI：
10.1111/1759-7714.14246
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发表时间：
2022-01
期刊：
影响因子：
2.9
通讯作者：
Saito H
中科院分区：
文献类型：
--
作者：
Shigeeda W;Yosihimura R;Fujita Y;Saiki H;Deguchi H;Tomoyasu M;Kudo S;Kaneko Y;Kanno H;Inoue Y;Saito H
术中快速诊断不明肺肿瘤对确定最佳手术方式（肺叶切除或肺叶下切除）至关重要。最近已经描述了使用质谱法（MS）诊断恶性肿瘤的尝试。本研究评价了MS和人工智能（AI）在鉴别原发性肺腺癌（PLAC）和结直肠转移性肺肿瘤中的作用。收集了40例接受PLAC肺切除术（20例肿瘤，20例正常肺）或源自结直肠转移性肺肿瘤（CRMPT）的肺转移（20例肿瘤，20例正常肺）的患者的肺样本，并通过探针电喷雾电离-MS进行回顾性分析。使用随机森林（RF）算法的AI被用来评估每个组合的准确性。使用RF来区分恶性肿瘤（PLAC或CRMPT）与正常肺的机器学习算法的准确性为100%。该算法提供了97.2%的准确率区分PLAC和CRMPT。MS与AI系统相结合，不仅在区分癌症与正常组织方面表现出高准确性，而且在短工作时间内区分PLAC和CRMPT。这种方法显示出潜在的应用程序作为一个支持工具，促进快速术中诊断，以确定肺切除术的手术程序。术中快速诊断是决定手术方式的关键。本研究评价了质谱（MS）鉴别原发性肺腺癌（PLAC）和结直肠转移性肺肿瘤（CRMPT）的价值。MS不仅表现出高准确性区分癌症与正常组织，而且还PLAC和CRMPT的工作时间短，这表明应用于快速术中诊断的潜力。
Rapid intraoperative diagnosis for unconfirmed pulmonary tumor is extremely important for determining the optimal surgical procedure (lobectomy or sublobar resection). Attempts to diagnose malignant tumors using mass spectrometry (MS) have recently been described. This study evaluated the usefulness of MS and artificial intelligence (AI) for differentiating primary lung adenocarcinoma (PLAC) and colorectal metastatic pulmonary tumor. Pulmonary samples from 40 patients who underwent pulmonary resection for PLAC (20 tumors, 20 normal lungs) or pulmonary metastases originating from colorectal metastatic pulmonary tumor (CRMPT) (20 tumors, 20 normal lungs) were collected and analyzed retrospectively by probe electrospray ionization‐MS. AI using random forest (RF) algorithms was employed to evaluate the accuracy of each combination. The accuracy of the machine learning algorithm applied using RF to distinguish malignant tumor (PLAC or CRMPT) from normal lung was 100%. The algorithms offered 97.2% accuracy in differentiating PLAC and CRMPT. MS combined with an AI system demonstrated high accuracy not only for differentiating cancer from normal tissue, but also for differentiating between PLAC and CRMPT with a short working time. This method shows potential for application as a support tool facilitating rapid intraoperative diagnosis to determine the surgical procedure for pulmonary resection. Rapid intraoperative diagnosis for unconfirmed lung tumor is extremely important determining the surgical procedure. This study evaluated the usefulness of mass spectrometry (MS) for differentiating primary lung adenocarcinoma (PLAC) and colorectal metastatic pulmonary tumor (CRMPT). MS demonstrated high accuracy for differentiating not only cancer from normal tissue, but also PLAC and CRMPT with a short working time, suggesting the potential for application to rapid intraoperative diagnosis.
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影响因子：
0.7
作者：
Aversa, Sara;Bellan, Cristiana
通讯作者：
Bellan, Cristiana
影响因子：
3.8
作者：
Kiritani S;Yoshimura K;Arita J;Kokudo T;Hakoda H;Tanimoto M;Ishizawa T;Akamatsu N;Kaneko J;Takeda S;Hasegawa K
通讯作者：
Hasegawa K
影响因子：
9.3
作者：
Ifa DR;Eberlin LS
通讯作者：
Eberlin LS
影响因子：
1.2
作者：
Committee for Scientific Affairs, The Japanese Association for Thoracic Surgery;Shimizu H;Okada M;Toh Y;Doki Y;Endo S;Fukuda H;Hirata Y;Iwata H;Kobayashi J;Kumamaru H;Miyata H;Motomura N;Natsugoe S;Ozawa S;Saiki Y;Saito A;Saji H;Sato Y;Taketani T;Tanemoto K;Tangoku A;Tatsuishi W;Tsukihara H;Watanabe M;Yamamoto H;Minatoya K;Yokoi K;Okita Y;Tsuchida M;Sawa Y
通讯作者：
Sawa Y
影响因子：
2.9
作者：
Imai K;Nanjo H;Takashima S;Hiroshima Y;Atari M;Matsuo T;Kuriyama S;Ishii Y;Wakamatsu Y;Sato Y;Motoyama S;Saito H;Nomura K;Minamiya Y
通讯作者：
Minamiya Y