Using receiver operating characteristic curves to evaluate the diagnostic value of the combination of multislice spiral CT and alpha-fetoprotein levels for small hepatocellular carcinoma in cirrhotic patients

Ge, Jia; Feng, Guang-Long; Li, Jinping; Xu, Hailong; Wang, Hui; Cheng, Yi-Peng; Yan, Linlin; Jiang, Huijie

doi:10.1016/s1499-3872(17)60018-3

Cited by 7 publications

(5 citation statements)

References 25 publications

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“…Moreover, novel agents, like iosimenol and GE-145, are on the way to commercialization with the improvements made on an existing basis. The diagnostic efficacy of CECT for HCC in terms of area under the receiver operating characteristic (ROC) curve (AUC), sensitivity, and specificity were reported to be 0.93, 93%, and 82%, respectively ( 14 ). For HCC patients, the most distinctive role that CT perfusion imaging has played is the transarterial chemoembolization (TACE) assessment ( 15 ).…”

Section: Blood Pool Contrast Agentsmentioning

confidence: 99%

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

Zhang

Numata

et al. 2022

Front. Oncol.

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Hepatocellular carcinoma (HCC) has the third-highest incidence in cancers and has become one of the leading threats to cancer death. With the research on the etiological reasons for cirrhosis and HCC, early diagnosis has been placed great hope to form a favorable prognosis. Non-invasive medical imaging, including the associated contrast media (CM)-based enhancement scan, is taking charge of early diagnosis as mainstream. Meanwhile, it is notable that various CM with different advantages are playing an important role in the different imaging modalities, or even combined modalities. For both physicians and radiologists, it is necessary to know more about the proper imaging approach, along with the characteristic CM, for HCC diagnosis and treatment. Therefore, a summarized navigating map of CM commonly used in the clinic, along with ongoing work of agent research and potential seeded agents in the future, could be a needed practicable aid for HCC diagnosis and prognosis.

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Section: Blood Pool Contrast Agentsmentioning

confidence: 99%

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

Zhang

Numata

et al. 2022

Front. Oncol.

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“…is study creatively uses medical techniques and CT imaging techniques to diagnose extravascular invasion, and using CT imaging diagnosis can significantly improve diagnostic accuracy [18]; the diagnosis can be seen, and the images can be used to analyze the lesions as well as more intuitively display the diffusion situation, and the stability is improved [19], which is also the innovation of this study. After surgical pathological diagnosis, 40 patients showed external vascular invasion of gastric cancer [20].…”

Section: Discussionmentioning

confidence: 99%

The Application Value of ceMDCT in the Diagnosis of Gastric Cancer Extramural Vascular Invasion and Its Influencing Factors

Yang

Zou

et al. 2022

Journal of Healthcare Engineering

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Objective. To investigate the value of enhanced multislice spiral CT (ceMDCT) in the diagnosis of extramural vascular invasion of gastric cancer and the influencing factors of extramural vascular invasion. There are different methods used in this paper. Method. 131 patients with primary gastric cancer treated in our hospital from January 2017 to May 2019 were selected. All patients underwent surgical resection and ceMDCT examination before operation. Result. There were 40 cases with extramural vascular invasion of gastric cancer by surgical pathological diagnosis. The kappa value of ceMDCT in diagnosing extramural vascular invasion of gastric cancer was 0.947, and the consistency was excellent. The diagnostic sensitivity, specificity, positive predictive value, and negative predictive value were 100.00%, 96.70%, 93.02%, and 100.00%, respectively. The proportions of T3-T4, tumour diameter ≥5.0 cm, and growth pattern of proximal nodular + diffuse type in patients with gastric cancer extramural vascular invasion were 92.50%, 85.00%, and 65.00%, respectively, which were significantly higher than those in patients without extramural vascular invasion ( P < 0.05 ). The logistic regression analysis results showed that T3-T4, tumour diameter ≥5.0 cm, proximal nodular + diffuse growth pattern were the risk factors for extrahepatic vascular invasion in gastric cancer (OR = 3.751, 2.901, and 3.367, P < 0.05 ). Conclusion. ceMDCT has good application value in diagnosing gastric cancer extramural vascular invasion. The occurrence of gastric cancer extramural vascular invasion is affected by T staging, tumour diameter, and tumour growth pattern.

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“…Melanoma protein and gene alterations promote cancer and induce membrane peroxidation [16]. This disrupts blood chemistry, alters liver function, and emits VOCs in breath [17].…”

Section: Vocs Analysis Through Gcmsmentioning

confidence: 99%

Novel breath biomarkers identification for early detection of hepatocellular carcinoma and cirrhosis using ML tools and GCMS

Ain Nazir,

Shaukat,

Luo

et al. 2023

PLoS ONE

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According to WHO 2019, Hepatocellular carcinoma (HCC) is the fourth highest cause of cancer death worldwide. More precise diagnostic models are needed to enhance early HCC and cirrhosis quick diagnosis, treatment, and survival. Breath biomarkers known as volatile organic compounds (VOCs) in exhaled air can be used to make rapid, precise, and painless diagnoses. Gas chromatography and mass spectrometry (GCMS) are utilized to diagnose HCC and cirrhosis VOCs. In this investigation, metabolically generated VOCs in breath samples (n = 35) of HCC, (n = 35) cirrhotic, and (n = 30) controls were detected via GCMS and SPME. Moreover, this study also aims to identify diagnostic VOCs for distinction among HCC and cirrhosis liver conditions, which are most closely related, and cause misleading during diagnosis. However, using gas chromatography-mass spectrometry (GC-MS) to quantify volatile organic compounds (VOCs) is time-consuming and error-prone since it requires an expert. To verify GC-MS data analysis, we present an in-house R-based array of machine learning models that applies deep learning pattern recognition to automatically discover VOCs from raw data, without human intervention. All-machine learning diagnostic model offers 80% sensitivity, 90% specificity, and 95% accuracy, with an AUC of 0.9586. Our results demonstrated the validity and utility of GCMS-SMPE in combination with innovative ML models for early detection of HCC and cirrhosis-specific VOCs considered as potential diagnostic breath biomarkers and showed differentiation among HCC and cirrhosis. With these useful insights, we can build handheld e-nose sensors to detect HCC and cirrhosis through breath analysis and this unique approach can help in diagnosis by reducing integration time and costs without compromising accuracy or consistency.

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Using receiver operating characteristic curves to evaluate the diagnostic value of the combination of multislice spiral CT and alpha-fetoprotein levels for small hepatocellular carcinoma in cirrhotic patients

Cited by 7 publications

References 25 publications

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

Contrast Agents for Hepatocellular Carcinoma Imaging: Value and Progression

The Application Value of ceMDCT in the Diagnosis of Gastric Cancer Extramural Vascular Invasion and Its Influencing Factors

Novel breath biomarkers identification for early detection of hepatocellular carcinoma and cirrhosis using ML tools and GCMS

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