Significance of pulmonary nodules in patients with colorectal cancer

Pomerri, Fabiox; Pucciarelli, Salvatore; Maretto, Isacco; Perrone, Ernesta; Pintacuda, Giovanna; Nitti, Donato; Muzzio, Pier Carlo

doi:10.1007/s00330-012-2431-4

Cited by 15 publications

(8 citation statements)

References 35 publications

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“…The careful evaluation of morphologic features is an essential step in pulmonary nodules assessment (13). Although several studies (22–24) have sought to identify significant image features for metastatic nodules, there is no consensus regarding the definition of IPNs, which led to slight differences between our results and previously published ones. In our study, we found that significant morphological features associated with pulmonary metastasis were long-axis diameter, density, and contour.…”

Section: Discussioncontrasting

confidence: 90%

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CT Morphological Features Integrated With Whole-Lesion Histogram Parameters to Predict Lung Metastasis for Colorectal Cancer Patients With Pulmonary Nodules

Wang

Xiangyu

et al. 2019

Front. Oncol.

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Purpose: To retrospectively identify the relationships between both CT morphological features and histogram parameters with pulmonary metastasis in patients with colorectal cancer (CRC) and compare the efficacy of single-slice and whole-lesion histogram analysis.Methods: Our study enrolled 196 CRC patients with pulmonary nodules (136 in the training dataset and 60 in the validation dataset). Twenty morphological features of contrast-enhanced chest CT were evaluated. The regions of interests were delineated in single-slice and whole-tumor lesions, and 22 histogram parameters were extracted. Stepwise logistic regression analyses were applied to choose the independent factors of lung metastasis in the morphological features model, the single-slice histogram model and whole-lesion histogram model. The areas under the curve (AUC) was applied to quantify the predictive accuracy of each model. Finally, we built a morphological-histogram nomogram for pulmonary metastasis prediction.Results: The whole-lesion histogram analysis (AUC of 0.888 and 0.865 in the training and validation datasets, respectively) outperformed the single-slice histogram analysis (AUC of 0.872 and 0.819 in the training and validation datasets, respectively) and the CT morphological features model (AUC of 0.869 and 0.845 in the training and validation datasets, respectively). The morphological-histogram model, developed with significant morphological features and whole-lesion histogram parameters, achieved favorable discrimination in both the training dataset (AUC = 0.919) and validation dataset (AUC = 0.895), and good calibration.Conclusions: CT morphological features in combination with whole-lesion histogram parameters can be used to prognosticate pulmonary metastasis for patients with colorectal cancer.

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Section: Discussioncontrasting

confidence: 90%

“…As reported by many other studies, nodule diameter is a reliable indicator of malignant potential (22, 23, 25). We found that solid nodules are more likely to be metastatic lesions.…”

Section: Discussionsupporting

confidence: 66%

CT Morphological Features Integrated With Whole-Lesion Histogram Parameters to Predict Lung Metastasis for Colorectal Cancer Patients With Pulmonary Nodules

Wang

Xiangyu

et al. 2019

Front. Oncol.

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“…Accordingly, we suggest that regular chest CT scans should be considered to diagnose pulmonary metastasis early. 13 Several widely recognized staging systems are available for evaluating HCC, such as the Barcelona Clinic Liver Cancer (BCLC) classification, TNM staging systems and American Joint Committee (AJCC) cancer staging system. 14 Many variables were identified as prognostic factors and were included in cancer staging systems, including the tumor size, vascular invasion, performance status, distant metastases, and liver function indicators such as serum albumin and bilirubin levels.…”

Section: Discussionmentioning

confidence: 99%

Nomogram for Predicting the Prognosis of Patients with Hepatocellular Carcinoma Presenting with Pulmonary Metastasis

Zhou¹,

Zhou²,

Ma³

et al. 2021

CMAR

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“…Accordingly, the follow-up of these patients should be more intensive. Thus, regular chest CT scans instead of chest X-ray should be taken (Pomerri et al , 2012) in order to diagnose PM early. The nomogram may also be a useful tool in deciding organ allocation for secondary liver transplantation for HCC patients who have been initially treated with partial hepatectomy.…”

Section: Discussionmentioning

confidence: 99%

A nomogram predicting pulmonary metastasis of hepatocellular carcinoma following partial hepatectomy

Liu

Yan

et al. 2014

Br J Cancer

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Background:Pulmonary metastasis (PM) following curative hepatectomy for hepatocellular carcinoma (HCC) is indicative of a poor prognosis. This study aimed to develop a nomogram to identify patients at high risks of PM.Methods:A primary cohort of patients who underwent curative hepatectomy for HCC at the Eastern Hepatobiliary Surgery Hospital from 2002 to 2010 was prospectively studied. A nomogram predicting PM was constructed based on independent risk factors of PM. The predictive performance was evaluated by the concordance index (c-index), calibration curve and decision curve analysis (DCA). During the study period, a validation cohort was included at the First Affiliated Hospital of Fujian Medical University.Results:Postoperative PMs were detected in 106 out of 620 and 45 out of 218 patients, respectively, in two cohorts. Factors included in the nomogram were microvascular invasion, serum alpha-fetoprotein, tumour size, tumour number, encapsulation and intratumoral CD34 staining. The nomogram had a c-index of 0.75 and 0.82 for the two cohorts for predicting PM, respectively. The calibration curves fitted well. In the two cohorts, the DCA demonstrated positive net benefits by the nomogram, within the threshold probabilities of PM >10%.Conclusion:The nomogram was accurate in predicting PM following curative hepatectomy for HCC.

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Significance of pulmonary nodules in patients with colorectal cancer

Cited by 15 publications

References 35 publications

CT Morphological Features Integrated With Whole-Lesion Histogram Parameters to Predict Lung Metastasis for Colorectal Cancer Patients With Pulmonary Nodules

CT Morphological Features Integrated With Whole-Lesion Histogram Parameters to Predict Lung Metastasis for Colorectal Cancer Patients With Pulmonary Nodules

Nomogram for Predicting the Prognosis of Patients with Hepatocellular Carcinoma Presenting with Pulmonary Metastasis

A nomogram predicting pulmonary metastasis of hepatocellular carcinoma following partial hepatectomy

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