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Invasive mucinous adenocarcinoma of the lung: Serial CT findings, clinical features, and treatment and survival outcomes.

ABSTRACT: Background: Invasive mucinous adenocarcinoma (IMA) of the lung is a rare and distinct subtype of adenocarcinoma that can appear as airspace opacities on computed tomography (CT). In daily practice, we have occasionally encountered spontaneous regression of airspace opacities (SRAs) without treatment on serial CTs in patients with IMAs, which has not previously been described in the literature. Here, we describe serial CT findings with emphasis on SRAs in relation to clinicopathological features and treatment outcomes in patients with IMAs.

Methods: A total of 46 patients with pathologically-confirmed IMAs of the lung from January 2013 to June 2018 were included. Serial CT scans were reviewed and the patients were classified into SRA and no-SRA groups according to the presence of SRA. Radiological features, clinicopathological characteristics, and treatment outcomes were compared between the SRA and no-SRA groups.

Results: A total of 32 patients were included in the no-SRA group and 14 patients in the SRA group. IMAs in the SRA group were mostly pneumonic (P
Conclusions: IMAs of the lung showing SRAs on serial CTs are larger and multifocal, and tend to be pneumonic in type on initial CT. Patients present at a higher stage of disease, with higher mortality rate and reduced overall survival.

Key points: SIGNIFICANT FINDINGS OF THE STUDY: Invasive mucinous adenocarcinomas (IMAs) of the lung can show spontaneous regression of airspace opacities (SRAs) on serial CTs, without being correlated to the administration of anticancer drugs. IMAs that showed SRAs demonstrated reduced overall survival in patients.

What this study adds: When airspace opacities show regression on CT, IMA should still be included in the differential diagnosis. A more careful application of RECIST 1.1 is needed in the assessment of tumor response of IMAs.

SUBMITTER: Beck KS

PROVIDER: S-EPMC7705898 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Invasive mucinous adenocarcinoma of the lung: Serial CT findings, clinical features, and treatment and survival outcomes.

Beck Kyongmin Sarah KS Sung Yeoun Eun YE Lee Kyo Young KY Han Dae Hee DH

Thoracic cancer 20201005 12

<h4>Background</h4>Invasive mucinous adenocarcinoma (IMA) of the lung is a rare and distinct subtype of adenocarcinoma that can appear as airspace opacities on computed tomography (CT). In daily practice, we have occasionally encountered spontaneous regression of airspace opacities (SRAs) without treatment on serial CTs in patients with IMAs, which has not previously been described in the literature. Here, we describe serial CT findings with emphasis on SRAs in relation to clinicopathological fe ...[more]

PMID: 33021074

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Project description:Objective: This study aimed to develop and validate predictive models using clinical parameters, radiomic features, and a combination of both for invasive mucinous adenocarcinoma (IMA) of the lung in patients with lung adenocarcinoma. Method: A total of 173 and 391 patients with IMA and non-IMA, respectively, were retrospectively analyzed from January 2017 to September 2022 in our hospital. Propensity Score Matching was used to match the 2 groups of patients. A total of 1037 radiomic features were extracted from contrast-enhanced computed tomography (CT). The patients were randomly divided into training and test groups at a ratio of 7:3. The least absolute shrinkage and selection operator algorithm was used for radiomic feature selection. Three radiomics prediction models were applied: logistic regression (logistic), support vector machine (SVM), and decision tree. The best-performing model was adopted, and the radiomics score (Radscore) was then computed. A clinical model was developed using logistic regression. Finally, a combined model was established based on a clinical model and a radiomics model. The area under the receiver operating characteristic (ROC) curve (AUC) and decision curve analysis were used to evaluate the predictive value of the developed models. Results: Both clinical and radiomics models established using the logistic method showed the best performance. The Delong test revealed that the combined model was superior to the clinical and radiomics models (P = .018 and .020, respectively). The ROC-AUC (also decision curve analysis) of the combined model was 0.840 and 0.850 in the training and testing groups, respectively, which showed good predictive performance for IMA. The Brier scores for the combined model were 0.161 and 0.154 in the training and testing groups, respectively. Conclusion: The combined model incorporating radiomic CT features and clinical predictors may have the potential to predict IMA in patients with lung cancer.

Project description:ObjectiveTo investigate the association between CT imaging features and survival outcomes in patients with primary invasive mucinous adenocarcinoma (IMA).Materials and methodsPreoperative CT image findings were consecutively evaluated in 317 patients with resected IMA from January 2011 to December 2015. The association between CT features and long-term survival were assessed by univariate analysis. The independent prognostic factors were identified by the multivariate Cox regression analyses. The survival comparison of IMA patients was investigated using the Kaplan-Meier method and propensity scores. Furthermore, the prognostic impact of CT features was assessed based on different imaging subtypes, and the results were adjusted using the Bonferroni method.ResultsThe median follow-up time was 52.8 months; the 5-year disease-free survival (DFS) and overall survival rates of resected IMAs were 68.5% and 77.6%, respectively. The univariate analyses of all IMA patients demonstrated that 15 CT imaging features, in addition to the clinicopathologic characteristics, significantly correlated with the recurrence or death of IMA patients. The multivariable analysis revealed that five of them, including imaging subtype (p = 0.002), spiculation (p < 0.001), tumor density (p = 0.008), air bronchogram (p < 0.001), emphysema (p < 0.001), and location (p = 0.029) were independent prognostic factors. The subgroup analysis demonstrated that pneumonic-type IMA had a significantly worse prognosis than solitary-type IMA. Moreover, for solitary-type IMAs, the most independent CT imaging biomarkers were air bronchogram and emphysema with an adjusted p value less than 0.05; for pneumonic-type IMA, the tumors with mixed consolidation and ground-glass opacity were associated with a longer DFS (adjusted p = 0.012).ConclusionCT imaging features characteristic of IMA may provide prognostic information and individual risk assessment in addition to the recognized clinical predictors.

Project description:Mucinous gastric carcinoma (MGC) is a rare histological subtype of gastric cancer. The clinicopathological characteristics and CT features of MGC remain controversial. This study aimed to determine the clinicopathological characteristics and CT features of MGC. We reviewed 62 patients with MGC and 104 patients with non-mucinous gastric carcinoma (NMGC), pathologically confirmed between 2003 and 2015. There are significant differences in some clinicopathological characteristics and CT features between MGC and NMGC. NMGC occurs preferentially in males and more frequently in the lower third of the stomach. Patients with MGC were characterized by larger tumor size, more advanced tumor stages (II and III) and fewer lymphatic invasions. Layered enhancement (83.3%) was the main pattern of MGC, while the most common pattern in NMGC was homogeneous enhancement (52.6%), followed by heterogonous enhancement (34.6%). The degree of enhancement of the inner layer in MGC was significantly higher than in NMGC (ΔCT of portal venous phase: 54.57 Hu vs. 47.19 Hu, P = 0.034), while the middle or outer layer in MGC was significantly less enhanced (ΔCT of portal venous phase: 19.07 Hu vs. 33.09 Hu, P <0.001). Calcifications were more common in MGC (P <0.001). ROC curves revealed that the most effective variables in distinguishing MGC and NMGC were ΔCT of the middle or outer layer in the arterial phase (AUC=0.774) and portal venous phase (AUC=0.774), followed by the attenuation value of the middle or outer layer in the unenhanced phase (AUC=0.763). Calcifications had a high specificity (98.7%) in the diagnosis of MGC. The accuracy (86.1%), sensitivity (83.3%) and specificity (87.2%) of layered enhancement in diagnosing MGC were all high. Therefore, MGC was more likely to have larger tumor size and more advanced tumor stage (II and III) than NMGC. The thicker gastric wall, layered enhancement pattern and calcification were highly suggestive CT features for differentiating MGC from NMGC.

Dataset Information

Invasive mucinous adenocarcinoma of the lung: Serial CT findings, clinical features, and treatment and survival outcomes.

Publications

Invasive mucinous adenocarcinoma of the lung: Serial CT findings, clinical features, and treatment and survival outcomes.

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