Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: Prognostic factors from CT findings

Ikehara, Mizuki; Saito, Haruhiro; Kondo, Tetsuro; Murakami, Shuji; Ito, Hiroyuki; Tsuboi, Masahiro; Oshita, Fumihiro; Noda, Kazumasa; Nakayama, Haruhiko; Yokose, Tomoyuki; Konishi, Yoichi; Yamada, Katsushi

doi:10.1016/j.ejrad.2010.09.026

Cited by 37 publications

(25 citation statements)

References 17 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, this appears to contrast with the studies that correlate the presence of an internal air bronchogram, in stage 1 tumors with pleural retraction, with good prognosis (31). Yet a recent study found a nonsignificant correlation between the presence of an air bronchogram and RFS, suggesting that larger studies that can adjust for confounding factors are needed (32). Consistent with our observations, Travis et al (33) reported a positive correlation between the presence of KRAS mutations and the presence of an internal air bronchogram.…”

Section: Leveraging Public Gene Expression Data Sets For Identifying supporting

confidence: 88%

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

Gevaert

Xu²,

Hoang³

et al. 2012

Radiology

358

287

View full text Add to dashboard Cite

show abstract

Section: Leveraging Public Gene Expression Data Sets For Identifying supporting

confidence: 88%

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

Gevaert

Xu²,

Hoang³

et al. 2012

Radiology

358

287

View full text Add to dashboard Cite

show abstract

“…Yet, by having both sets of patients, it was possible to show that texture heterogeneity was a survival predictor independent of treatment. Density on CT has been observed as a prognostic factor on CT before, for example, using the presence of air in the tumor (33,34); however, use of the CT component of PET/CT to measure tumor heterogeneity in lung cancer survival as such is novel.…”

Section: Discussionmentioning

confidence: 99%

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

Win

Miles

Janes

et al. 2013

Clinical Cancer Research

188

152

View full text Add to dashboard Cite

Purpose: We prospectively examined the role of tumor textural heterogeneity on positron emission tomography/computed tomography (PET/CT) in predicting survival compared with other clinical and imaging parameters in patients with non-small cell lung cancer (NSCLC).Experimental Design: The feasibility study consisted of 56 assessed consecutive patients with NSCLC (32 males, 24 females; mean age 67 AE 9.7 years) who underwent combined fluorodeoxyglucose (FDG) PET/ CT. The validation study population consisted of 66 prospectively recruited consecutive consenting patients with NSCLC (37 males, 29 females; mean age, 67.5 AE 7.8 years) who successfully underwent combined FDG PET/CT-dynamic contrast-enhanced (DCE) CT. Images were used to derive tumoral PET/CT textural heterogeneity, DCE CT permeability, and FDG uptake (SUV max ). The mean follow-up periods were 22.6 AE 13.3 months and 28.5AE 13.2 months for the feasibility and validation studies, respectively. Optimum threshold was determined for clinical stage and each of the above biomarkers (where available) from the feasibility study population. Kaplan-Meier analysis was used to assess the ability of the biomarkers to predict survival in the validation study. Cox regression determined survival factor independence.Results: Univariate analysis revealed that tumor CT-derived heterogeneity (P < 0.001), PET-derived heterogeneity (P ¼ 0.003), CT-derived permeability (P ¼ 0.002), and stage (P < 0Á001) were all significant survival predictors. The thresholds used in this study were derived from a previously conducted feasibility study. Tumor SUV max did not predict survival. Using multivariable analysis, tumor CT textural heterogeneity (P ¼ 0.021), stage (P ¼ 0.001), and permeability (P < 0.001) were independent survival predictors. These predictors were independent of patient treatment.Conclusions: Tumor stage and CT-derived textural heterogeneity were the best predictors of survival in NSCLC. The use of CT-derived textural heterogeneity should assist the management of many patients with NSCLC.

show abstract

“…375,389 In solid adenocarcinomas, the presence of notches, or concave cuts on thin section CT, has been associated with poor differentiation on histology and adverse outcome. 390 …”

Section: Radiologic Featuresmentioning

confidence: 99%

International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma

Travis¹,

Brambilla²,

Noguchi³

et al. 2011

Journal of Thoracic Oncology

Self Cite

3,992

2,438

View full text Add to dashboard Cite

Introduction Adenocarcinoma is the most common histologic type of lung cancer. To address advances in oncology, molecular biology, pathology, radiology, and surgery of lung adenocarcinoma, an international multidisciplinary classification was sponsored by the International Association for the Study of Lung Cancer, American Thoracic Society, and European Respiratory Society. This new adenocarcinoma classification is needed to provide uniform terminology and diagnostic criteria, especially for bronchioloalveolar carcinoma (BAC), the overall approach to small nonresection cancer specimens, and for multidisciplinary strategic management of tissue for molecular and immunohistochemical studies. Methods An international core panel of experts representing all three societies was formed with oncologists/pulmonologists, pathologists, radiologists, molecular biologists, and thoracic surgeons. A systematic review was performed under the guidance of the American Thoracic Society Documents Development and Implementation Committee. The search strategy identified 11,368 citations of which 312 articles met specified eligibility criteria and were retrieved for full text review. A series of meetings were held to discuss the development of the new classification, to develop the recommendations, and to write the current document. Recommendations for key questions were graded by strength and quality of the evidence according to the Grades of Recommendation, Assessment, Development, and Evaluation approach. Results The classification addresses both resection specimens, and small biopsies and cytology. The terms BAC and mixed subtype adenocarcinoma are no longer used. For resection specimens, new concepts are introduced such as adenocarcinoma in situ (AIS) and minimally invasive adenocarcinoma (MIA) for small solitary adenocarcinomas with either pure lepidic growth (AIS) or predominant lepidic growth with ≤5 mm invasion (MIA) to define patients who, if they undergo complete resection, will have 100% or near 100% disease-specific survival, respectively. AIS and MIA are usually nonmucinous but rarely may be mucinous. Invasive adenocarcinomas are classified by predominant pattern after using comprehensive histologic subtyping with lepidic (formerly most mixed subtype tumors with nonmucinous BAC), acinar, papillary, and solid patterns; micropapillary is added as a new histologic subtype. Variants include invasive mucinous adenocarcinoma (formerly mucinous BAC), colloid, fetal, and enteric adenocarcinoma. This classification provides guidance for small biopsies and cytology specimens, as approximately 70% of lung cancers are diagnosed in such samples. Non-small cell lung carcinomas (NSCLCs), in patients with advanced-stage disease, are to be classified into more specific types such as adenocarcinoma or squamous cell carcinoma, whenever possible for several reasons: (1) adenocarcinoma or NSCLC not otherwise specified should be tested for epidermal growth factor receptor (EGFR) mutations as the presence of these mutations is predictive o...

show abstract

Comparison of thin-section CT and pathological findings in small solid-density type pulmonary adenocarcinoma: Prognostic factors from CT findings

Cited by 37 publications

References 17 publications

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

Non–Small Cell Lung Cancer: Identifying Prognostic Imaging Biomarkers by Leveraging Public Gene Expression Microarray Data—Methods and Preliminary Results

Tumor Heterogeneity and Permeability as Measured on the CT Component of PET/CT Predict Survival in Patients with Non–Small Cell Lung Cancer

International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society International Multidisciplinary Classification of Lung Adenocarcinoma

Contact Info

Product

Resources

About