Small Cell Lung Carcinoma Metastasis to Atypical Meningioma: Importance of Perfusion Magnetic Resonance Imaging Graphics in Differential Diagnosis

The differential diagnosis of advanced lung cancer is difficult in clinical practice. Our study aims to compare the value of diffusion weighted imaging (DWI) with short-term inversion recovery sequence (STIR) for sagittal imaging in the differential diagnosis of lung cancer. 149 patients with non-small cell lung carcinoma (NSCLC) were enrolled and underwent DWI and STIR sagittal imaging. To quantify cancer types, we evaluated the apparent diffusion coefficient (ADC) value on DWI and the contrast ratio (CRs) on sagittal imaging. The ADC values of subclasses in NSCLC were significantly higher than small cell lung carcinoma (SCLC) (p <0.01). The mean CRs were 1.59 for SCLC and 1.30 for NSCLC with a significant difference (p < 0.01). Large cell carcinomas (LCC) and adenocarcinomas have significant differences compared to small cell carcinomas (SCC) without difference between squamous cell carcinomas (p > 0.05); this is also the case for CRs. Squamous cell carcinoma and adenocarcinoma have significant differences compared to SCC without difference in LCC (p > 0.05). Qualitative evaluation of the feasible thresholds DWI and STIR showed that the thresholds were 0.9810−3 mm2/s and 1.37 respectively. The specificity and accuracy was 78.5% is 85.3% for DWI, which was significantly higher than STIR (56.3% and 61.0%). The combination of DWI and STIR sequences was superior to DWI alone with an accuracy rate of 94.3%. DWI is more helpful than STIR in differentiating SCLC and NSCLC, and their combined use can significantly improve diagnosis accuracy.

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MicroRNA-based assay for differential diagnosis of squamous from non-squamous non-small cell lung carcinoma

Journal of Clinical Oncology ◽

10.1200/jco.2009.27.15_suppl.11069 ◽

2009 ◽

Vol 27 (15_suppl) ◽

pp. 11069-11069

Author(s):

D. Lebanony ◽

H. Benjamin ◽

S. Gilad ◽

K. Ashkenazi ◽

D. Nonaka ◽

...

Keyword(s):

Differential Diagnosis ◽

Lung Carcinoma ◽

Small Cell Lung Carcinoma ◽

Small Cell ◽

Cancer Type ◽

Diagnostic Assay ◽

Small Cell Lung ◽

Cell Lung Carcinoma ◽

Qrt Pcr

11069 Background: Recent advances in biologically directed therapies for non-small cell lung carcinoma (NSCLC) emphasize the need for more accurate sub-classification of NSCLC, as treatment may be dictated by histologic subtype. In particular, squamous histology can be a counter-indication for treatment by VEGF inhibitors. MicroRNAs are highly tissue-specific biomarkers with potential clinical applicability for defining cancer type and origin. MicroRNAs are well preserved in formalin fixed tissue, making them ideal candidates for molecular markers for use in routinely processed material. Here we report on the development and performance of a microRNA-based assay for the differential diagnosis of squamous from non-squamous NSCLC. Methods: We developed protocols for extraction of high-quality RNA that retain the microRNA fraction from FFPE archival tissue samples. MicroRNA microarrays were used to profile more than a hundred NSCLC samples. Specific microRNA qRT-PCR was used to validate results, and to develop a diagnostic assay. Results: We identified a microRNA biomarker that is strongly overexpressed in squamous cell NSCLC. A diagnostic assay (miRview squamous) was developed, that utilizes qRT-PCR measurement of this microRNA, normalized by an additional microRNA and a small nuclear RNA. This assay was validated on a blinded test set of 64 tumor samples, and had sensitivity of 97% and specificity of 91%. More than ¾ of the samples were classified with high confidence, and these classifications were accurate in 96% of the cases. Conclusions: MicroRNAs are becoming an important tool for classification of cancers. A diagnostic assay based on the specificity of a single microRNA accurately identifies squamous from non-squamous NSCLC. This assay provides an important new tool for the classification of NSCLC. [Table: see text]

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Is diffusion-weighted magnetic resonance imaging superior to positron emission tomography with fludeoxyglucose F 18 in imaging non–small cell lung cancer?

Journal of Thoracic and Cardiovascular Surgery ◽

10.1016/j.jtcvs.2008.12.026 ◽

2009 ◽

Vol 138 (2) ◽

pp. 439-445 ◽

Cited By ~ 48

Author(s):

Yasuomi Ohba ◽

Hiroaki Nomori ◽

Takeshi Mori ◽

Koei Ikeda ◽

Hidekatsu Shibata ◽

...

Keyword(s):

Magnetic Resonance Imaging ◽

Lung Cancer ◽

Positron Emission Tomography ◽

Magnetic Resonance ◽

Small Cell ◽

Emission Tomography ◽

Resonance Imaging ◽

Small Cell Lung ◽

Positron Emission ◽

Weighted Magnetic Resonance Imaging

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Functional Imaging in Lung Cancer

Journal of Clinical Oncology ◽

10.1200/jco.2005.08.854 ◽

2005 ◽

Vol 23 (14) ◽

pp. 3203-3211 ◽

Cited By ~ 22

Author(s):

Lalitha K. Shankar ◽

Daniel C. Sullivan

Keyword(s):

Magnetic Resonance Imaging ◽

Lung Cancer ◽

Magnetic Resonance ◽

Small Cell Lung Cancer ◽

Functional Imaging ◽

Cell Lung Cancer ◽

Small Cell ◽

Resonance Imaging ◽

Small Cell Lung ◽

Dynamic Contrast Enhancement

Accurate detection of the presence and extent of disease is vital in the management of non–small-cell lung cancer. While computed tomography and magnetic resonance imaging tend to be the routine diagnostic modalities used in the management of lung cancer, there have been significant advances in the field of functional and molecular imaging. In this article, we review the performance of the functional imaging techniques that are currently available for the evaluation of non–small-cell lung cancer. The techniques range from evaluation of glucose metabolism in tumors with fluorodeoxyglucose, to evaluation of proliferation with fluorothymidine and evaluation of tumor hypoxia with agents such as fluoromisonidazole. Magnetic resonance imaging with an emphasis on dynamic contrast enhancement of tumors as well as detecting of malignant lymph nodes with targeted contrast agents is discussed. Emerging technologies such as lung imaging fluorescence endoscopy are considered. The role of functional imaging in planning, predicting response to, and evaluating effects of, various therapies is explored.

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