Characterization of Lung Cancer by Amide Proton Transfer (APT) Imaging: An In-Vivo Study in an Orthotopic Mouse Model

Osamu Togao,Koji Sagiyama,A Dean Sherry,Chase W Kessinger,Jinming Gao,Todd C Soesbe,Ivan Dimitrov,Masaya Takahashi,Gang Huang,Stephanie Filleur

doi:10.1371/journal.pone.0077019

Abstract

Amide proton transfer (APT) imaging is one of the chemical exchange saturation transfer (CEST) imaging methods which images the exchange between protons of free tissue water and the amide groups (−NH) of endogenous mobile proteins and peptides. Previous work suggested the ability of APT imaging for characterization of the tumoral grade in the brain tumor. In this study, we tested the feasibility of in-vivo APT imaging of lung tumor and investigated whether the method could differentiate the tumoral types on orthotopic tumor xenografts from two malignant lung cancer cell lines. The results revealed that APT imaging is feasible to quantify lung tumors in the moving lung. The measured APT effect was higher in the tumor which exhibited more active proliferation than the other. The present study demonstrates that APT imaging has the potential to provide a characterization test to differentiate types or grade of lung cancer noninvasively, which may eventually reduce the need invasive needle biopsy or resection for lung cancer.

Highlights

Lung cancer is the most common cause of cancer and the leading cause of cancer-related death in both men and women in the United States
The average sizes of the tumors that were involved in the Amide proton transfer (APT) measurement were 2.060.5 mm in the A549 group and 2.661.4 mm in the Lewis lung carcinoma (LLC) group where no significance was found in size between the groups (P = 0.35)
On the APT-weighted images (MTRasym map at 63.5 ppm) of A549 (Fig. 2A, right) and LLC (Fig. 2B, right), the tumors appeared brighter than the surrounding tissues including spinal cord and skeletal muscles

Summary

Introduction

Technical developments in computed tomography (CT) have enabled larger volume coverage with higher resolution and lower noise, and currently high-resolution CT (HRCT) is the standard imaging technique for assessing lung cancer [2] [3]. It provides excellent anatomic detail and the number of smaller lung nodules detected has increased [4]. If the lung nodule grows, subsequent needle biopsy or video-assisted thoracoscopic resection of the lung nodule is recommended there is still argument how accurately we can measure the growth of the lung nodule [5] This current situation delays the start of treatment even when it is needed. Previous data from multi-center studies have shown that approximately

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Conclusion