In:
Cancer Research, American Association for Cancer Research (AACR), Vol. 78, No. 16 ( 2018-08-15), p. 4774-4785
Abstract:
The established role of hypoxia-induced signaling in prostate cancer growth, metastasis, and response to treatment suggests that a method to image hypoxia in tumors could aid treatment decisions. Here, we present consumption and supply-based hypoxia (CSH) imaging, an approach that integrates images related to oxygen consumption and supply into a single image. This integration algorithm was developed in patients with prostate cancer receiving hypoxia marker pimonidazole prior to prostatectomy. We exploited the intravoxel incoherent motion (IVIM) signal in diagnostic diffusion-weighted (DW) magnetic resonance (MR) images to generate separate images of the apparent diffusion coefficient (ADC) and fractional blood volume (fBV). ADC and fBV correlated with cell density (CD) and blood vessel density (BVD) in histology and whole-mount sections from 35 patients, thus linking ADC to oxygen consumption and fBV to oxygen supply. Pixel-wise plots of ADC versus fBV were utilized to predict the hypoxia status of each pixel in a tumor and to visualize the predicted value in a single image. The hypoxic fraction (HFDWI) of CSH images correlated strongly (R2 = 0.66; n = 41) with pimonidazole immunoscore (HSPimo); this relationship was validated in a second pimonidazole cohort (R2 = 0.54; n = 54). We observed good agreement between CSH images and pimonidazole staining in whole-mount sections. HFDWI correlated with tumor stage and lymph node status, consistent with findings for HSPimo. Moreover, CSH imaging could be applied on histologic CD and BVD images, demonstrating transferability to a histopathology assay. Thus, CSH represents a robust approach for hypoxia imaging in prostate cancer that could easily be translated into clinical practice. Significance: These findings present a novel imaging strategy that indirectly measures tumor hypoxia and has potential application in a wide variety of solid tumors and other imaging modalities. Graphical Abstract: http://cancerres.aacrjournals.org/content/canres/78/16/4774/F1.large.jpg. Cancer Res; 78(16); 4774–85. ©2018 AACR.
Type of Medium:
Online Resource
ISSN:
0008-5472
,
1538-7445
DOI:
10.1158/0008-5472.CAN-17-3806
Language:
English
Publisher:
American Association for Cancer Research (AACR)
Publication Date:
2018
detail.hit.zdb_id:
2036785-5
detail.hit.zdb_id:
1432-1
detail.hit.zdb_id:
410466-3
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