Diffusion-weighted MRI-derived ADC values reflect collagen I content in PDX models of uterine cervical cancer
Metrics: HTML 1133 views | ?
Anette Hauge1, Catherine S. Wegner1, Jon-Vidar Gaustad1, Trude G. Simonsen1, Lise Mari K. Andersen1 and Einar K. Rofstad1
1Group of Radiation Biology and Tumor Physiology, Department of Radiation Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
Einar K. Rofstad, email: email@example.com
Keywords: DW-MRI; ADC; collagen; cervix carcinoma; PDX models
Received: September 05, 2017 Accepted: October 27, 2017 Published: November 11, 2017
Apparent diffusion coefficient (ADC) values derived from diffusion-weighted magnetic resonance imaging (DW-MRI) are known to reflect the cellular environment of biological tissues. However, emerging evidence accentuates the influence of stromal elements on ADC values. The current study sought to elucidate whether a correlation exists between ADC and the fraction of collagen I-positive tissue across different tumor models of uterine cervical cancer. Early and late generation tumors of four patient-derived xenograft (PDX) models of squamous cell carcinoma (BK-12, ED-15, HL-16, and LA-19) were included. DW-MRI was performed with diffusion encoding constants (b) of 200, 400, 700, and 1000 s/mm2 and diffusion gradient sensitization in three orthogonal directions. The fraction of collagen I-positive connective tissue was determined by immunohistochemistry. Mono-exponential decay curves, from which the ADC value of tumor voxels was calculated, yielded good fits to the diffusion data. A significant inverse correlation was detected between median tumor ADC and collagen I fraction across the four PDX models, indicating that collagen fibers in the extracellular space have the ability to inhibit the movement of water molecules in these xenografts. The results encourage further exploration of DW-MRI as a non-invasive imaging method for characterizing the stromal microenvironment of tumors.
All site content, except where otherwise noted, is licensed under a Creative Commons Attribution 3.0 License.