Investigation of breast cancer microstructure and microvasculature from time-dependent DWI and CEST in correlation with histological biomarkers

Abstract

Abstract We investigated the associations of time-dependent DWI, non-Gaussian DWI, and CEST parameters with histological biomarkers in a breast cancer xenograft model. 22 xenograft mice (7 MCF-7 and 15 MDA-MB-231) were scanned at 4 diffusion times [T d = 2.5/5 ms with 11 b-values (0–600 s/mm 2 ) and T d = 9/27.6 ms with 17 b-values (0–3000 s/mm 2 ), respectively]. The apparent diffusion coefficient (ADC) was estimated using 2 b-values in different combinations (ADC 0–600 using b = 0 and 600 s/mm 2 and shifted ADC [sADC 200–1500 ] using b = 200 and 1500 s/mm 2 ) at each of those diffusion times. Then the change (Δ) in ADC/sADC between diffusion times was evaluated. Non-Gaussian diffusion and intravoxel incoherent motion (IVIM) parameters (ADC 0 , the virtual ADC at b = 0; K, Kurtosis from non-Gaussian diffusion; f , the IVIM perfusion fraction) were estimated. CEST images were acquired and the amide proton transfer signal intensity (APT SI) were measured. The ΔsADC 9–27.6 (between $${\text{sADC}}_{{9\,{\text{ms}}}}^{200{-}1500}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>sADC</mml:mtext> <mml:mrow> <mml:mrow> <mml:mn>9</mml:mn> <mml:mspace/> <mml:mtext>ms</mml:mtext> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>200</mml:mn> <mml:mo>-</mml:mo> <mml:mn>1500</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> and $${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>sADC</mml:mtext> <mml:mrow> <mml:mrow> <mml:mn>27.6</mml:mn> <mml:mspace/> <mml:mtext>ms</mml:mtext> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>200</mml:mn> <mml:mo>-</mml:mo> <mml:mn>1500</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> and ΔADC 2.5 _sADC 27.6 (between $${\text{ADC}}_{{2.5\, {\text{ms}}}}^{0{-}600}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>ADC</mml:mtext> <mml:mrow> <mml:mrow> <mml:mn>2.5</mml:mn> <mml:mspace/> <mml:mtext>ms</mml:mtext> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>0</mml:mn> <mml:mo>-</mml:mo> <mml:mn>600</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> and $${\text{sADC}}_{{27.6\,{\text{ms}}}}^{200{-}1500}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:msubsup> <mml:mtext>sADC</mml:mtext> <mml:mrow> <mml:mrow> <mml:mn>27.6</mml:mn> <mml:mspace/> <mml:mtext>ms</mml:mtext> </mml:mrow> </mml:mrow> <mml:mrow> <mml:mn>200</mml:mn> <mml:mo>-</mml:mo> <mml:mn>1500</mml:mn> </mml:mrow> </mml:msubsup> </mml:math> ) was significantly larger for MCF-7 groups, and ΔADC 2.5 _sADC 27.6 was positively correlated with Ki67 max and APT SI. ADC 0 decreased significantly in MDA-MB-231 group and K increased significantly with T d in MCF-7 group. APT SI and cellular area had a moderately strong positive correlation in MDA-MB-231 and MCF-7 tumors combined, and there was a positive correlation in MDA-MB-231 tumors. There was a significant negative correlation between APT SI and the Ki-67-positive ratio in MDA-MB-231 tumors and when combined with MCF-7 tumors. The associations of ΔADC 2.5 _sADC 27.6 and API SI with Ki-67 parameters indicate that the T d -dependent DW and CEST parameters are useful to predict the histological markers of breast cancers.