In 2006, Parker et al published a population-average AIF that has subsequently been used by numerous investigators for both simulation and data analysis. Despite its utility, the published AIF suffers from a number of limitations. In this study we tried to address many of these limitations and made measurements in a population of patients with advanced breast cancer, resulting in a total of 74 individual AIFs. We fitted each AIF with a physiological model and assessed inter- and intra-patient variability.
Thirty-three female patients with locally advanced breast cancer undergoing neoadjuvant chemotherapy were enrolled in this prospective multiple visit MRI study. Data were acquired, at 1.5 T (Siemens Aera), in the transverse plane using a bilateral breast coil and a flexible matrix coil. The latter was positioned on the patients’ back to enhance the signal from the descending aorta. A 3D inversion recovery (IR) prepared TurboFLASH sequence (Table 1) was used for T1 measurement before and after the dynamic acquisition. High temporal resolution DCE data were acquired using a 3D FLASH sequence (Table 1) interleaved with the acquisition of high spatial resolution data3. Gd-DOTA (Doteram) was administered intravenously using a power injector at a dose of 0.1 mmol/kg, followed by 20 ml of saline, at a rate of 3 ml/s.
Regions of interest (ROIs) were drawn in the descending aorta on several inferior slices (Figure 1). T1 relaxation times were estimated by fitting the IR turboFLASH signal equation to the measured signal at both baseline and tail4,5 and a bookend correction was applied to the signal intensity time series as described by Cron et al6. Contrast agent concentration was calculated using a Dotarem relaxivity of 4.2 s-1 mM-1 in blood7. For accurate interpolation and integration, a functional form of the AIF8 was fitted to the acquired data. Using the area under the first pass peak (AUC1st) and indicator dilution principles the patients’ cardiac output (CO) was estimated at each visit9. To assess reproducibility of AIF measurement we examined the variability of pre-contrast T1, AUC1st and CO estimates using a one-way analysis of variance (ANOVA) for repeated measurements and the inter- and intra-patient coefficients of variability (COV).
1. Sourbron SP, Buckley DL. Tracer kinetic modelling in MRI: estimating perfusion and capillary permeability. Phys Med Biol. 2012;57:R1-R33.
2. Parker GJ, Roberts C, Macdonald A, Buonaccorsi GA, Cheung S, Buckley DL, et al. Experimentally-derived functional form for a population-averaged high-temporal-resolution arterial input function for dynamic contrast-enhanced MRI. Magn Reson Med. 2006;56:993-1000.
3. Georgiou L, Sharma N, Broadbent DA, et al. Estimating Breast Tumor Blood Flow During Neoadjuvant Chemotherapy Using Interleaved High Temporal and High Spatial Resolution MRI. Magn Reson Med. 2017;DOI 10.1002/mrm.26684.
4. Brix G, Schad LR, Deimling M, et al. Fast and precise T1 imaging using a TOMROP sequence. Magn Reson Imaging. 1990;8:351-356.
5. Kershaw LE, Hutchinson CE, Buckley DL. Benign prostatic hyperplasia: Evaluation of T1, T2, and microvascular characteristics with T1-weighted dynamic contrast-enhanced MRI. J Magn Reson Imaging. 2009;29:641-648.
6. Cron GO, Santyr G, Kelcz F. Accurate and Rapid Quantitative Dynamic Contrast-Enhanced Breast MR Imaging Using Spoiled Gradient-Recalled Echoes and Bookend T 1 Measurements. Magn Reson Med. 1999;753:746-753.
7. Rohrer M, Bauer H, Mintorovitch J, Requardt M, Weinmann H-J. Comparison of magnetic properties of MRI contrast media solutions at different magnetic field strengths. Invest Radiol. 2005;40:715–724.
8. Horsfield MA, Thornton JS, Gill A, Jager HR, Priest AN, Morgan B. A functional form for injected MRI Gd-chelate contrast agent concentration incorporating recirculation, extravasation and excretion. Phys Med Biol. 2009;54:2933–2949.
9. Yang C, Karczmar GS, Medved M, Oto A, Zamora M, Stadler WM. Reproducibility assessment of a multiple reference tissue method for quantitative dynamic contrast enhanced-MRI analysis. Magn Reson Med. 2009;61:851-9.
10. Dharmavaram S, Jellish WS, Nockels RP, et al. Effect of Prone Positioning Systems on Hemodynamic and Cardiac Function During Lumbar Spine Surgery: An Echocardiographic Study. Spine. 2006;31:1388-1393.
*CAIPIRINHA=controlled aliasing in parallel imaging results in higher acceleration, FLASH=fast low angle shot, GRAPPA=generalized auto-calibrating partially parallel acquisition, IR=inversion recovery, T1W=T1-weighted.
‡ IR-TR of 3000 ms repeated at 4 inversion times: 100/600/1200/2800 ms.