3D Arterial Spin Labeling in breast cancer: A case study.
Thorsten Honroth1, Suzan Vreemann2, Marco Vicari1, Hendrik Laue1, Ritse Mann2, and Matthias G√ľnther1,3,4

1Fraunhofer MEVIS, Bremen, Germany, 2Radboud University Medical Center, Nijmegen, Netherlands, 3University of Bremen, Bremen, Germany, 4mediri GmbH, Heidelberg, Germany


A single-shot 3D arterial spin labeling (ASL) sequence has been developed and optimized for breast cancer imaging. In a case study, its ability to measure the perfusion of a tumor without contrast agents is demonstrated. The resulting ASL perfusion-weighted image of the tumor shows high correspondence with the subtraction image of the contrast-enhanced measurement.


MRI is of high importance in breast cancer imaging. Contrast-enhanced (CE) measurements can reveal the tumor perfusion and thus serve to classify and characterize lesions. However, especially in screening situations, repetitive administration of contrast agents should be avoided if possible1.

Arterial Spin Labeling (ASL) is an established technique for measuring perfusion without contrast agents in the brain2, but in other organs, ASL remains challenging. Only few groups have shown the feasibility of Arterial Spin Labeling (ASL) in the breast3-8 using either 2D single-slice or multi-slice imaging.

In this breast cancer case study, we present a fast 3D single-shot ASL sequence that is designed to provide high SNR and to cover a large volume within reasonable acquisition time.


The patient measurements for this case study have been performed at the Department of Radiology of Radboud University Medical Center, Nijmegen, Netherlands, on a Siemens Magnetom Skyra 3T system (Siemens Healthcare, Erlangen).

The pulsed ASL sequence (PASL) uses a FAIR9 labeling with a 3D-GRASE readout10. In an almost coronal orientation we acquire a volume with a 96x48x8 matrix and a voxel size of 3.6x3.6x4mm3 in single-shot mode. 80 label and control pairs are acquired within 7:36 min. A relatively long inflow time of TI=2000ms has been chosen to measure the tumor enhancement. Perfusion is not quantified but instead, the sequence is used to qualitatively specify lesions. Background suppression with 4 adiabatic inversion pulses11 has been optimized to minimize artifacts related to signal from fat and static tissue.

The slice-selective inversion volume of the FAIR labeling was chosen to be identical with the imaging volume, which means that only blood outside the imaging volume is labeled. Therefore, this volume needs to be positioned very carefully in order to label all inflowing blood (Fig.2). By keeping a small gap between chest wall and breast we ensure that blood is labeled in all feeding vessels.

Each image was acquired in single-shot mode, which makes the sequence robust against motion. Still, motion can also occur between label and control image as well as between different repetitions. Therefore, we manually excluded affected label and control pairs from the evaluation but we did not correct for between-repetition movement as the latter does not affect measured data significantly. Finally, the individual measurements were averaged.


The examined patient has a cystic carcinoma with a diameter of 3 cm in the right breast (Fig.1). The tumor tissue around the cystic part of the tumor is highly perfused as the CE subtraction images show.

12 label and control pairs of the ASL data have been corrupted by motion and removed manually before averaging.

In Fig.3 the CE image has been reformatted to match the ASL slices. For the tumor perfusion, the ASL perfusion-weighted image corresponds well to the CE image. When the ASL perfusion weighted image is reformatted to the CE image (Fig.4), the correspondence becomes even more obvious.


Using our approach it is possible to obtain perfusion images of breast lesions without contrast agent. However, a major drawback of the demonstrated sequence is that the tumor position must be known before scanning as the thickness of the volume does not offer full-breast coverage. A thicker volume could be acquired using multiple segments but also the FAIR labeling would hamper a complete imaging of the breast.

Furthermore, spatial resolution and SNR are inferior to CE sequences and might hide smaller lesions. In addition, vessels perpendicular to the slice orientation also appear bright in the subtraction images and thus might lead to false positive findings.

Finally, by applying this method to more subjects, parameters like the necessary number of measurements and the optimal inflow time (TI) must be optimized further.


We demonstrated a fast 3D ASL single-shot sequence which provides perfusion-weighted images of the tumor that show high correspondence with the CE subtraction image, but further optimization is required to make the technique clinically viable.


The research leading to these results has received funding from the European Union’s Seventh Framework Programme FP7 under grant agreement no’s 306088 and 601040.


1. Kanda et al., Radiology 276:228-232, 2015.

2. Alsop et al., MRM 73:102-116, 2015.

3. Zhu, Buonocore, MRM 50:966-75, 2003.

4. Li et al., Proc ISMRM 17:2130, 2009.

5. Wu et al., Proc ISMRM 15:2801, 2007.

6. Han et al., Proc ISMRM 18:2501, 2010.

7. Kawashima et al., JMRI 35:436-440, 2012.

8. Buchbender et al., Clin Radiol 68:e123-e127, 2013.

9. Kim, MRM 34:293–301, 2005.

10. Günther et al., MRM 54:491-498, 2005.

11. Mani et al., MRM 37:898-905, 1997.


Fig.1: Contrast-enhanced subtraction image in three orientations. The examined patient shows a cystic carcinoma in the right breast with a diameter of 3 cm.

Fig.2: The positioning of the ASL volume (blue overlay) relative to the contrast-enhanced image (orange) is shown in three orientations. Most of the tumor in the right breast is covered by the ASL volume.

Fig.3: Left: All 8 slices of the ASL perfusion-weighted image. 68 label/control pairs of 80 have been used for averaging. The tumor and vessels are visible. Right: The contrast-enhanced image reformatted to the ASL image. Both windows show the same slices.

Fig.4: The ASL perfusion weighted image (left) has been reformatted to the contrast-enhanced image (right).

Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)