Automatic acquisition of dynamic susceptibility contrast and dynamic contrast enhanced images using a single contrast dose
Yufen Chen1 and Todd B Parrish1

1Radiology, Northwestern University, Chicago, IL, United States

Synopsis

In clinical settings, dynamic susceptibility contrast (DSC) and dynamic contrast enhanced (DCE) data are rarely acquired together as both require a full single dose for optimal contrast-to-noise-ratio (CNR). However, both techniques offer complementary information that aid in the assessment of tumors. Current double acquisition methods acquire the DCE scan first with a half dose to minimize leakage effects in the subsequent DSC scan, compromising both scans. Here, we demonstrate the feasibility of an automatically switching DSC-DCE scan sequence by monitoring the signal intensity of the DSC scan, allowing acquisition of both datasets with a single contrast dose.

Purpose

Automatic acquisition of both DSC and DCE data with a single dose of MR contrast.

Methods

Images were acquired in 3 patients on a 1.5T Siemens Espree scanner. Prior to contrast injection, gradient echo images for intrinsic T1 mapping utilized in DCE quantification were acquired at flip angles 2°, 7°, 10°, 15° and 25° with 10 dynamic scans each and 2 averages (see below for other parameters). A baseline DCE acquisition at 12° was also acquired. The DSC images were acquired using gradient-echo echo planar imaging (GR-EPI) with TR/TE=1500ms/35ms, resolution=2.1x2.1mm2, 13 slices of 5mm thickness (2.5mm gap), 50 dynamic scans. 0.1mmol/kg body weight of gadolinium was injected during the 8th dynamic scan. This was followed by the T1-weighted gradient echo DCE scan with the following parameters: TR/TE 3.9/1.5ms, flip angle=12°, resolution=1.8x0.9mm2, 26 slices of 3mm thickness, 80 dynamic scans.

The innovation implemented was signal surveillance during the DSC acquisition to indicate when to switch from the DSC to the DCE scan. The DSC sequence was modified to receive real time feedback from the image reconstruction environment (ICE), which monitors the derivative of the global signal intensity of an imaging slice. The first 10 images were used to generate the baseline mean and standard deviation of the derivative. The following time points were determined in real time:

1) Start of first bolus passage (iStart): when the derivative of the signal is smaller than baseline mean - 3x baseline standard deviation

2) Minimum point (iMinimum): when the derivative becomes positive after iStart

3) Stop point (iStop): Either when the derivative becomes negative after iMinimum or when the number of time points exceeds iMinimum+3x(iMinimum-iStart). The second condition provides a strict stop point in the event of severe T2 leakage effects where the signal remains close to iMinimum. This criterion is based on previous findings in 24 tumor patients1.

Once iStop is defined, a feedback signal is sent to stop the DSC acquisition and automatically start the DCE acquisition. The scanner operator does not have to do anything except start the contrast injection.

Results

The sequence successfully switched from the DSC acquisition at the stop point to the DCE scan without manual intervention in all subjects. The DSC global bolus plot with iStart, iMinimum and iStop (highlighted in red) detected by the sequence is shown in Figure 1. Figure 2 shows the concatenated timecourses of the pre-contrast gradient echo scan (blue), the DSC scan (green) and the DCE scan (purple) extracted from regions of interest placed in the low grade tumor (red) and healthy tissue (yellow). The DSC and post contrast DCE signals were scaled to match the precontrast signal level to illustrate the acquisition details. Notice the similarity between the DSC timecourses of healthy tissue and global bolus plot, demonstrating the proposed monitoring methodology’s insensitivity to leakage effects in DSC.

Discussion

In this study, we demonstrate the feasibility of automatically switching from DSC to DCE acquisition with a single contrast dose using real-time monitoring of the global signal intensity of the DSC data acquisition. Although the data presented were acquired at 1.5T, the technique is not limited by field strength. The DSC scan provides an estimate of the arterial input function, which is critical for both DSC and DCE quantification. Currently the vendor quantification package for DCE uses an assumed arterial input function (AIF) for different flow situations. The preceding DSC scan in our proposed method provides a patient-specific AIF that will improve the accuracy of the DCE quantification process. Another feature of the proposed technique is its relative insensitivity to leakage effects as the DSC stop criterion is based on signal intensity from an entire slice. Even if the tumor region suffers from severe leakage effects, the mean slice signal should be minimally affected by the tumor, allowing the algorithm to successfully capture the entire AIF. In the rare situation when the algorithm fails, the built-in hard stop timepoint ensures that the DCE scan will not be delayed significantly. Future efforts will focus on automating the combined analysis of both datasets immediately after data acquisition with minimal operator intervention and incorporating more advanced modeling to correct for leakage effects in the DSC data.

Conclusion

We have successfully demonstrated the feasibility of an automatically switching DSC-DCE scan sequence that allows optimal acquisition of both types of data using a single full-dose of contrast.

Acknowledgements

The authors wish to acknowledge Dr. Haris Saybasili for helpful discussions in implementing this technique.

References

1. Parrish T CG, Varadheeswaran J, Wang X, Chen Y. Measurement of perfusion and permeability using a single full dose contrast injection. Proceedings of the Organization of Human Brain Mapping 2014

Figures

Figure 1. Representative DSC global bolus plot with the three timepoints: iStart, iMinimum and iStop, detected by the sequence highlighted in red.

Figure 2. a) Location of tumor (red) and healthy (yellow) tissue regions of interest (ROI) on a DCE image. b) Concatenated timecourses of precontrast DCE (blue), DSC (green) and postcontrast DCE (purple) from healthy ROI. c) Concatenated timecourses of precontrast DCE (blue), DSC (green) and postcontrast DCE (purple) from tumor ROI.



Proc. Intl. Soc. Mag. Reson. Med. 24 (2016)
4186