This poster is published under an
open license. Please read the
disclaimer for further details.
Keywords:
Ear / Nose / Throat, Oncology, Head and neck, PET-MR, Diagnostic procedure, Molecular imaging, Cancer, Tissue characterisation
Authors:
M. Gawlitza, S. Purz, A. Boehm, H. Barthel, T. Kahn, O. Sabri, P. Stumpp; Leipzig/DE
DOI:
10.1594/ecr2014/C-0264
Conclusion
The current study demonstrates that,
by integrating advanced MRI techniques for tissue characterisation into a simultaneous PET/MRI protocol,
the in vivo assessment of glucose metabolism,
tissue cell density and microcirculatory parameters of the tumour’s vascular bed is feasible.
It is demonstrated that – using PET/MRI - complex interactions between glucose metabolism and microcirculation (expressed by correlations between SUV and Ktrans / kep),
between glucose uptake and cellular density (depicted by correlations between SUV and ADC) and between cellularity and volume of the extravascular space (estimated by the correlation between ADC and ve) can be displayed.
As all correlations between the different molecular modalities were at best moderate,
their combined acquisition seems to provide complementary and not redundant information; yet,
they seem to be connected to a certain degree.
In the future,
this could be of special interest for treatment planning and prognostic stratification.
DWI and T1-DCE as well as 18F-FDG-PET were proven to be suitable for this purpose in patients with HNSCC prior to radiochemotherapy [8]; a satisfactory therapy response and a better prognosis is thought to be related to (a) higher Ktrans[9],
(b) higher ADCmean and (c) lower SUVmax values [9].
During successful radiochemotherapy,
ADC values are increasing [10],
whereas 18F-FDG uptake and Ktrans are known to decrease [11].
With PET/MRI and a combined acquisition of numerous parameters,
further studies to investigate the most suitable modality for assessment and prediction of therapy response are possible.
Moreover,
by imaging only,
the combination of a number of molecular imaging parameters could characterize the tumour biology and (sub)cellular tissue properties and contribute to the planning and adaptation of treatment plans with the aim of optimising patient outcomes.