TY  - JOUR
AU  - Schüre, Jan-Rüdiger
AU  - Rajput, Junaid
AU  - Shrestha, Manoj
AU  - Deichmann, Ralf
AU  - Hattingen, Elke
AU  - Maier, Andreas
AU  - Nagel, Armin M
AU  - Dörfler, Arnd
AU  - Steidl, Eike
AU  - Zaiss, Moritz
TI  - Toward Noninvasive High-Resolution In Vivo pH Mapping in Brain Tumors by 31P-Informed deepCEST MRI.
JO  - NMR in biomedicine
VL  - 38
IS  - 6
SN  - 0952-3480
CY  - New York, NY
PB  - Wiley
M1  - DKFZ-2025-01035
SP  - e70060
PY  - 2025
AB  - The intracellular pH (pHi) is critical for understanding various pathologies, including brain tumors. While conventional pHi measurement through 31P-MRS suffers from low spatial resolution and long scan times, 1H-based APT-CEST imaging offers higher resolution with shorter scan times. This study aims to directly predict 31P-pHi maps from CEST data by using a fully connected neuronal network. Fifteen tumor patients were scanned on a 3-T Siemens PRISMA scanner and received 1H-based CEST and T1 measurement, as well as 31P-MRS. A neural network was trained voxel-wise on CEST and T1 data to predict 31P-pHi values, using data from 11 patients for training and 4 for testing. The predicted pHi maps were additionally down-sampled to the original the 31P-pHi resolution, to be able to calculate the RMSE and analyze the correlation, while higher resolved predictions were compared with conventional CEST metrics. The results demonstrated a general correspondence between the predicted deepCEST pHi maps and the measured 31P-pHi in test patients. However, slight discrepancies were also observed, with a RMSE of 0.04 pH units in tumor regions. High-resolution predictions revealed tumor heterogeneity and features not visible in conventional CEST data, suggesting the model captures unique pH information and is not simply a T1 segmentation. The deepCEST pHi neural network enables the APT-CEST hidden pH-sensitivity and offers pHi maps with higher spatial resolution in shorter scan time compared with 31P-MRS. Although this approach is constrained by the limitations of the acquired data, it can be extended with additional CEST features for future studies, thereby offering a promising approach for 3D pH imaging in a clinical environment.
KW  - Humans
KW  - Magnetic Resonance Imaging
KW  - Hydrogen-Ion Concentration
KW  - Brain Neoplasms: diagnostic imaging
KW  - Male
KW  - Female
KW  - Middle Aged
KW  - Adult
KW  - Neural Networks, Computer
KW  - 31P‐MRS (Other)
KW  - AI (Other)
KW  - APTw (Other)
KW  - CEST (Other)
KW  - brain tumor (Other)
KW  - deep learning (Other)
KW  - intracellular pH (Other)
KW  - pHi (Other)
LB  - PUB:(DE-HGF)16
C6  - pmid:40374188
C2  - pmc:PMC12081166
DO  - DOI:10.1002/nbm.70060
UR  - https://inrepo02.dkfz.de/record/301493
ER  -