001     286590
005     20240229155126.0
024 7 _ |a 10.1148/rycan.220127
|2 doi
024 7 _ |a pmid:38133553
|2 pmid
024 7 _ |a altmetric:157720332
|2 altmetric
037 _ _ |a DKFZ-2023-02807
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a Paech, Daniel
|0 P:(DE-He78)c6e31fb8f19e185e254174554a0cccfc
|b 0
|e First author
|u dkfz
245 _ _ |a Whole-Brain Intracellular pH Mapping of Gliomas Using High-Resolution 31P MR Spectroscopic Imaging at 7.0 T.
260 _ _ |a Oak Brook, IL
|c 2023
|b RSNA, Radiological Society of North America
336 7 _ |a article
|2 DRIVER
336 7 _ |a Output Types/Journal article
|2 DataCite
336 7 _ |a Journal Article
|b journal
|m journal
|0 PUB:(DE-HGF)16
|s 1703765476_2100
|2 PUB:(DE-HGF)
336 7 _ |a ARTICLE
|2 BibTeX
336 7 _ |a JOURNAL_ARTICLE
|2 ORCID
336 7 _ |a Journal Article
|0 0
|2 EndNote
500 _ _ |a #EA:E010#LA:E020#
520 _ _ |a Malignant tumors commonly exhibit a reversed pH gradient compared with normal tissue, with a more acidic extracellular pH and an alkaline intracellular pH (pHi). In this prospective study, pHi values in gliomas were quantified using high-resolution phosphorous 31 (31P) spectroscopic MRI at 7.0 T and were used to correlate pHi alterations with histopathologic findings. A total of 12 participants (mean age, 58 years ± 18 [SD]; seven male, five female) with histopathologically proven, newly diagnosed glioma were included between September 2018 and November 2019. The 31P spectroscopic MRI scans were acquired using a double-resonant 31P/1H phased-array head coil together with a three-dimensional (3D) 31P chemical shift imaging sequence (5.7-mL voxel volume) performed with a 7.0-T whole-body system. The 3D volumetric segmentations were performed for the whole-tumor volumes (WTVs); tumor subcompartments of necrosis, gadolinium enhancement, and nonenhancing T2 (NCE T2) hyperintensity; and normal-appearing white matter (NAWM), and pHi values were compared. Spearman correlation was used to assess association between pHi and the proliferation index Ki-67. For all study participants, mean pHi values were higher in the WTV (7.057 ± 0.024) compared with NAWM (7.006 ± 0.012; P < .001). In eight participants with high-grade gliomas, pHi was increased in all tumor subcompartments (necrosis, 7.075 ± 0.033; gadolinium enhancement, 7.075 ± 0.024; NCE T2 hyperintensity, 7.043 ± 0.015) compared with NAWM (7.004 ± 0.014; all P < .01). The pHi values of WTV positively correlated with Ki-67 (R2 = 0.74, r = 0.78, P = .001). In conclusion, 31P spectroscopic MRI at 7.0 T enabled high-resolution quantification of pHi in gliomas, with pHi alteration associated with the Ki-67 proliferation index, and may aid in diagnosis and treatment monitoring. Keywords: 31P MRSI, pH, Glioma, Glioblastoma, Ultra-High-Field MRI, Imaging Biomarker, 7 Tesla Supplemental material is available for this article. © RSNA, 2023.
536 _ _ |a 315 - Bildgebung und Radioonkologie (POF4-315)
|0 G:(DE-HGF)POF4-315
|c POF4-315
|f POF IV
|x 0
588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: inrepo02.dkfz.de
650 _ 7 |a 31P MRSI
|2 Other
650 _ 7 |a 7 Tesla
|2 Other
650 _ 7 |a Glioblastoma
|2 Other
650 _ 7 |a Glioma
|2 Other
650 _ 7 |a Imaging Biomarker
|2 Other
650 _ 7 |a Ultra-High-Field MRI
|2 Other
650 _ 7 |a pH
|2 Other
650 _ 7 |a Contrast Media
|2 NLM Chemicals
650 _ 7 |a Gadolinium
|0 AU0V1LM3JT
|2 NLM Chemicals
650 _ 7 |a Ki-67 Antigen
|2 NLM Chemicals
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Contrast Media
|2 MeSH
650 _ 2 |a Prospective Studies
|2 MeSH
650 _ 2 |a Gadolinium
|2 MeSH
650 _ 2 |a Ki-67 Antigen
|2 MeSH
650 _ 2 |a Brain Neoplasms: diagnostic imaging
|2 MeSH
650 _ 2 |a Glioma: diagnostic imaging
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging: methods
|2 MeSH
650 _ 2 |a Brain: pathology
|2 MeSH
650 _ 2 |a Necrosis
|2 MeSH
650 _ 2 |a Hydrogen-Ion Concentration
|2 MeSH
700 1 _ |a Weckesser, Nina
|0 P:(DE-He78)e9deaa758e8af7948e97a28aaf0bb7d1
|b 1
|e First author
|u dkfz
700 1 _ |a Franke, Vanessa
|0 P:(DE-He78)aa7c5ddf01ae4204a9724ad52583db88
|b 2
|u dkfz
700 1 _ |a Breitling, Johannes
|0 P:(DE-He78)8a54e49721e8ba58de289702bad026d9
|b 3
700 1 _ |a Görke, Steffen
|0 P:(DE-He78)802bc375f8583fdb15ccd0abf30c1bfe
|b 4
700 1 _ |a Deike-Hofmann, Katerina
|0 P:(DE-He78)34255b119acbf293af0239d8f85ce24e
|b 5
700 1 _ |a Wick, Antje
|0 0000-0003-0020-6386
|b 6
700 1 _ |a Scherer, Moritz
|0 0000-0003-1203-9351
|b 7
700 1 _ |a Unterberg, Andreas
|b 8
700 1 _ |a Wick, Wolfgang
|b 9
700 1 _ |a Bendszus, Martin
|b 10
700 1 _ |a Bachert, Peter
|0 P:(DE-He78)29b2f01310f7022916255ddba2750f9b
|b 11
|u dkfz
700 1 _ |a Ladd, Mark
|0 P:(DE-He78)022611a2317e4de40fd912e0a72293a8
|b 12
|u dkfz
700 1 _ |a Schlemmer, Heinz-Peter
|0 P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec
|b 13
|u dkfz
700 1 _ |a Korzowski, Andreas
|0 P:(DE-He78)577a5c61f44b8023e229610afbc7cd4e
|b 14
|e Last author
|u dkfz
773 _ _ |a 10.1148/rycan.220127
|g Vol. 6, no. 1, p. e220127
|0 PERI:(DE-600)2986040-4
|n 1
|p e220127
|t Radiology / Imaging cancer
|v 6
|y 2024
|x 2638-616X
909 C O |o oai:inrepo02.dkfz.de:286590
|p VDB
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 0
|6 P:(DE-He78)c6e31fb8f19e185e254174554a0cccfc
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 1
|6 P:(DE-He78)e9deaa758e8af7948e97a28aaf0bb7d1
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 2
|6 P:(DE-He78)aa7c5ddf01ae4204a9724ad52583db88
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 3
|6 P:(DE-He78)8a54e49721e8ba58de289702bad026d9
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 4
|6 P:(DE-He78)802bc375f8583fdb15ccd0abf30c1bfe
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 5
|6 P:(DE-He78)34255b119acbf293af0239d8f85ce24e
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 11
|6 P:(DE-He78)29b2f01310f7022916255ddba2750f9b
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 12
|6 P:(DE-He78)022611a2317e4de40fd912e0a72293a8
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 13
|6 P:(DE-He78)3d04c8fee58c9ab71f62ff80d06b6fec
910 1 _ |a Deutsches Krebsforschungszentrum
|0 I:(DE-588b)2036810-0
|k DKFZ
|b 14
|6 P:(DE-He78)577a5c61f44b8023e229610afbc7cd4e
913 1 _ |a DE-HGF
|b Gesundheit
|l Krebsforschung
|1 G:(DE-HGF)POF4-310
|0 G:(DE-HGF)POF4-315
|3 G:(DE-HGF)POF4
|2 G:(DE-HGF)POF4-300
|4 G:(DE-HGF)POF
|v Bildgebung und Radioonkologie
|x 0
914 1 _ |y 2023
915 _ _ |a JCR
|0 StatID:(DE-HGF)0100
|2 StatID
|b RADIOL-IMAG CANCER : 2022
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0200
|2 StatID
|b SCOPUS
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0300
|2 StatID
|b Medline
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0320
|2 StatID
|b PubMed Central
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0199
|2 StatID
|b Clarivate Analytics Master Journal List
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1050
|2 StatID
|b BIOSIS Previews
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)1190
|2 StatID
|b Biological Abstracts
|d 2023-08-24
915 _ _ |a WoS
|0 StatID:(DE-HGF)0112
|2 StatID
|b Emerging Sources Citation Index
|d 2023-08-24
915 _ _ |a DBCoverage
|0 StatID:(DE-HGF)0150
|2 StatID
|b Web of Science Core Collection
|d 2023-08-24
915 _ _ |a IF < 5
|0 StatID:(DE-HGF)9900
|2 StatID
|d 2023-08-24
920 2 _ |0 I:(DE-He78)E020-20160331
|k E020
|l E020 Med. Physik in der Radiologie
|x 0
920 1 _ |0 I:(DE-He78)E010-20160331
|k E010
|l E010 Radiologie
|x 0
920 1 _ |0 I:(DE-He78)E020-20160331
|k E020
|l E020 Med. Physik in der Radiologie
|x 1
920 0 _ |0 I:(DE-He78)E010-20160331
|k E010
|l E010 Radiologie
|x 0
980 _ _ |a journal
980 _ _ |a VDB
980 _ _ |a I:(DE-He78)E010-20160331
980 _ _ |a I:(DE-He78)E020-20160331
980 _ _ |a UNRESTRICTED


LibraryCollectionCLSMajorCLSMinorLanguageAuthor
Marc 21