1
|
Maurer GD, Tichy J, Harter PN, Nöth U, Weise L, Quick-Weller J, Deichmann R, Steinbach JP, Bähr O, Hattingen E. Matching Quantitative MRI Parameters with Histological Features of Treatment-Naïve IDH Wild-Type Glioma. Cancers (Basel) 2021; 13:cancers13164060. [PMID: 34439213 PMCID: PMC8392045 DOI: 10.3390/cancers13164060] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 08/05/2021] [Accepted: 08/10/2021] [Indexed: 11/16/2022] Open
Abstract
Quantitative MRI allows to probe tissue properties by measuring relaxation times and may thus detect subtle changes in tissue composition. In this work we analyzed different relaxation times (T1, T2, T2* and T2') and histological features in 321 samples that were acquired from 25 patients with newly diagnosed IDH wild-type glioma. Quantitative relaxation times before intravenous application of gadolinium-based contrast agent (GBCA), T1 relaxation time after GBCA as well as the relative difference between T1 relaxation times pre-to-post GBCA (T1rel) were compared with histopathologic features such as the presence of tumor cells, cell and vessel density, endogenous markers for hypoxia and cell proliferation. Image-guided stereotactic biopsy allowed for the attribution of each tissue specimen to its corresponding position in the respective relaxation time map. Compared to normal tissue, T1 and T2 relaxation times and T1rel were prolonged in samples containing tumor cells. The presence of vascular proliferates was associated with higher T1rel values. Immunopositivity for lactate dehydrogenase A (LDHA) involved slightly longer T1 relaxation times. However, low T2' values, suggesting high amounts of deoxyhemoglobin, were found in samples with elevated vessel densities, but not in samples with increased immunopositivity for LDHA. Taken together, some of our observations were consistent with previous findings but the correlation of quantitative MRI and histologic parameters did not confirm all our pathophysiology-based assumptions.
Collapse
Affiliation(s)
- Gabriele D. Maurer
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Correspondence:
| | - Julia Tichy
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Patrick N. Harter
- Institute of Neurology (Edinger Institute), Goethe University Hospital, 60528 Frankfurt am Main, Germany;
- German Cancer Consortium (DKTK), Partner Site Frankfurt/Mainz, 60590 Frankfurt am Main, Germany
- German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany
- Frankfurt Cancer Institute (FCI), 60596 Frankfurt am Main, Germany
| | - Ulrike Nöth
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Lutz Weise
- Division of Neurosurgery, Dalhousie University Halifax, Halifax, NS B3H 4R2, Canada;
| | - Johanna Quick-Weller
- Department of Neurosurgery, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
| | - Ralf Deichmann
- Brain Imaging Center, Goethe University, 60528 Frankfurt am Main, Germany; (U.N.); (R.D.)
| | - Joachim P. Steinbach
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
| | - Oliver Bähr
- Senckenberg Institute of Neurooncology, Goethe University Hospital, 60528 Frankfurt am Main, Germany; (J.T.); (J.P.S.); (O.B.)
- Department of Neurology, Klinikum Aschaffenburg-Alzenau, 63739 Aschaffenburg, Germany
| | - Elke Hattingen
- Institute of Neuroradiology, Goethe University Hospital, 60528 Frankfurt am Main, Germany;
| |
Collapse
|
2
|
Cluceru J, Nelson SJ, Wen Q, Phillips JJ, Shai A, Molinaro AM, Alcaide-Leon P, Olson MP, Nair D, LaFontaine M, Chunduru P, Villanueva-Meyer JE, Cha S, Chang SM, Berger MS, Lupo JM. Recurrent tumor and treatment-induced effects have different MR signatures in contrast enhancing and non-enhancing lesions of high-grade gliomas. Neuro Oncol 2021; 22:1516-1526. [PMID: 32319527 DOI: 10.1093/neuonc/noaa094] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
BACKGROUND Differentiating treatment-induced injury from recurrent high-grade glioma is an ongoing challenge in neuro-oncology, in part due to lesion heterogeneity. This study aimed to determine whether different MR features were relevant for distinguishing recurrent tumor from the effects of treatment in contrast-enhancing lesions (CEL) and non-enhancing lesions (NEL). METHODS This prospective study analyzed 291 tissue samples (222 recurrent tumor, 69 treatment-effect) with known coordinates on imaging from 139 patients who underwent preoperative 3T MRI and surgery for a suspected recurrence. 8 MR parameter values were tested from perfusion-weighted, diffusion-weighted, and MR spectroscopic imaging at each tissue sample location for association with histopathological outcome using generalized estimating equation models for CEL and NEL tissue samples. Individual cutoff values were evaluated using receiver operating characteristic curve analysis with 5-fold cross-validation. RESULTS In tissue samples obtained from CEL, elevated relative cerebral blood volume (rCBV) was associated with the presence of recurrent tumor pathology (P < 0.03), while increases in normalized choline (nCho) and choline-to-NAA index (CNI) were associated with the presence of recurrent tumor pathology in NEL tissue samples (P < 0.008). A mean CNI cutoff value of 2.7 had the highest performance, resulting in mean sensitivity and specificity of 0.61 and 0.81 for distinguishing treatment-effect from recurrent tumor within the NEL. CONCLUSION Although our results support prior work that underscores the utility of rCBV in distinguishing the effects of treatment from recurrent tumor within the contrast enhancing lesion, we found that metabolic parameters may be better at differentiating recurrent tumor from treatment-related changes in the NEL of high-grade gliomas.
Collapse
Affiliation(s)
- Julia Cluceru
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Sarah J Nelson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Qiuting Wen
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Joanna J Phillips
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California.,Department of Neurological Surgery, University of California San Francisco, San Francisco, California.,Department of Pathology, University of California San Francisco, San Francisco, California
| | - Anny Shai
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Annette M Molinaro
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Paula Alcaide-Leon
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Marram P Olson
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Devika Nair
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Marisa LaFontaine
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Pranathi Chunduru
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Javier E Villanueva-Meyer
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Soonmee Cha
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| | - Susan M Chang
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Mitchel S Berger
- Department of Neurological Surgery, University of California San Francisco, San Francisco, California
| | - Janine M Lupo
- Department of Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, California
| |
Collapse
|