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Metabolites
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Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging
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Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging

A special issue of Metabolites (ISSN 2218-1989). This special issue belongs to the section "Metabolomic Profiling Technology".

Deadline for manuscript submissions: closed (30 November 2022) | Viewed by 9538

Special Issue Editors

Dr. Shivanand M. Pudakalakatti

E-Mail Website
Guest Editor
Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, 1881 East Road, Houston, TX, USA
Interests: metabolomics; NMR spectroscopy; MRI; hyperpolarized MRI; MRI contrast agents; cancer diagnosis; metabolic imaging; molecular imaging; cancer metabolism; PET; CT; dynamic nuclear polarization
Special Issues, Collections and Topics in MDPI journals
Dr. Pratip K. Bhattacharya

E-Mail Website
Guest Editor
Department of Cancer Systems Imaging, University of Texas MD Anderson Cancer Center, Houston, TX, USA
Interests: metabolomics; NMR spectroscopy; MRI; hyperpolarized MRI; MRI contrast agents; cancer diagnosis; metabolic imaging; molecular imaging; cancer metabolism; PET; CT; dynamic nuclear polarization
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In the last decade, cancer metabolism has been one of the avidly researched areas of study. Cancer cells alter their metabolism to meet the energy requirements for their proliferation and survival. It is well known that an altered metabolism is one of the hallmarks of cancer, and harnessing this feature will have an important role in investigations of the diagnosis, therapeutic intervention, and finally, the cure for cancer. It is very important to shed light on ongoing research into the tumor metabolism, unmet needs, and future challenges.  Therefore, this Special Issue aims to further our understanding of the tumor metabolism. Articles and reviews that are related to understanding the metabolism in cancer and that utilize magnetic resonance as an analytical tool are welcome for this Special Issue.

Dr. Shivanand M. Pudakalakatti
Dr. Pratip K. Bhattacharya
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Metabolites is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • cancer metabolism
  • nuclear magnetic resonance (NMR)
  • magnetic resonance imaging (MRI)
  • metabolomics
  • hyperpolarized MRI
  • artificial intelligence
  • metabolomics
  • early diagnosis
  • therapeutic intervention

Published Papers (5 papers)

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Research

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17 pages, 3797 KiB  
Article
Ensemble Learning for Breast Cancer Lesion Classification: A Pilot Validation Using Correlated Spectroscopic Imaging and Diffusion-Weighted Imaging
by Ajin Joy, Marlene Lin, Melissa Joines, Andres Saucedo, Stephanie Lee-Felker, Jennifer Baker, Aichi Chien, Uzay Emir, Paul M. Macey and M. Albert Thomas
Metabolites 2023, 13(7), 835; https://doi.org/10.3390/metabo13070835 - 11 Jul 2023
Viewed by 1114
Abstract
The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional echo-planar correlated spectroscopic imaging (5D EP-COSI) and [...] Read more.
The main objective of this work was to evaluate the application of individual and ensemble machine learning models to classify malignant and benign breast masses using features from two-dimensional (2D) correlated spectroscopy spectra extracted from five-dimensional echo-planar correlated spectroscopic imaging (5D EP-COSI) and diffusion-weighted imaging (DWI). Twenty-four different metabolite and lipid ratios with respect to diagonal fat peaks (1.4 ppm, 5.4 ppm) from 2D spectra, and water and fat peaks (4.7 ppm, 1.4 ppm) from one-dimensional non-water-suppressed (NWS) spectra were used as the features. Additionally, water fraction, fat fraction and water-to-fat ratios from NWS spectra and apparent diffusion coefficients (ADC) from DWI were included. The nine most important features were identified using recursive feature elimination, sequential forward selection and correlation analysis. XGBoost (AUC: 93.0%, Accuracy: 85.7%, F1-score: 88.9%, Precision: 88.2%, Sensitivity: 90.4%, Specificity: 84.6%) and GradientBoost (AUC: 94.3%, Accuracy: 89.3%, F1-score: 90.7%, Precision: 87.9%, Sensitivity: 94.2%, Specificity: 83.4%) were the best-performing models. Conventional biomarkers like choline, myo-Inositol, and glycine were statistically significant predictors. Key features contributing to the classification were ADC, 2D diagonal peaks at 0.9 ppm, 2.1 ppm, 3.5 ppm, and 5.4 ppm, cross peaks between 1.4 and 0.9 ppm, 4.3 and 4.1 ppm, 2.3 and 1.6 ppm, and the triglyceryl–fat cross peak. The results highlight the contribution of the 2D spectral peaks to the model, and they demonstrate the potential of 5D EP-COSI for early breast cancer detection. Full article
(This article belongs to the Special Issue Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging)
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18 pages, 1852 KiB  
Article
Efficient SABRE-SHEATH Hyperpolarization of Potent Branched-Chain-Amino-Acid Metabolic Probe [1-13C]ketoisocaproate
by Isaiah Adelabu, Md Raduanul H. Chowdhury, Shiraz Nantogma, Clementinah Oladun, Firoz Ahmed, Lukas Stilgenbauer, Marianna Sadagurski, Thomas Theis, Boyd M. Goodson and Eduard Y. Chekmenev
Metabolites 2023, 13(2), 200; https://doi.org/10.3390/metabo13020200 - 29 Jan 2023
Cited by 5 | Viewed by 2882
Abstract
Efficient 13C hyperpolarization of ketoisocaproate is demonstrated in natural isotopic abundance and [1-13C]enriched forms via SABRE-SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei). Parahydrogen, as the source of nuclear spin order, and ketoisocaproate undergo simultaneous [...] Read more.
Efficient 13C hyperpolarization of ketoisocaproate is demonstrated in natural isotopic abundance and [1-13C]enriched forms via SABRE-SHEATH (Signal Amplification By Reversible Exchange in SHield Enables Alignment Transfer to Heteronuclei). Parahydrogen, as the source of nuclear spin order, and ketoisocaproate undergo simultaneous chemical exchange with an Ir-IMes-based hexacoordinate complex in CD3OD. SABRE-SHEATH enables spontaneous polarization transfer from parahydrogen-derived hydrides to the 13C nucleus of transiently bound ketoisocaproate. 13C polarization values of up to 18% are achieved at the 1-13C site in 1 min in the liquid state at 30 mM substrate concentration. The efficient polarization build-up becomes possible due to favorable relaxation dynamics. Specifically, the exponential build-up time constant (14.3 ± 0.6 s) is substantially lower than the corresponding polarization decay time constant (22.8 ± 1.2 s) at the optimum polarization transfer field (0.4 microtesla) and temperature (10 °C). The experiments with natural abundance ketoisocaproate revealed polarization level on the 13C-2 site of less than 1%—i.e., one order of magnitude lower than that of the 1-13C site—which is only partially due to more-efficient relaxation dynamics in sub-microtesla fields. We rationalize the overall much lower 13C-2 polarization efficiency in part by less favorable catalyst-binding dynamics of the C-2 site. Pilot SABRE experiments at pH 4.0 (acidified sample) versus pH 6.1 (unaltered sodium [1-13C]ketoisocaproate) reveal substantial modulation of SABRE-SHEATH processes by pH, warranting future systematic pH titration studies of ketoisocaproate, as well as other structurally similar ketocarboxylate motifs including pyruvate and alpha-ketoglutarate, with the overarching goal of maximizing 13C polarization levels in these potent molecular probes. Finally, we also report on the pilot post-mortem use of HP [1-13C]ketoisocaproate in a euthanized mouse, demonstrating that SABRE-hyperpolarized 13C contrast agents hold promise for future metabolic studies. Full article
(This article belongs to the Special Issue Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging)
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14 pages, 6055 KiB  
Article
Noninvasive Delineation of Glioma Infiltration with Combined 7T Chemical Exchange Saturation Transfer Imaging and MR Spectroscopy: A Diagnostic Accuracy Study
by Yifan Yuan, Yang Yu, Yu Guo, Yinghua Chu, Jun Chang, Yicheng Hsu, Patrick Alexander Liebig, Ji Xiong, Wenwen Yu, Danyang Feng, Baofeng Yang, Liang Chen, He Wang, Qi Yue and Ying Mao
Metabolites 2022, 12(10), 901; https://doi.org/10.3390/metabo12100901 - 24 Sep 2022
Cited by 6 | Viewed by 1919
Abstract
For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST [...] Read more.
For precise delineation of glioma extent, amino acid PET is superior to conventional MR imaging. Since metabolic MR sequences such as chemical exchange saturation transfer (CEST) imaging and MR spectroscopy (MRS) were developed, we aimed to evaluate the diagnostic accuracy of combined CEST and MRS to predict glioma infiltration. Eighteen glioma patients of different tumor grades were enrolled in this study; 18F-fluoroethyltyrosine (FET)-PET, amide proton transfer CEST at 7 Tesla(T), MRS and conventional MR at 3T were conducted preoperatively. Multi modalities and their association were evaluated using Pearson correlation analysis patient-wise and voxel-wise. Both CEST (R = 0.736, p < 0.001) and MRS (R = 0.495, p = 0.037) correlated with FET-PET, while the correlation between CEST and MRS was weaker. In subgroup analysis, APT values were significantly higher in high grade glioma (3.923 ± 1.239) and IDH wildtype group (3.932 ± 1.264) than low grade glioma (3.317 ± 0.868, p < 0.001) or IDH mutant group (3.358 ± 0.847, p < 0.001). Using high FET uptake as the standard, the CEST/MRS combination (AUC, 95% CI: 0.910, 0.907–0.913) predicted tumor infiltration better than CEST (0.812, 0.808–0.815) or MRS (0.888, 0.885–0.891) alone, consistent with contrast-enhancing and T2-hyperintense areas. Probability maps of tumor presence constructed from the CEST/MRS combination were preliminarily verified by multi-region biopsies. The combination of 7T CEST/MRS might serve as a promising non-radioactive alternative to delineate glioma infiltration, thus reshaping the guidance for tumor resection and irradiation. Full article
(This article belongs to the Special Issue Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging)
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Review

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17 pages, 1684 KiB  
Review
Enhancing Cancer Diagnosis with Real-Time Feedback: Tumor Metabolism through Hyperpolarized 1-13C Pyruvate MRSI
by Gaurav Sharma, José S. Enriquez, Ryan Armijo, Muxin Wang, Pratip Bhattacharya and Shivanand Pudakalakatti
Metabolites 2023, 13(5), 606; https://doi.org/10.3390/metabo13050606 - 28 Apr 2023
Cited by 1 | Viewed by 1662
Abstract
This review article discusses the potential of hyperpolarized (HP) 13C magnetic resonance spectroscopic imaging (MRSI) as a noninvasive technique for identifying altered metabolism in various cancer types. Hyperpolarization significantly improves the signal-to-noise ratio for the identification of 13C-labeled metabolites, enabling dynamic [...] Read more.
This review article discusses the potential of hyperpolarized (HP) 13C magnetic resonance spectroscopic imaging (MRSI) as a noninvasive technique for identifying altered metabolism in various cancer types. Hyperpolarization significantly improves the signal-to-noise ratio for the identification of 13C-labeled metabolites, enabling dynamic and real-time imaging of the conversion of [1-13C] pyruvate to [1-13C] lactate and/or [1-13C] alanine. The technique has shown promise in identifying upregulated glycolysis in most cancers, as compared to normal cells, and detecting successful treatment responses at an earlier stage than multiparametric MRI in breast and prostate cancer patients. The review provides a concise overview of the applications of HP [1-13C] pyruvate MRSI in various cancer systems, highlighting its potential for use in preclinical and clinical investigations, precision medicine, and long-term studies of therapeutic response. The article also discusses emerging frontiers in the field, such as combining multiple metabolic imaging techniques with HP MRSI for a more comprehensive view of cancer metabolism, and leveraging artificial intelligence to develop real-time, actionable biomarkers for early detection, assessing aggressiveness, and interrogating the early efficacy of therapies. Full article
(This article belongs to the Special Issue Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging)
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Other

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11 pages, 2305 KiB  
Systematic Review
Prognostic Value of Choline and Other Metabolites Measured Using 1H-Magnetic Resonance Spectroscopy in Gliomas: A Meta-Analysis and Systemic Review
by Yixin Shi, Delin Liu, Ziren Kong, Qianshu Liu, Hao Xing, Yuekun Wang, Yu Wang and Wenbin Ma
Metabolites 2022, 12(12), 1219; https://doi.org/10.3390/metabo12121219 - 5 Dec 2022
Cited by 1 | Viewed by 1309
Abstract
Glioma is the most prevalent primary central nervous system malignant tumor, with high heterogeneity observed among different grades; therefore, non-invasive prediction of prognosis could improve the clinical management of patients with glioma. 1H-magnetic resonance spectroscopy (MRS) can estimate metabolite levels non-invasively. Multiple [...] Read more.
Glioma is the most prevalent primary central nervous system malignant tumor, with high heterogeneity observed among different grades; therefore, non-invasive prediction of prognosis could improve the clinical management of patients with glioma. 1H-magnetic resonance spectroscopy (MRS) can estimate metabolite levels non-invasively. Multiple studies have investigated its prognostic value in gliomas; however, no consensus has been reached. PubMed and Embase databases were searched up to 20 October 2022 to identify studies investigating the prognostic value of metabolites using 1H-MRS in patients with glioma. Heterogeneity across studies was evaluated using the Q and I2 tests, and a fixed- or random-effects model was used to estimate the combined overall hazard ratio (HR). Funnel plots and Begg tests were used to assess publication bias. Higher choline levels were associated with shorter overall survival (HR = 2.69, 95% CI, 1.92–2.99; p < 0.001) and progression-free survival (HR = 2.20, 95% CI, 1.16–4.17; p = 0.02) in all patients; however, in pediatric gliomas, it showed no significant correlation with overall survival (HR = 1.60, 95% CI, 0.97–2.64; p = 0.06). The estimated choline level by 1H-MRS could be used to non-invasively predict the prognosis of patients with adult gliomas, and more studies are needed to evaluate the prognostic value of other metabolites. Full article
(This article belongs to the Special Issue Interrogation of Tumor Metabolism Employing Magnetic Resonance Spectroscopy and Imaging)
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