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Global Translational Medicine

PERSPECTIVE ARTICLE
Nuclear magnetic resonance-biochemical

correlation toward deep learning of theranosis
and precision medicine

Rakesh Sharma * and Arvind Trivedi 2
1
1 Plastic Surgery Scholar, Surgery NMR Lab, Shriners Children Hospital, Massachusetts General
Hospital, Harvard Medical School, Boston, MA, USA
2 Department of Medicine, Government Medical College, Saharanpur, Uttar Pradesh, India

Abstract

Efforts have been made to employ the nuclear magnetic resonance (NMR)-
biochemical correlation concept or a combination of MR imaging (MRI) and MR
spectroscopy (MRS) as an established diagnostic tool for medical practice in clinical
settings. Recent reviews and meta-analyses indicate the great possibility of using
integrated multimodal multiparametric MRI and MRS for deep learning (DL) of soft-
tissue pathophysiology, enabling improved decision-making and disease progression
monitoring in precision medicine. Recent guidelines and clinical trials suggest the
need for DL of the biophysical and biochemical nature of the brain, breast, prostate,
liver, and heart tissue from digital spectromics analysis, along with other molecular
imaging modalities. The current opinions, based on recent recommendations,
available literature on evidence-based MR spectromics, clinical trials, and meta-
analyses on high-resolution MRI and MRS suggest that utilizing MRI and MRS signals
as theranostic biomarkers for various soft tissues can demonstrate NMR-biochemical
*Corresponding author: correlation and employ MRI with MRS as adjunct real-time tools, generating robust,
Rakesh Sharma
(rksz2009@gmail.com) and fast tissue digital images with metabolic screening. The integration of DL features
can aid in evaluating patient disease diagnosis and therapy within a clinical setting,
Citation: Sharma R, Trivedi A,
2023, Nuclear magnetic resonance- considering the available medical practices and their limitations.
biochemical correlation toward deep
learning of theranosis and precision
medicine. Global Transl Med, 2(3): Keywords: Nuclear magnetic resonance-biochemical correlation; Magnetic resonance
337. imaging; Magnetic resonance spectroscopy; Deep learning of disease nature; Clinical
https://doi.org/10.36922/gtm.337
trials; Magnetic resonance meta-analysis
Received: January 23, 2023
Accepted: June 7, 2023
Published Online: August 16, 2023
Copyright: © 2023 Author(s). 1. Introduction
This is an Open Access article
distributed under the terms of the The concept of “nuclear magnetic resonance (NMR)-biochemical correlation” was
Creative Commons Attribution proposed by researchers in the 90s as a non-invasive diagnostic monitoring tool .
[1]
License, permitting distribution,
and reproduction in any medium, Initially, the correlation of longitudinal T1 and transverse T2* with ex vivo NMR and
provided the original work is in vivo MR spectroscopy (MRS) data, along with serum analytes and tissue histology,
properly cited. were integrated as established NMR relaxation-biochemical biomarkers, as shown in
Publisher’s Note: AccScience Figure 1 and Table 1 [1,2] . Over years of continued efforts, NMR has shown great potential
Publishing remains neutral with in deep learning (DL) features by integrating multimodal T1-, T2-molecular images,
regard to jurisdictional claims in
published maps and institutional 2D/3D spectra generating regression, convolutional neural network (CNN) framework,
affiliations. trained dataset for decision-making, and measurements of metabolite concentrations at

Volume 2 Issue 3 (2023) 1 https://doi.org/10.36922/gtm.337