Advances in Magnetic Resonance Imaging (MRI) and Its Role in Radiation Therapy

Topic Information

Dear Colleagues,

This is the second edition of a previous edition on “Advances of MRI in Radiation Oncology”. Radiation oncology treatment planning requires CT data for dose calculation; however, CT lacks soft-tissue visualization and characterization. MR images are best suited for soft tissues, especially liver, pancreas, kidney, prostate, and brain tissues. MR images have been augmented using image fusion, but their accuracy can be questionable. Additionally, MR images do not provide the electron density information needed for dose calculation. Moving structures pose additional challenges in radiation oncology. The active trend in radiation oncology is to use MR images with the help of synthetic CT for image-guided radiation therapy. Integrated MR imaging and linear accelerator system (MRL), which provides the optimum treatment for soft tissue and moving structures, is a new frontier in radiation oncology. The focus of this Special Issue is to review current MR imaging options, as well as imaging-assisted therapies and adaptive therapies, in radiation oncology. This issue will cover MR imaging parameters/sequences in low and high magnetic fields, MR-linacs, synthetic CT, dose calculation, and motion management as well as every aspect of MR use in radiation oncology.

Prof. Dr. Indra J. Das
Dr. Minsong Cao
Topic Editors

Keywords

Participating Journals

Journal Name	Impact Factor	CiteScore	Launched Year	First Decision (median)	APC
Biomedicines biomedicines	3.9	6.8	2013	21 Days	CHF 2600
Cancers cancers	4.4	8.8	2009	19.1 Days	CHF 2900
Current Oncology curroncol	3.4	4.9	1994	22.8 Days	CHF 2200
Diagnostics diagnostics	3.3	5.9	2011	21.6 Days	CHF 2600
Journal of Clinical Medicine jcm	2.9	5.2	2012	18.5 Days	CHF 2600

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Published Papers (2 papers)

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All Biomedicines Cancers Current Oncology Diagnostics JCM

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12 pages, 1982 KB  

Open AccessArticle

Prognostic Value of Multimodal Cardiac Magnetic Resonance Parameters in Patients with Nondilated Left Ventricular Cardiomyopathy and Reduced Left Ventricular Ejection Fraction

by Chunlong Yan, Shuang Li, Baiyan Zhuang, Shujuan Yang, Jiayi Liu, Jiangjun Qin and Lei Xu

J. Clin. Med. 2026, 15(3), 918; https://doi.org/10.3390/jcm15030918 - 23 Jan 2026

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Abstract

Background: To investigate the predictive value of cardiac magnetic resonance (CMR) feature parameters for major adverse cardiovascular events (MACEs) in patients with nondilated left ventricular cardiomyopathy and reduced left ventricular ejection fraction (NDLVC-rLVEF). Methods: This single-center retrospective study enrolled patients with [...] Read more.

Background: To investigate the predictive value of cardiac magnetic resonance (CMR) feature parameters for major adverse cardiovascular events (MACEs) in patients with nondilated left ventricular cardiomyopathy and reduced left ventricular ejection fraction (NDLVC-rLVEF). Methods: This single-center retrospective study enrolled patients with NDLVC-rLVEF who underwent CMR between January 2015 and May 2025. MACEs included cardiovascular death, implantable cardioverter–defibrillator (ICD) discharge, and hospitalization due to heart failure or arrhythmia. Multivariable Cox regression analysis was used to identify independent risk factors for MACEs. Results: A total of 160 patients were included (mean age: 50.83 ± 15.81 years; 114 males, 46 females), with a median follow-up time of 53.00 months (IQR: 32.25–82.00). During this period, 41 patients (25.63%) experienced MACEs, including 10 cases of cardiovascular death, 1 case of ICD discharge, and 30 cases of rehospitalization due to heart failure or arrhythmia. Multivariable Cox regression analysis revealed that right ventricular ejection fraction (RVEF) and left ventricular global radial strain (LVGRS) were independent predictors of MACEs in patients with NDLVC-rLVEF. Kaplan–Meier analysis further demonstrated that patients with RVEF < 37% or LVGRS < 13% had a significantly higher incidence of MACEs (p < 0.05). Conclusions: Multimodal CMR parameters (RVEF and LVGRS) have significant predictive value for adverse prognosis in patients with NDLVC-rLVEF, facilitating early risk stratification and clinical intervention. Full article

(This article belongs to the Topic Advances in Magnetic Resonance Imaging (MRI) and Its Role in Radiation Therapy)

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14 pages, 1984 KB  

Open AccessSystematic Review

Diagnostic Accuracy of MRI for Orbital and Intracranial Invasion of Sinonasal Malignancies: A Systematic Review and Meta-Analysis

by Umida Abdullaeva, Bernd Pape and Jussi Hirvonen

J. Clin. Med. 2024, 13(24), 7556; https://doi.org/10.3390/jcm13247556 - 12 Dec 2024

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Abstract

Background/Objectives: In this study, we review the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting orbital and intracranial invasion of sinonasal malignancies (SNMs) using histopathological and surgical evidence as the reference standard. Methods: A systematic search of studies in English [...] Read more.

Background/Objectives: In this study, we review the diagnostic accuracy of magnetic resonance imaging (MRI) in detecting orbital and intracranial invasion of sinonasal malignancies (SNMs) using histopathological and surgical evidence as the reference standard. Methods: A systematic search of studies in English was conducted in MEDLINE and Embase, limited to articles published since 1990. We included studies using preoperative MRI to detect the intracranial and orbital invasion of SNMs, with histological or surgical confirmation as the reference standard, and reported patient numbers in each class as required to assess diagnostic accuracy. The outcome measures were sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). Heterogeneity was assessed with the Higgins inconsistency test (I²). Results: Seven original articles with 546 subjects were included in the review, with six included in the meta-analysis. The pooled overall accuracy for orbital invasion was higher at 0.88 (95% CI, 0.75–0.94) than that for intracranial invasion at 0.80 (95% CI, 0.76–0.83). The meta-analytic estimates and their 95% confidence intervals were as follows for intracranial/orbital invasion: sensitivity 0.77 (0.69–0.83)/0.71 (0.40–0.90); specificity 0.79 (0.74–0.83)/0.91 (0.78–0.97); PPV 0.76 (0.64–0.85)/0.78 (0.61–0.88); and NPV 0.82 (0.72–0.89)/0.90 (0.63–0.98). Substantial heterogeneity was observed in the Higgins inconsistency test (I²) for orbital invasion (84%, 83%, and 93% for sensitivity, specificity, and NPV, respectively). Conclusions: MRI yielded moderate-to-high diagnostic accuracy for intracranial and orbital invasion, despite some limitations leading to false diagnoses. Loss of the hypointense zone on postcontrast MRI was found to predict dural invasion. Infiltration of the extraconal fat beyond the periorbita was found to be an MRI feature of orbital invasion. Full article

(This article belongs to the Topic Advances in Magnetic Resonance Imaging (MRI) and Its Role in Radiation Therapy)

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