Journal of Magnetic Resonance Imaging最新文献

Representative Images Comparing DTI Metrics between Participants with PMS and Healthy Controls by TBSS Analysis. Areas in Blue and Red Respectively Represent Brain Regions with Significant Decrease in Fractional Anisotropy (FA) and Increase in Mean Diffusivity (MD), Axial Diffusivity (AD) and Radial Diffusivity (RD) in PMS Group Relative to HCS (TFCE, FWE-Corrected). Results are Shown Overlaid on Montreal Neurological Institute 152-T1 Template (Gray) and Mean FA Skeleton (Green). By Duan et Al. (2271-2280)

Background: Cancer-related cognitive impairment (CRCI) impacts breast cancer (BC) patients' quality of life after chemotherapy. While recent studies have explored its neural correlates, single time-point designs cannot capture how these changes evolve over time.

Purpose: To investigate changes in the brain connectome of BC patients at several time points during neoadjuvant chemotherapy (NAC).

Study type: Longitudinal.

Subjects: 55 participants with BC underwent clinical assessments and fMRI at baseline (TP1), the first cycle of NAC (TP2, 30 days later), and the end (TP3, 140 days later). Two matched female healthy control (HCs, n = 20 and n = 18) groups received the same assessments. FIELD STRENGTH/SEQUENCE: rs-fMRI (gradient-echo EPI) and 3D T1-weighted magnetization-prepared rapid gradient echo sequence at 3.0 T.

Assessment: Brain functional networks were analyzed using graph theory approaches. We analyzed changes in brain connectome metrics and explored the relationship between these changes and clinical scales (including emotion and cognitive test). Patients were divided into subgroups according to clinical classification, chemotherapy regimen, and menopausal status. Longitudinal analysis was performed at three time points for each subgroup.

Statistical tests: An independent sample t-test for patient-HC comparison at TP1. Analysis of variance and paired t-test for longitudinal changes. Regression analysis for relations between network measurements changes and clinical symptom scores changes. Significance was defined as p < 0.05.

Results: Post-NAC, BC patients showed increased global efficiency (TP2-TP1 = 0.087, TP3-TP1 = 0.078), decreased characteristic path length (TP2-TP1 = -0.413, TP3-TP1 = -0.312), and altered nodal centralities mainly in the frontal-limbic system and cerebellar cortex. These abnormalities expanded with chemotherapy progression significantly (TP2 vs. TP3). Topological parameters changes were also correlated with clinical scales changes significantly. No differences were found within or between HC groups (p = 0.490-0.989) or BC subgroups (p = 0.053-0.988) at TP1.

Data conclusions: NAC affects the brain functional connectome of BC patients at TP2, and these changes persist and further intensify at TP3.

Level of evidence: 2:

Technical efficacy: Stage 5.

Background: Papillary muscle infarction (PMI) has been linked to significantly increased mortality and is associated with ventricular arrhythmias and mitral regurgitation. Reference bright-blood late gadolinium enhancement (LGE) imaging provides poor scar-to-blood contrast, making PMI visualization challenging. Black-blood LGE imaging overcomes this limitation by improving the blood-scar contrast.

Purpose: To evaluate a recent co-registered bright- (papillary muscle localization) and black-blood (PMI visualization) sequence (Scar-specific imaging with Preserved myOcardial visualizaTion: SPOT) to improve PMI visualization compared to a reference standard phase-sensitive inversion recovery (PSIR) sequence, and to enable automated PMI detection (auto-PMI).

Study type: Retrospective.

Population: 198 patients with ischemic heart disease were divided into an optimization dataset (N = 127) and a testing dataset (N = 71).

Field strength/sequence: 2D SPOT and PSIR balanced steady-state free precession sequences at 1.5 T.

Assessment: Auto-PMI included: image acquisition, slice selection, endocardial segmentation, blood pool preprocessing, and PMI detection. Three radiologists (8, 5 and 2 years of MRI experience) assessed PMI in SPOT and PSIR images independently. A consensus reading regarding all assessments of both sequences was established. The number of patients with PMI in SPOT and PSIR acquisitions was compared. The diagnostic performances of visual (SPOT and PSIR) and auto-PMI (SPOT) detection were evaluated. Inter- and intra-observer reproducibility of the visual PMI detection was assessed.

Statistical tests: McNemar test, p-value < 0.05 was considered statistically significant.

Results: In the testing dataset, significantly more patients with PMI were detected using SPOT compared to PSIR in each session (37 vs. 27, 36 vs. 29, 41 vs. 31, 42 vs. 25). Sensitivity ranges for visual PMI detection were significantly higher using SPOT (89%-100% vs. 61%-82%). SPOT vs. PSIR inter- and intra-observer reproducibility ranges were 77%-80% vs. 71%-77%, and 97% vs. 88%, respectively. Auto-PMI sensitivity was 87%.

Data conclusion: Co-registered bright- and black-blood SPOT imaging improved visual PMI detection and facilitated automated PMI assessment.

Evidence level: 3. Technical Efficacy: Stage 2.

Background: Glutamate and glutamine are critical metabolites in gliomas, each serving distinct roles in tumor biology. Separate quantification of these metabolites using in vivo MR spectroscopy (MRS) at clinical field strengths (≤ 3T) is hindered by their molecular similarity, resulting in overlapping, hence indistinguishable, spectral peaks.

Purpose: To develop an MRS imaging (MRSI) protocol to map glutamate and glutamine separately at 3T within clinically feasible time, using J-modulation to enhance spectral differentiation, demonstrate its reliability/reproducibility, and quantify the metabolites in glioma subregions.

Study type: Prospective.

Population: Phantoms, 5 healthy subjects, and 30 patients with suspected glioma. IDH wild-type glioblastoma cases were evaluated to establish a uniform group.

Field strength/sequence: 3T, Research protocol: 2D ¹H sLASER MRSI (40 and 120 ms TE) with water reference, 3D T1-weighted and 2D T2-weighted. Trial-screening process: T1-weighted, T1-weighted contrast-enhanced, T2-weighted, FLAIR.

Assessment: Spectral simulations and phantom measurements were performed to design and validate the protocol. Spectral quality/fitting parameters for scan-rescan measurements were obtained using LCModel. The proposed long-TE data were compared with short-TE data. BraTS Toolkit was employed for fully automated tumor segmentation.

Statistical tests: Scan-rescan comparison was performed using Bland-Altman analysis. LCModel coefficient of modeling covariance (CMC) between glutamate and glutamine was mapped to evaluate their model interactions for each spectral fitting. Metabolite levels in tumor subregions were compared using one-way ANOVA and Kruskal-Wallis. A p value < 0.05 was considered statistically significant.

Results: Spectral quality/fitting parameters and metabolite levels were highly consistent between scan-rescan measurements. A negative association between glutamate and glutamine models at short TE (CMC = -0.16 ± 0.06) was eliminated at long TE (0.01 ± 0.05). Low glutamate in tumor subregions (non-enhancing-tumor-core: 5.35 ± 4.45 mM, surrounding-non-enhancing-FLAIR-hyperintensity: 7.39 ± 2.62 mM, and enhancing-tumor: 7.60 ± 4.16 mM) was found compared to contralateral (10.84 ± 2.94 mM), whereas glutamine was higher in surrounding-non-enhancing-FLAIR-hyperintensity (9.17 ± 6.84 mM) and enhancing-tumor (7.20 ± 4.42 mM), but not in non-enhancing-tumor-core (4.92 ± 3.38 mM, p = 0.18) compared to contralateral (2.94 ± 1.35 mM).

Data conclusion: The proposed MRSI protocol (~12 min) enables separate mapping of glutamate and glutamine reliably along with other MRS-detectable standard metabolites in glioma subregions at 3T.

Evidence level: 1 TECHNICAL EFFICACY: Stage 3.

Background: Imaging-based molecular characterization is important for identifying treatment targets in adult-type diffuse gliomas.

Purpose: To assess isocitrate dehydrogenase (IDH) mutation and epidermal growth factor receptor (EGFR) amplification status in primary and recurrent gliomas using diffusion and perfusion MRI, addressing spatial and temporal heterogeneity.

Study type: Retrospective.

Subjects: Three-hundred and twelve newly diagnosed (cross-sectional set, 57.9 ± 13.2 years, 52.2% male, 235 IDH-wildtype, 71 EGFR-amplified) and 38 recurrent (longitudinal set, 53.1 ± 13.4 years, 44.7% male, 30 IDH-wildtype, 13 EGFR-amplified) adult-type diffuse glioma patients.

Field strength/sequence: 3.0T; diffusion weighted and dynamic susceptibility contrast-perfusion weighted imaging.

Assessment: Radiomics features from contrast-enhancing tumors (CET) and non-enhancing lesions (NEL) were extracted from apparent diffusion coefficient and perfusion maps. Spatial heterogeneity was assessed using intersection and Bhattacharyya distance between CET and NEL. Stable imaging features were identified in patients with unchanged genetic profiles in the longitudinal set. The "best model," using features from the cross-sectional set (n = 312), and the "concordant model," using stable features identified in the longitudinal set (n = 38), were constructed using the LASSO for IDH and EGFR status.

Statistical tests: The area under the receiver-operating-characteristic curve (AUC).

Results: For IDH mutations, both best and concordant models demonstrated high AUCs in the cross-sectional set (0.936; 95% confidence interval [CI]: 0.903-0.969 and 0.964 [0.943-0.986], respectively). Only the concordant model maintained strong performance in recurrent tumors (AUC, 0.919 vs. 0.656). For EGFR amplification in IDH-wildtype, the best and concordant models showed AUCs of 0.821 (95% CI: 0.761-0.881) and 0.746 (95% CI: 0.675-0.817) in newly diagnosed gliomas, but poor performance in recurrent tumors with AUCs of 0.503 (95% CI: 0.34-0.665) and 0.518 (95% CI: 0.357-0.678).

Data conclusion: Diffusion and perfusion MRI characterized IDH status in both newly diagnosed and recurrent gliomas, but showed limited diagnostic performance for EGFR, especially for recurrent tumors.

Evidence level: 3 TECHNICAL EFFICACY: Stage 3.

The integration of Positron emission tomography (PET) with Magnetic resonance imaging (MRI) combines the functional imaging capabilities of PET with the high-resolution anatomical detail of MRI, creating a synergistic platform for advanced diagnostic imaging and image-guided therapies. Central to the success of this dual-modality system is the development of specialized PET/MRI dual-modality probes, particularly those capable of simultaneous functionality, which present significant technical challenges in synthesis and applications. This review explores the advancements in PET/MRI probe development, summarizes the current applications, and highlights the critical challenges in translating PET/MRI probes from experimental research to clinical applications, offering insights into the future direction of this transformative imaging technology. EVIDENCE LEVEL: 5. TECHNICAL EFFICACY: Stage 1.