Changes and variability of proton density and T1 relaxation times in early multiple sclerosis: MRI markers of neuronal damage in the cerebral cortex

Multiparametric approach with synthetic MR imaging for diagnosing salivary gland lesions

PURPOSE

To determine whether synthetic MR imaging can distinguish between benign and malignant salivary gland lesions.

METHODS

The study population included 44 patients with 33 benign and 11 malignant salivary gland lesions. All MR imaging was obtained using a 3 Tesla system. The QRAPMASTER pulse sequence was used to acquire images with four TI values and two TE values, from which quantitative images of T1 and T2 relaxation times and proton density (PD) were generated. The Mann-Whitney U test was used to compare T1, T2, PD, and ADC values among the subtypes of salivary gland lesions. ROC analysis was used to evaluate diagnostic capability between malignant tumors (MTs) and either pleomorphic adenomas (PAs) or Warthin tumors (WTs). We further calculated diagnostic accuracy for distinguishing malignant from benign lesions when combining these parameters.

RESULTS

PAs demonstrated significantly higher T1, T2, PD, and ADC values than WTs (all p < 0.001). Compared to MTs, PAs had significantly higher T1, T2, and ADC values (all p < 0.001), whereas WTs had significantly lower T1, T2, and PD values (p < 0.001, p = 0.008, and p = 0.003, respectively). T2 and ADC were most effective in differentiating between MTs and PAs (AUC = 0.928 and 0.939, respectively), and T1 and PD values for differentiating between MTs and WTs (AUC = 0.915 and 0.833, respectively). Combining T1 with T2 or ADC achieved accuracy of 86.4% in distinguishing between malignant and benign tumors. Similarly, combining PD with T2 or ADC reached accuracy of 86.4% for differentiating between malignant and benign tumors.

CONCLUSIONS

Utilizing a combination of synthetic MRI parameters may assist in differentiating malignant from benign salivary gland lesions.

Feasibility of using synthetic MRI to predict lymphatic vascular space invasion status in early-stage cervical cancer: added value to morphological MRI

OBJECTIVES

To investigate the feasibility of synthetic magnetic resonance imaging (syMRI) in predicting the lymphatic vascular space invasion (LVSI) status of early-stage cervical cancer, and its added value to morphological MRI.

MATERIALS AND METHODS

A total of 72 patients with pathology-confirmed early-stage cervical cancer were enrolled, and classified into LVSI- positive (n=41) and LVSI- negative (n=31) groups. Together with morphological parameters including gross tumor volume (GTV) and maximum tumor diameter (MTD), the T1, T2, and proton density (PD) values of the tumors were also measured and compared between two groups. Binary logistic regression analysis was used to identify the independent variable associated with LVSI. Receiver operating characteristic curve analyses and DeLong tests were used to evaluate and compare the performances of significant parameters or their combination in predicting LVSI.

RESULTS

LVSI- positive group showed significantly higher GTV (P=0.008) and MTD (P=0.019), and lower T1 (P<0.001) and PD values (P=0.041) than LVSI- negative group. However, no statistical significance was observed regarding the T2 values (P=0.331). Binary logistic regression indicated that T1 value (odds ratio [OR] = 0.993; P=0.001) and MTD (OR=1.903, P=0.027) were independent variables associated with LVSI in early cervical cancer. Optimal performance could be achieved [area under ROC curve (AUC) = 0.784; cut-off value = 0.56; sensitivity = 80.5%; specificity = 71.0%] when combining T1 and MTD for predicting LVSI. Its performance was significantly better than that of MTD alone (AUC, 0.784 vs 0.662, P=0.035).

CONCLUSION

syMRI might be a feasible approach, and it can provide added value to morphological MRI in predicting the LVSI status of early-stage cervical cancer.

Advanced Brain Imaging in Central Nervous System Demyelinating Diseases

In recent decades, advances in neuroimaging have profoundly transformed our comprehension of central nervous system demyelinating diseases. Remarkable technological progress has enabled the integration of cutting-edge acquisition and postprocessing techniques, proving instrumental in characterizing subtle focal changes, diffuse microstructural alterations, and macroscopic pathologic processes. This review delves into state-of-the-art modalities applied to multiple sclerosis, neuromyelitis optica spectrum disorders, and myelin oligodendrocyte glycoprotein antibody-associated disease. Furthermore, it explores how this dynamic landscape holds significant promise for the development of effective and personalized clinical management strategies, encompassing support for differential diagnosis, prognosis, monitoring treatment response, and patient stratification.

Multimodal neuroimaging exploration of the mechanisms of sleep quality deterioration after SARS-CoV-2 Omicron infection

BACKGROUND

To evaluate the neurological alterations induced by Omicron infection, to compare brain changes in chronic insomnia with those in exacerbated chronic insomnia in Omicron patients, and to examine individuals without insomnia alongside those with new-onset insomnia.

METHODS

In this study, a total of 135 participants were recruited between January 11 and May 4, 2023, including 26 patients with chronic insomnia without exacerbation, 24 patients with chronic insomnia with exacerbation, 40 patients with no sleep disorder, and 30 patients with new-onset insomnia after infection with Omicron (a total of 120 participants with different sleep statuses after infection), as well as 15 healthy controls who were never infected with Omicron. Neuropsychiatric data, clinical symptoms, and multimodal magnetic resonance imaging data were collected. The gray matter thickness and T1, T2, proton density, and perivascular space values were analyzed. Associations between changes in multimodal magnetic resonance imaging findings and neuropsychiatric data were evaluated with correlation analyses.

RESULTS

Compared with healthy controls, gray matter thickness changes were similar in the patients who have and do not have a history of chronic insomnia groups after infection, including an increase in cortical thickness near the parietal lobe and a reduction in cortical thickness in the frontal, occipital, and medial brain regions. Analyses showed a reduced gray matter thickness in patients with chronic insomnia compared with those with an aggravation of chronic insomnia post-Omicron infection, and a reduction was found in the right medial orbitofrontal region (mean [SD], 2.38 [0.17] vs. 2.67 [0.29] mm; P < 0.001). In the subgroups of Omicron patients experiencing sleep deterioration, patients with a history of chronic insomnia whose insomnia symptoms worsened after infection displayed heightened medial orbitofrontal cortical thickness and increased proton density values in various brain regions. Conversely, patients with good sleep quality who experienced a new onset of insomnia after infection exhibited reduced cortical thickness in pericalcarine regions and decreased proton density values. In new-onset insomnia patients post-Omicron infection, the thickness in the right pericalcarine was negatively correlated with the Self-rating Anxiety Scale (r =  - 0.538, P = 0.002, PFDR = 0.004) and Self-rating Depression Scale (r =  - 0.406, P = 0.026, PFDR = 0.026) scores.

CONCLUSIONS

These findings help us understand the pathophysiological mechanisms involved when Omicron invades the nervous system and induces various forms of insomnia after infection. In the future, we will continue to pay attention to the dynamic changes in the brain related to insomnia caused by Omicron infection.

Synthetic MRI and diffusion-weighted imaging for differentiating nasopharyngeal lymphoma from nasopharyngeal carcinoma: combination with morphological features

OBJECTIVES

To investigate the feasibility of synthetic MRI (syMRI), diffusion-weighted imaging (DWI), and their combination with morphological features for differentiating nasopharyngeal lymphoma (NPL) from nasopharyngeal carcinoma (NPC).

METHODS

Sixty-nine patients with nasopharyngeal tumours (NPL, n = 22; NPC, n = 47) who underwent syMRI and DWI were retrospectively enrolled between October 2020 and May 2022. syMRI and DWI quantitative parameters (T1, T2, PD, ADC) and morphological features were obtained. Diagnostic performance was assessed by independent sample t-test, chi-square test, logistic regression analysis, receiver operating characteristic curve (ROC), and DeLong test.

RESULTS

NPL has significantly lower T2, PD, and ADC values compared to NPC (all P < .05), whereas no significant difference was found in T1 value between these two entities (P > .05). The morphological features of tumour type, skull-base involvement, Waldeyer ring involvement, and lymph nodes involvement region were significantly different between NPL and NPC (all P < .05). The syMRI (T2 + PD) model has better diagnostic efficacy, with AUC, sensitivity, specificity, and accuracy of 0.875, 77.27%, 89.36%, and 85.51%. Compared with syMRI model, syMRI + Morph (PD + Waldeyer ring involvement + lymph nodes involvement region), syMRI + DWI (T2 + PD + ADC), and syMRI + DWI + Morph (PD + ADC + skull-base involvement + Waldeyer ring involvement) models can further improve the diagnostic efficiency (all P < .05). Furthermore, syMRI + DWI + Morph model has excellent diagnostic performance, with AUC, sensitivity, specificity, and accuracy of 0.986, 95.47%, 97.87%, and 97.10%, respectively.

CONCLUSION

syMRI and DWI quantitative parameters were helpful in discriminating NPL from NPC. syMRI + DWI + Morph model has the excellent diagnostic efficiency in differentiating these two entities.

ADVANCES IN KNOWLEDGE

syMRI + DWI + morphological feature method can differentiate NPL from NPC with excellent diagnostic performance.

Histogram analysis of MR quantitative parameters: are they correlated with prognostic factors in prostate cancer?

PURPOSE

To investigate the correlation between quantitative MR parameters and prognostic factors in prostate cancer (PCa).

METHOD

A total of 186 patients with pathologically confirmed PCa who underwent preoperative multiparametric MRI (mpMRI), including synthetic MRI (SyMRI), were enrolled from two medical centers. The histogram metrics of SyMRI [T1, T2, proton density (PD)] and apparent diffusion coefficient (ADC) values were extracted. The Mann‒Whitney U test or Student's t test was employed to determine the association between these histogram features and the prognostically relevant factors. Receiver operating characteristic (ROC) curve analysis was conducted to evaluate the differentiation performance. Spearman's rank correlation coefficients were calculated to determine the correlations between histogram parameters and the International Society of Urological Pathology (ISUP) grade group as well as pathological T stage.

RESULTS

Significant correlations were found between the histogram parameters and the ISUP grade as well as pathological T stage of PCa. Among these histogram parameters, ADC_minimum had the strongest correlation with the ISUP grade (r = - 0.481, p < 0.001), and ADC_Median showed the strongest association with pathological T stage (r = - 0.285, p = 0.008). The ADC_10th percentile exhibited the highest performance in identifying clinically significant prostate cancer (csPCa) (AUC 0.833; 95% CI 0.771-0.883). When discriminating between the status of different prognostically relevant factors, a significant difference was observed between extraprostatic extension-positive and -negative cancers with regard to histogram parameters of the ADC map (10th percentile, 90th percentile, mean, median, minimum) and T1 map (minimum) (p = 0.002-0.032). Moreover, histogram parameters of the ADC map (90th percentile, maximum, mean, median), T2 map (10th percentile, median), and PD map (10th percentile, median) were significantly lower in PCa with perineural invasion (p = 0.009-0.049). The T2 values were significantly lower in patients with seminal vesicle invasion (minimum, p = 0.036) and positive surgical margin (10th percentile, 90th percentile, mean, median, and minimum, p = 0.015-0.025).

CONCLUSION

Quantitative histogram parameters derived from synthetic MRI and ADC maps may have great potential for predicting the prognostic features of PCa.

The quantitative parameters based on marrow metabolism derived from synthetic MRI: A pilot study of prognostic value in participants with newly diagnosed multiple myeloma

BACKGROUND

The value of SyMRI-derived parameters from lumbar marrow for predicting early treatment response and optimizing the risk stratification of the Revised International Staging System (R-ISS) in participants with multiple myeloma (MM) is unknown.

METHODS

We prospectively enrolled participants with newly diagnosed MM before treatment. The SyMRI of lumbar marrow was used to calculate T1, T2, and PD values and the clinical features were collected. All participants were divided into good response (≥VGPR) and poor response (

RESULTS

Fifty-nine participants (good response, n = 33; poor response, n = 26) were evaluated. The bone marrow plasma cell percentage, β2-microglobulin, T1 and T2 value were difference between two groups (all p < 0.05). The T1 (odds ratio 1.003, p = 0.005) and T2 values (odds ratio 0.910, p = 0.002) were independent predictors and the AUC and cut-off values were 0.787, 967.2 ms and 0.784, 75.9 ms, respectively. There were no significant differences in SyMRI parameters between genders. Participants with both T1 value ≥967.2 ms and T2 value ≤75.9 ms in the R-ISS II stage were potentially to get poor response.

CONCLUSIONS

Synthetic MRI is a promising tool for predicting early treatment response to MM and promoting R-ISS II stage risk stratification.

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Key Words

• R‐ISS stage
• early treatment response
• magnetic resonance imaging
• multiple myeloma
• tumor burden

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MESH Headings

• Humans
• Male
• Female
• Prognosis
• Multiple Myeloma/diagnostic imaging
• Multiple Myeloma/pathology
• Bone Marrow/diagnostic imaging
• Bone Marrow/pathology
• Pilot Projects
• Neoplasm Staging
• Magnetic Resonance Imaging
• Retrospective Studies

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Grants

• 82071898 National Natural Science Foundation of China
• National Natural Science Foundation of China

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Affiliation(s)

Sha Cui Department of Medical ImagingShanxi Medical UniversityTaiyuanChina Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Yinnan Guo Department of PainFifth Hospital of Shanxi Medical UniversityTaiyuanChina
Weiran Niu Department of Medical ImagingShanxi Medical UniversityTaiyuanChina
Jianting Li Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Wenjin Bian Department of Medical ImagingShanxi Medical UniversityTaiyuanChina
Wenqi Wu Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Wenjia Zhang Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Qian Zheng Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Jun Wang Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina
Jinliang Niu Department of RadiologySecond Hospital of Shanxi Medical UniversityTaiyuanChina

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Multiparametric quantitative MRI reveals progressive cortical damage over time in clinically stable relapsing-remitting MS

BACKGROUND

In relapsing-remitting multiple sclerosis (RRMS), cortical grey matter pathology relevantly contributes to long-term disability. Still, diffuse cortical inflammation cannot be detected with conventional MRI.

OBJECTIVE

We aimed to assess microstructural damage of cortical grey matter over time and the relation to clinical disability as well as relapse activity in patients with RRMS using multiparametric quantitative (q)MRI techniques.

METHODS

On 40 patients with RRMS and 33 age-matched and sex-matched healthy controls, quantitative T1, T2, T2* and proton density (PD) mapping was performed at baseline and follow-up after 2 years. Cortical qMRI parameter values were extracted with the FreeSurfer software using a surface-based approach. QMRI parameters, cortical thickness and white matter lesion (WML) load, as well as Expanded Disability Status Scale (EDSS) and relapse rate, were compared between time points.

RESULTS

Over 2 years, significant increases of T1 (p≤0.001), PD (p≤0.001) and T2 (p=0.005) values were found in the patient, but not in the control group. At decreased relapse rate over time (p=0.001), cortical thickness, WML volume and EDSS remained unchanged.

CONCLUSION

Despite clinical stability, cortical T1, T2 and PD values increased over time, indicating progressive demyelination and increasing water content. These parameters represent promising surrogate parameters of diffuse cortical inflammation in RRMS.

Synthetic MRI plus FSE-PROPELLER DWI for differentiating malignant from benign head and neck tumors: a preliminary study

Background

Preoperative classification of head and neck (HN) tumors remains challenging, especially distinguishing early cancerogenic masses from benign lesions. Synthetic MRI offers a new way for quantitative analysis of tumors. The present study investigated the application of synthetic MRI and stimulus and fast spin echo diffusion-weighted imaging with periodically rotated overlapping parallel lines with enhanced reconstruction (FSE-PROPELLER DWI) to differentiate malignant from benign HN tumors.

Materials and methods

Forty-eight patients with pathologically confirmed HN tumors were retrospectively recruited between August 2022 and October 2022. The patients were divided into malignant (n = 28) and benign (n = 20) groups. All patients were scanned using synthetic MRI and FSE-PROPELLER DWI. T1, T2, and proton density (PD) values were acquired on the synthetic MRI and ADC values on the FSE-PROPELLER DWI.

Results

Benign tumors (ADC: 2.03 ± 0.31 × 10-3 mm2/s, T1: 1741.13 ± 662.64 ms, T2: 157.43 ± 72.23 ms) showed higher ADC, T1, and T2 values compared to malignant tumors (ADC: 1.46 ± 0.37 × 10-3 mm2/s, T1: 1390.06 ± 241.09 ms, T2: 97.64 ± 14.91 ms) (all P<0.05), while no differences were seen for PD values. ROC analysis showed that T2+ADC (cut-off value, > 0.55; AUC, 0.950) had optimal diagnostic performance vs. T1 (cut-off value, ≤ 1675.84 ms; AUC, 0.698), T2 (cut-off value, ≤ 113.24 ms; AUC, 0.855) and PD (cut off value, > 80.67 pu; AUC, 0.568) alone in differentiating malignant from benign lesions (all P<0.05); yet, the difference in AUC between ADC and T2+ADC or T2 did not reach statistical significance.

Conclusion

Synthetic MRI and FSE-PROPELLER DWI can quantitatively differentiate malignant from benign HN tumors. T2 value is comparable to ADC value, and T2+ADC values could improve diagnostic efficacy., apparent diffusion coeffificient, head and neck tumors.

The advantages of the magnetic resonance image compilation (MAGiC) method for the prognosis of neonatal hypoglycemic encephalopathy

Objectives

To explore the prognostic value of magnetic resonance image compilation (MAGiC) in the quantitative assessment of neonatal hypoglycemic encephalopathy (HE).

Methods

A total of 75 neonatal HE patients who underwent synthetic MRI were included in this retrospective study. Perinatal clinical data were collected. T1, T2 and proton density (PD) values were measured in the white matter of the frontal lobe, parietal lobe, temporal lobe and occipital lobe, centrum semiovale, periventricular white matter, thalamus, lenticular nucleus, caudate nucleus, corpus callosum and cerebellum, which were generated by MAGiC. The patients were divided into two groups (group A: normal and mild developmental disability; group B: severe developmental disability) according to the score of Bayley Scales of Infant Development (Bayley III) at 9-12 months of age. Student's t test, Wilcoxon test, and Fisher's test were performed to compare data across the two groups. Multivariate logistic regression was used to identify the predictors of poor prognosis, and receiver operating characteristic (ROC) curves were created to evaluate the diagnostic accuracy.

Results

T1 and T2 values of the parietal lobe, occipital lobe, center semiovale, periventricular white matter, thalamus, and corpus callosum were higher in group B than in group A (p < 0.05). PD values of the occipital lobe, center semiovale, thalamus, and corpus callosum were higher in group B than in group A (p < 0.05). Multivariate logistic regression analysis showed that the duration of hypoglycemia, neonatal behavioral neurological assessment (NBNA) scores, T1 and T2 values of the occipital lobe, and T1 values of the corpus callosum and thalamus were independent predictors of severe HE (OR > 1, p < 0.05). The T2 values of the occipital lobe showed the best diagnostic performance, with an AUC value of 0.844, sensitivity of 83.02%, and specificity of 88.16%. Furthermore, the combination of MAGiC quantitative values and perinatal clinical features can improve the AUC (AUC = 0.923) compared with the use of MAGiC or perinatal clinical features alone.

Conclusion

The quantitative values of MAGiC can predict the prognosis of HE early, and the prediction efficiency is further optimized after being combined with clinical features.

Synthetic MRI in differentiating benign from metastatic retropharyngeal lymph node: combination with diffusion-weighted imaging

OBJECTIVES

This study aimed to evaluate the synthetic MRI (syMRI), its combination with diffusion-weighted imaging (DWI), and morphological features for discriminating benign from metastatic retropharyngeal lymph nodes (RLNs).

METHODS

Fifty-eight patients with a total of 63 RLNs (21 benign and 42 metastatic) were enrolled. The mean and standard deviation of syMRI-derived relaxometry parameters (T1, T2, PD; T1_SD, T2_SD, PD_SD) were obtained from two different regions of interest (namely, partial-lesion and full-lesion ROI). The parameters derived from benign and metastatic RLNs were compared using Student's t or chi-square tests. Logistic regression analysis was used to construct a multi-parameter model of syMRI, syMRI + DWI, and syMRI + DWI + morphological features. Areas under the curve (AUC) were compared using the DeLong test to determine the best diagnostic approach.

RESULTS

Benign RLNs had significantly higher T1, T2, PD, and T1_SD values compared with metastatic RLNs in both partial-lesion and full-lesion ROI (all p < 0.05). The T1_SD obtained from full-lesion ROI showed the best diagnostic performance among all syMRI-derived single parameters. The AUC of combined syMRI multiple parameters (T1, T2, PD, T1_SD) were higher than those of any single parameter from syMRI. The combination of synthetic MRI and DWI can improve the AUC regardless of ROI delineation. Furthermore, the combination of synthetic MRI, DWI-derived quantitative parameters, and morphological features can significantly improve the overall diagnostic performance.

CONCLUSIONS

The value of syMRI has been validated in differential diagnosis of benign and metastatic RLNs, and syMRI + DWI + morphological features can further improve the diagnostic efficiency for discriminating these two entities.

KEY POINTS

• Synthetic MRI was useful in differential diagnosis of benign and metastatic RLNs. • The combination of syMRI, DWI, and morphological features can significantly improve the diagnostic efficiency.

Assessment of cognitive impairment after acute cerebral infarction with T1 relaxation time measured by MP2RAGE sequence and cerebral hemodynamic by transcranial Doppler

Objective

This study aimed to investigate early brain microstructural changes discovered using magnetization-prepared two rapid acquisition gradient echo (MP2RAGE) sequence and cerebral hemodynamic using TCD for cognitive impairment after acute cerebral infarction.

Methods

We enrolled 43 patients with acute cerebral infarction and 21 healthy people in the study, who were subjected to cognitive assessments, the MP2RAGE sequence, and a cerebral hemodynamic examination. A total of 26 brain regions of interest were investigated. Furthermore, we used cerebral hemodynamics to explain brain microstructural changes, which helped us better understand the pathophysiology of cognitive impairment after acute cerebral infarction and guide treatment.

Results

T1 relaxation times in the left frontal lobe, right frontal lobe, right temporal lobe, left precuneus, left thalamus, right hippocampus, right head of caudate nucleus, and splenium of corpus callosum were substantially different across the three groups, which were significantly correlated with neuropsychological test scores. CI group patients had significantly lower cerebral blood flow velocity than those in the N-CI and Normal groups. The receiver operating curve analysis revealed that most T1 relaxation times had high sensitivity and specificity, especially on the right temporal lobe and right frontal lobe. There was a potential correlation between T1 relaxation times and MMSE scores through TCD parameters.

Conclusion

The MP2RAGE sequence can detect alterations in whole brain microstructure in patients with cognitive impairment after acute cerebral infarction. Brain microstructural changes could influence cognitive function through cerebral hemodynamics. T1 relaxation times on the right temporal lobe and the right frontal lobe are expected to be a prospective biomarker of cognitive impairment after acute cerebral infarction.

Combining navigator and optical prospective motion correction for high-quality 500 μm resolution quantitative multi-parameter mapping at 7T

PURPOSE

High-resolution quantitative multi-parameter mapping shows promise for non-invasively characterizing human brain microstructure but is limited by physiological artifacts. We implemented corrections for rigid head movement and respiration-related B0-fluctuations and evaluated them in healthy volunteers and dementia patients.

METHODS

Camera-based optical prospective motion correction (PMC) and FID navigator correction were implemented in a gradient and RF-spoiled multi-echo 3D gradient echo sequence for mapping proton density (PD), longitudinal relaxation rate (R1) and effective transverse relaxation rate (R2*). We studied their effectiveness separately and in concert in young volunteers and then evaluated the navigator correction (NAVcor) with PMC in a group of elderly volunteers and dementia patients. We used spatial homogeneity within white matter (WM) and gray matter (GM) and scan-rescan measures as quality metrics.

RESULTS

NAVcor and PMC reduced artifacts and improved the homogeneity and reproducibility of parameter maps. In elderly participants, NAVcor improved scan-rescan reproducibility of parameter maps (coefficient of variation decreased by 14.7% and 11.9% within WM and GM respectively). Spurious inhomogeneities within WM were reduced more in the elderly than in the young cohort (by 9% vs. 2%). PMC increased regional GM/WM contrast and was especially important in the elderly cohort, which moved twice as much as the young cohort. We did not find a significant interaction between the two corrections.

CONCLUSION

Navigator correction and PMC significantly improved the quality of PD, R1, and R2* maps, particularly in less compliant elderly volunteers and dementia patients.

Multiparametric mapping in the brain from conventional contrast-weighted images using deep learning

PURPOSE

To develop a deep-learning-based method to quantify multiple parameters in the brain from conventional contrast-weighted images.

METHODS

Eighteen subjects were imaged using an MR Multitasking sequence to generate reference T₁ and T₂ maps in the brain. Conventional contrast-weighted images consisting of T₁ MPRAGE, T₁ GRE, and T₂ FLAIR were acquired as input images. A U-Net-based neural network was trained to estimate T₁ and T₂ maps simultaneously from the contrast-weighted images. Six-fold cross-validation was performed to compare the network outputs with the MR Multitasking references.

RESULTS

The deep-learning T₁ /T₂ maps were comparable with the references, and brain tissue structures and image contrasts were well preserved. A peak signal-to-noise ratio >32 dB and a structural similarity index >0.97 were achieved for both parameter maps. Calculated on brain parenchyma (excluding CSF), the mean absolute errors (and mean percentage errors) for T₁ and T₂ maps were 52.7 ms (5.1%) and 5.4 ms (7.1%), respectively. ROI measurements on four tissue compartments (cortical gray matter, white matter, putamen, and thalamus) showed that T₁ and T₂ values provided by the network outputs were in agreement with the MR Multitasking reference maps. The mean differences were smaller than ± 1%, and limits of agreement were within ± 5% for T₁ and within ± 10% for T₂ after taking the mean differences into account.

CONCLUSION

A deep-learning-based technique was developed to estimate T₁ and T₂ maps from conventional contrast-weighted images in the brain, enabling simultaneous qualitative and quantitative MRI without modifying clinical protocols.

T1 Relaxation Times in the Cortex and Thalamus Are Associated With Working Memory and Information Processing Speed in Patients With Multiple Sclerosis

Background: Cortical and thalamic pathologies have been associated with cognitive impairment in patients with multiple sclerosis (MS). Objective: We aimed to quantify cortical and thalamic damage in patients with MS using a high-resolution T1 mapping technique and to evaluate the association of these changes with clinical and cognitive impairment. Methods: The study group consisted of 49 patients with mainly relapsing-remitting MS and 17 age-matched healthy controls who received 3T MRIs including a T1 mapping sequence (MP2RAGE). Mean T1 relaxation times (T1-RT) in the cortex and thalami were compared between patients with MS and healthy controls. Additionally, correlation analysis was performed to assess the relationship between MRI parameters and clinical and cognitive disability. Results: Patients with MS had significantly decreased normalized brain, gray matter, and white matter volumes, as well as increased T1-RT in the normal-appearing white matter, compared to healthy controls (p < 0.001). Partial correlation analysis with age, sex, and disease duration as covariates revealed correlations for T1-RT in the cortex (r = -0.33, p < 0.05), and thalami (right thalamus: r = -0.37, left thalamus: r = -0.50, both p < 0.05) with working memory and information processing speed, as measured by the Symbol-Digit Modalities Test. Conclusion: T1-RT in the cortex and thalamus correlate with information processing speed in patients with MS.

The use of positron emission tomography/magnetic resonance imaging in dementia: A literature review

OBJECTIVES

Positron emission tomography-magnetic resonance imaging (PET/MRI) is an emerging hybrid imaging system in clinical nuclear medicine. Research demonstrates a comparative utility to current unimodal and hybrid methods, including PET-computed tomography (PET/CT), in several medical subspecialities such as neuroimaging. The aim of this review is to critically evaluate the literature from 2016 to 2021 using PET/MRI for the investigation of patients with mild cognitive impairment or dementia, and discuss the evidence base for widening its application into clinical practice.

METHODS

A comprehensive literature search using the PubMed database was conducted to retrieve studies using PET/MRI in relation to the topics of mild cognitive impairment, dementia, or Alzheimer's disease between January 2016 and January 2021. This search strategy enabled studies on all dementia types to be included in the analysis. Studies were required to have a minimum of 10 human subjects and incorporate simultaneous PET/MRI.

RESULTS

A total of 116 papers were retrieved, with 39 papers included in the final selection. These were broadly categorised into reviews (12), technical/methodological papers (11) and new data studies (16). For the current review, discussion focused on findings from the new data studies.

CONCLUSIONS

PET/MRI offers additional insight into the underlying anatomical, metabolic and functional changes associated with dementia when compared with unimodal methods and PET/CT, particularly relating to brain regions including the hippocampus and default mode network. Furthermore, the improved diagnostic utility of PET/MRI, as reported by radiologists, offers improved classification of dementia patients, with important implications for clinical management.

Preoperative evaluation of extramural venous invasion in rectal cancer using radiomics analysis of relaxation maps from synthetic MRI

OBJECTIVE

To establish a radiomics nomogram based on relaxation maps for predicting the extramural venous invasion (EMVI) of rectal cancer (RC) and compare the diagnostic efficacy of the nomogram and subjective assessment by radiologists.

MATERIAL AND METHODS

Among 94 RC patients receiving direct surgical resection, 65 were randomly allocated to the training cohort and 29 to the validation cohort. Radiomics features were extracted from synthetic magnetic resonance imaging including T1, T2, and proton density (PD) maps. The least absolute shrinkage and selection operator methods were used for dimension reduction, feature selection, and radiomics model building. Multivariable logistic regression analysis was used for nomogram development. The performance of the nomogram was assessed with respect to its calibration, receiver operating characteristics (ROC) curve, and decision curve analysis.

RESULTS

The radiomics model demonstrated good predictive efficacy for EMVI, with an area under the ROC curve (AUC), sensitivity, and specificity of 0.912 (95% confidence interval (CI), 0.837-0.986), 0.824, and 0.875 in the training cohort and 0.877 (95% CI 0.751-1.000), 0.833, and 0.826 in the validation cohort. The nomogram had good diagnostic performance, with AUCs of 0.925 (95% CI 0.862-0.988) and 0.899 (95% CI 0.782-1.000) in the training and validation cohort. Furthermore, the radiomics signature showed better diagnostic efficiency than the subjective assessment by both readers (AUC =0.912 vs. 0.732 and 0.763, P = 0.023 and 0.028, respectively).

CONCLUSION

A radiomics nomogram was developed to preoperatively predict EMVI in RC patients. The application of the radiomics model based on relaxation maps could improve the diagnostic efficacy of EMVI.

Associations between brain volumetry and relaxometry signatures and the Edmonton Frail Scale in frailty

Background

Frailty is a geriatric condition characterized by a decreased reserve. The Edmonton frailty scale (EFS) has been widely used as an assessment tool in clinical practice. However, the brain's underlying pathophysiological changes in frailty and their associations with the EFS remain unclear. This study aimed to explore the associations between brain volumetry and relaxometry signatures and the EFS (and each domain score of the EFS) in frailty.

Methods

A total of 40 non-demented subjects were enrolled in this prospective study. Frailty assessment was performed for each subject according to the EFS. All subjects underwent synthetic magnetic resonance imaging (MRI) (MAGnetic resonance image Compilation, MAGiC) and three-dimensional fast spoiled gradient-recalled echo (3D-FSPGR) T1-weighted structural image acquisitions on a 3.0 T MR scanner. Brain segmentation was performed based on quantitative values obtained from the MAGiC and 3D-FSPGR images. Volumetry and relaxometry of the global brain and regional gray matter (GM) were also obtained. The associations between the total EFS score (and the score of each domain) and the brain's volumetry and relaxometry were investigated by partial correlation while eliminating the effects of age. Multiple comparisons of regional GM volumetry and relaxometry analyses were controlled by false discovery rate (FDR) correction. All data were analyzed using the SPSS 13.0 statistical package (IBM, Armonk, NY, USA) and MATLAB (MathWorks, Natick, MA, USA).

Results

For global volumetry, significant correlations were found between multiple global volumetry parameters and the EFS, as well as the cognition score, functional independence score, nutrition score, and functional performance score (P<0.05). For global relaxometry, notable positive correlations were found between the T2 values of gray and white matter (WM) and the EFS (r=0.357, P=0.026; r=0.357, P=0.026, respectively). Significant correlations were also identified between the T2 value of GM, the T1, T2, and PD values of WM, and the cognition score (r=0.426, P=0.007; r=0.456, P=0.003; r=0.377, P=0.018; r=0.424, P=0.007, respectively), functional independence score (r=-0.392, P=0.014; r=-0.611, P<0.001; r=-0.367, P=0.022; r=-0.569, P<0.001, respectively), and functional performance score (r=0.337, P=0.036; r=0.472, P=0.002; r=0.354, P=0.027; r=0.376, P=0.018, respectively). For regional GM volumetry, multiple regions showed significant negative correlations with the EFS (P<0.05). Notable negative correlations were found between multiple regional GM volume and the functional independence score (P<0.05). For regional GM relaxometry, the T1 and T2 values of several regions showed significant negative correlations with the functional independence score (T1 value of caudate, r=-0.617, P<0.001; T2 value of insula, r=-0.510, P=0.015; T2 value of caudate, r=-0.633, P<0.001, respectively). No significant correlation was found between the domain scores of the EFS and regional GM PD values (P>0.05).

Conclusions

In conclusion, brain volumetry and relaxometry signatures showed strong associations with the EFS and some EFS domain scores in frailty. These associations may reveal the possible underlying pathophysiology of the EFS and different domains of the EFS.

Carbonic anhydrase activity in the frontal lobe of human brain

Carbonic anhydrase (CA) plays an important role in many biological processes. Recent technological advances have demonstrated the feasibility of measuring CA activity in the occipital lobe of human subjects in vivo. In this work we report, for the first time, in vivo measurement of CA activity in the frontal lobe of human brain, where structural and function abnormalities are strongly associated with symptoms of major psychiatric disorders. Despite the much larger magnetic field distortion in the frontal lobe, the pseudo first-order bicarbonate dehydration rate constant was determined with high precision using in vivo ¹³ C magnetic resonance magnetization transfer spectroscopy following oral administration of [U-¹³ C₆ ]glucose. Nuclear Overhauser effect pulses were used to increase the signal-to-noise ratio; no proton decoupling was applied. The unidirectional dehydration rate constant of bicarbonate was found to be 0.26 ± 0.07 s^-1 , which is not statistically different from the dehydration rate constant in the occipital lobe determined in our previous study, indicating that CA activity in the two brain regions is essentially indistinguishable. These results demonstrate the feasibility of characterizing CA activity in the frontal lobe for future psychiatric studies.

Quantitative Analysis of Synthetic Magnetic Resonance Imaging in Alzheimer's Disease

Objectives: The purpose of this study was to evaluate the feasibility and whether synthetic MRI can benefit diagnosis of Alzheimer’s disease (AD).

Materials and Methods: Eighteen patients and eighteen age-matched normal controls (NCs) underwent MR examination. The mini-mental state examination (MMSE) scores were obtained from all patients. The whole brain volumetric characteristics, T1, T2, and proton density (PD) values of different cortical and subcortical regions were obtained. The volumetric characteristics and brain regional relaxation values between AD patients and NCs were compared using independent-samples t-test. The correlations between these quantitative parameters and MMSE score were assessed by the Pearson correlation in AD patients.

Results: Although the larger volume of cerebrospinal fluid (CSF), lower brain parenchymal volume (BPV), and the ratio of brain parenchymal volume to intracranial volume (BPV/ICV) were found in AD patients compared with NCs, there were no significant differences (p > 0.05). T1 values of right insula cortex and T2 values of left hippocampus and right insula cortex were significantly higher in AD patients than in NCs, but T1 values of left caudate showed a reverse trend (p < 0.05). As the MMSE score decreased in AD patients, the BPV and BPV/ICV decreased, while the volume of CSF and T1 values of bilateral insula cortex and bilateral hippocampus as well as T2 values of bilateral hippocampus increased (p < 0.05).

Conclusion: Synthetic MRI not only provides more information to differentiate AD patients from normal controls, but also reflects the disease severity of AD.

Histogram analysis of quantitative parameters from synthetic MRI: Correlations with prognostic factors and molecular subtypes in invasive ductal breast cancer

PURPOSE

To evaluate intra-tumoral heterogeneity through a histogram analysis of quantitative parameters obtained from synthetic MRI (magnetic resonance imaging), and determine correlations of these histogram characteristics with prognostic factors and molecular subtypes of invasive ductal carcinoma (IDC).

METHODS

A total of 122 IDC from 122 women who underwent preoperative synthetic MRI and DCE (dynamic contrast enhancement)-MRI were investigated. The synthetic MRI parameters (T1, T2, and PD (proton density)) were obtained. For each parameter, the minimum, 10th percentile, mean, median, 90th percentile, maximum, skewness, and kurtosis values of tumor were calculated, and correlations with prognostic factors and subtypes were assessed. The Mann-Whitney U test or the Student^'s t test were utilized to analyze the association between the histogram features of synthetic MRI parameters and prognostic factors. The Kruskal-Wallis test followed by the post-hoc test was used to analyze differences of synthetic MRI parameters among molecular subtypes.

RESULTS

IDC with high histopathologic grade showed statistically higher PD_maxium, T1_mean and T1_median values than those with low grade (p = 0.003, p = 0.007, p = 0.003). The T1_10th were significantly higher in cancers with PR (progesterone receptor) negativity than those with PR positivity (p = 0.005). ER-negative cancers had significant higher values of T2_10th, T2_mean, and T2_median than ER-positive cancers (p = 0.006, 0.002, and 0.006, respectively). The values of PD_median were significantly higher in IDC with HER2 (human epidermal growth factor receptor 2) positivity than those with HER2 negativity (p = 0.001). When discriminating molecular subtypes of IDC, the T2_mean achieved the highest performance. The T2_mean values of TN (triple-negative), luminal B and luminal A types are arranged in descending order (p <  0.0001).

CONCLUSIONS

Histogram features derived from synthetic MRI quantifies the distributions of tissue relaxation time and proton density, and may serve as a potential biomarker for discriminating histopathological grade, hormone receptor status, HER2 expression status and breast cancer subtypes.

Prediction of pathological prognostic factors of rectal cancer by relaxation maps from synthetic magnetic resonance imaging

PURPOSE

To explore the feasibility of relaxation maps from synthetic MRI for predicting pathological prognostic factors of rectal cancer (RC) and to compare the predictive performance of quantitative values and conventional subjective evaluation.

MATERIAL AND METHODS

A total of 94 patients with pathologically proven RC who underwent direct surgical resection were enrolled in this prospective study. Preoperative rectal MRI including synthetic MRI was performed. The mean T₁, T₂, and PD value of the whole tumor was obtained to preoperatively assess the pathological T stage, N stage, extramural venous invasion (EMVI), differentiation, and perineural invasion. Receiver operating characteristic curves were used to explore the predictive performance for assessing the prognostic factors. The T stage, N stage and EMVI status on conventional T2WI were evaluated and compared with the quantitative values.

RESULTS

The T₂ value decreased significantly in patients with positive perineural invasion, lymph node metastasis (LNM), EMVI, and higher T stage RC (p =  0.007 and < 0.001). The T₁ value of LNM and EMVI positive groups was significantly lower than those of the negative groups (p =  0.034 and 0.011). For predicting N stage and EMVI, the T₂ value demonstrated good performance with an AUC of 0.883 (95 % confidence interval, CI, 0.801-0.940) and 0.821 (95 % CI, 0.729-0.893); the T₂ value was superior to the T₁ value and subjective evaluation of radiologists (all p < 0.05).

CONCLUSION

Synthetic MRI is a promising tool for noninvasive evaluation of prognostic factors of RC by generating relaxation maps.

Multiparametric Quantitative MRI in Neurological Diseases

Magnetic resonance imaging (MRI) is the gold standard imaging technique for diagnosis and monitoring of many neurological diseases. However, the application of conventional MRI in clinical routine is mainly limited to the visual detection of macroscopic tissue pathology since mixed tissue contrasts depending on hardware and protocol parameters hamper its application for the assessment of subtle or diffuse impairment of the structural tissue integrity. Multiparametric quantitative (q)MRI determines tissue parameters quantitatively, enabling the detection of microstructural processes related to tissue remodeling in aging and neurological diseases. In contrast to measuring tissue atrophy via structural imaging, multiparametric qMRI allows for investigating biologically distinct microstructural processes, which precede changes of the tissue volume. This facilitates a more comprehensive characterization of tissue alterations by revealing early impairment of the microstructural integrity and specific disease-related patterns. So far, qMRI techniques have been employed in a wide range of neurological diseases, including in particular conditions with inflammatory, cerebrovascular and neurodegenerative pathology. Numerous studies suggest that qMRI might add valuable information, including the detection of microstructural tissue damage in areas appearing normal on conventional MRI and unveiling the microstructural correlates of clinical manifestations. This review will give an overview of current qMRI techniques, the most relevant tissue parameters and potential applications in neurological diseases, such as early (differential) diagnosis, monitoring of disease progression, and evaluating effects of therapeutic interventions.

A Comparison of Quantitative R1 and Cortical Thickness in Identifying Age, Lifespan Dynamics, and Disease States of the Human Cortex

Brain development and aging are complex processes that unfold in multiple brain regions simultaneously. Recently, models of brain age prediction have aroused great interest, as these models can potentially help to understand neurological diseases and elucidate basic neurobiological mechanisms. We test whether quantitative magnetic resonance imaging can contribute to such age prediction models. Using R1, the longitudinal rate of relaxation, we explore lifespan dynamics in cortical gray matter. We compare R1 with cortical thickness, a well-established biomarker of brain development and aging. Using 160 healthy individuals (6-81 years old), we found that R1 and cortical thickness predicted age similarly, but the regions contributing to the prediction differed. Next, we characterized R1 development and aging dynamics. Compared with anterior regions, in posterior regions we found an earlier R1 peak but a steeper postpeak decline. We replicate these findings: firstly, we tested a subset (N = 10) of the original dataset for whom we had additional scans at a lower resolution; and second, we verified the results on an independent dataset (N = 34). Finally, we compared the age prediction models on a subset of 10 patients with multiple sclerosis. The patients are predicted older than their chronological age using R1 but not with cortical thickness.

DSC perfusion-based collateral imaging and quantitative T2 mapping to assess regional recruitment of leptomeningeal collaterals and microstructural cortical tissue damage in unilateral steno-occlusive vasculopathy

Leptomeningeal collateral supply is considered pivotal in steno-occlusive vasculopathy to prevent chronic microstructural ischaemic tissue damage. The aim of this study was to assess the alleged protective role of leptomeningeal collaterals in patients with unilateral high-grade steno-occlusive vasculopathy using quantitative (q)T2 mapping and perfusion-weighted imaging (PWI)-based collateral abundance. High-resolution qT2 was used to estimate microstructural damage of the segmented normal-appearing cortex. Volumetric abundance of collaterals was assessed based on PWI source data. The ratio relative cerebral blood flow/relative cerebral blood volume (rCBF/rCBV) as a surrogate of relative cerebral perfusion pressure (rCPP) was used to investigate the intravascular hemodynamic competency of pial collateral vessels and the hemodynamic state of brain parenchyma. Within the dependent vascular territory with increased cortical qT2 values (P = 0.0001) compared to the contralateral side, parenchymal rCPP was decreased (P = 0.0001) and correlated negatively with increase of qT2 (P  < 0.05). Furthermore, volumetric abundance of adjacent leptomeningeal collaterals was significantly increased (P < 0.01) and negatively correlated with changes of parenchymal rCPP (P = 0.01). Microstructural cortical damage is closely related to restrictions of antegrade blood flow despite increased pial collateral vessel abundance. Therefore, increased leptomeningeal collateral supply cannot necessarily be regarded as a sign of effective compensation in patients with high-grade steno-occlusive vasculopathy.

Improved discrimination of molecular subtypes in invasive breast cancer: Comparison of multiple quantitative parameters from breast MRI

PURPOSE

To compare multiple quantitative parameters from breast magnetic resonance imaging (MRI) with the synthetic MRI sequence included for discrimination of molecular subtypes of invasive breast cancer.

MATERIALS AND METHODS

Between March 2019 and September 2020, two hundred breast cancer patients underwent preoperative breast multiparametric MRI examinations including synthetic MRI, diffusion weighted imaging (DWI) and dynamic contrast enhancement (DCE)-MRI sequences. MRI morphological features, T1 and T2 relaxation times (T1, T2) and proton density (PD) values from synthetic MRI, K_trans, K_ep, and V_e from DCE-MRI, mean apparent diffusion coefficient (ADC) from DWI and tumor volume were measured. Quantitative parameters were compared according to molecular markers and subtypes. Logistic regression were performed to find the related MRI parameters and establish combined parameters. The comparison between single and combined quantitative parameters by using DeLong tests.

RESULTS

T1, T2 values were significantly higher in hormone receptor (HR)- negative and Ki67 > 14% tumors (p < 0.05). Human epidermal growth factor receptor 2 (HER2)-positive tumors demonstrated significantly higher K_trans and K_ep (p < 0.01). Mean ADC values were significantly decreased in HR-positive and Ki67 > 14% tumors (p < 0.01). Tumor volumes were significantly higher in HER2-positive and Ki67 > 14% tumors (p < 0.05). Independent influencing factors were lower T2 values (p < 0.001), smaller tumor volume (p = 0.031) and higher mean ADC (p = 0.002) associated with luminal A subtype, while T1 values (p = 0.007) was the only quantitative parameter associated with triple-negative subtype. The diagnostic efficiency of combined parameters (T2 + mean ADC + volume) (AUC = 0.765) was significantly higher than that of mean ADC (AUC = 0.666, p = 0.031 by DeLong test) and volume (AUC = 0.650, p = 0.008 by DeLong test) for separating luminal A subtype.

CONCLUSIONS

MRI quantitative parameters could help distinguish molecular markers and subtypes. The emerging synthetic MRI parameters - T1 values were associated with the TN subtype, and combined parameters with added T2 values might improve the discrimination of the luminal A subtype. Application of synthetic MRI can enrich quantitative descriptors from breast MRI.

Cortical aging - new insights with multiparametric quantitative MRI

Understanding the microstructural changes related to physiological aging of the cerebral cortex is pivotal to differentiate healthy aging from neurodegenerative processes. The aim of this study was to investigate the age-related global changes of cortical microstructure and regional patterns using multiparametric quantitative MRI (qMRI) in healthy subjects with a wide age range. 40 healthy participants (age range: 2^nd to 8^th decade) underwent high-resolution qMRI including T1, PD as well as T2, T2* and T2′ mapping at 3 Tesla. Cortical reconstruction was performed with the FreeSurfer toolbox, followed by tests for correlations between qMRI parameters and age. Cortical T1 values were negatively correlated with age (p=0.007) and there was a widespread age-related decrease of cortical T1 involving the frontal and the parietotemporal cortex, while T2 was correlated positively with age, both in frontoparietal areas and globally (p=0.004). Cortical T2′ values showed the most widespread associations across the cortex and strongest correlation with age (r= -0.724, p=0.0001). PD and T2* did not correlate with age. Multiparametric qMRI allows to characterize cortical aging, unveiling parameter-specific patterns. Quantitative T2′ mapping seems to be a promising imaging biomarker of cortical age-related changes, suggesting that global cortical iron deposition is a prominent process in healthy aging.

Rotating frame MRI relaxations as markers of diffuse white matter abnormalities in multiple sclerosis

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T1ρ and RAFF4 - MRI protocols sensitive to slow motional regimes – are able to detect changes in T2w-defined normally appearing white matter of patients with multiple sclerosis.

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RAFF4, T1ρ and T2ρ showed differences in hippocampus in patients with multiple sclerosis despite the absence of alterations in resting-state functional MRI metrics.

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Hence, RAFF4, T1ρ and T2ρ hold promise as potential non-invasive tools for monitoring MS activity and eventually for the evaluation of therapeutic effects.

Even though MRI visualization of white matter lesions is pivotal for the diagnosis and management of multiple sclerosis (MS), the issue of detecting diffuse brain tissue damage beyond the apparent T2-hyperintense lesions continues to spark considerable interest. Motivated by the notion that rotating frame MRI methods are sensitive to slow motional regimes critical for tissue characterization, here we utilized novel imaging protocols of rotating frame MRI on a clinical 3 Tesla platform, including adiabatic longitudinal, T1ρ, and transverse, T2ρ, relaxation methods, and Relaxation Along a Fictitious Field (RAFF) in the rotating frame of rank 4 (RAFF4), in 10 relapsing-remitting multiple sclerosis patients and 10 sex- and age-matched healthy controls. T1ρ, T2ρ and RAFF4 relaxograms extracted from the whole white matter exhibited a significant shift towards longer relaxation time constants in MS patients as compared to controls. T1ρ and RAFF4 detected alterations even when considering only regions of normally appearing white matter (NAWM), while other MRI metrics such as T1w/T2w ratio and diffusion tensor imaging measures failed to find group differences. In addition, RAFF4, T2ρ and, to a lesser extent, T1ρ showed differences in subcortical grey matter structures, mainly hippocampus, whereas no functional changes in this region were detected in resting-state functional MRI metrics. We conclude that rotating frame MRI techniques are exceptionally sensitive methods for the detection of subtle abnormalities not only in NAWM, but also in deep grey matter in MS, where they surpass even highly sensitive measures of functional changes, which are often suggested to precede detectable structural alterations. Such abnormalities are consistent with a wide spectrum of different, but interconnected pathological features of MS, including the loss of neuronal cells and their axons, decreased levels of myelin even in NAWM, and altered iron content.

Diagnosis and Grading of Prostate Cancer by Relaxation Maps From Synthetic MRI

BACKGROUND

The interpretation system for prostate MRI is largely based on qualitative image contrast of different tissue types. Therefore, a fast, standardized, and robust quantitative technique is necessary. Synthetic MRI is capable of quantifying multiple relaxation parameters, which might have potential applications in prostate cancer (PCa).

PURPOSE

To investigate the use of quantitative relaxation maps derived from synthetic MRI for the diagnosis and grading of PCa.

STUDY TYPE

Prospective.

SUBJECTS

In all, 94 men with pathologically confirmed PCa or benign pathological changes.

FIELD STRENGTH/SEQUENCE

T₁ -weighted imaging, T₂ -weighted imaging, diffusion-weighted imaging, and synthetic MRI at 3.0T.

ASSESSMENT

Four kinds of tissue types were identified on pathology, including PCa, stromal hyperplasia (SH), glandular hyperplasia (GH), and noncancerous peripheral zone (PZ). PCa foci were grouped as low-grade (LG, Gleason score ≤6) and intermediate/high-grade (HG, Gleason score ≥7). Regions of interest were manually drawn by two radiologists in consensus on parametric maps according to the pathological results.

STATISTICAL TESTS

Independent sample t-test, Mann-Whitney U-test, and receiver operating characteristic curve analysis.

RESULTS

T₁ and T₂ values of PCa were significantly lower than SH (P = 0.015 and 0.002). The differences of T₁ and T₂ values between PCa and noncancerous PZ were also significant (P ≤ 0.006). The area under the curve (AUC) of the apparent diffusion coefficient (ADC) value was significantly higher than T₁ , T₂ , and proton density (PD) values in discriminating PCa from SH and noncancerous PZ (P ≤ 0.025). T₂ , PD, and ADC values demonstrated similar diagnostic performance in discriminating LG from HG PCa (AUC = 0.806 [0.640-0.918], 0.717 [0.542-0.854], and 0.817 [0.652-0.925], respectively; P ≥ 0.535).

DATA CONCLUSION

Relaxation maps derived from synthetic MRI were helpful for discriminating PCa from other benign pathologies. But the overall diagnostic performance was inferior to the ADC values. T₂ , PD, and ADC values performed similarly in discriminating LG from HG PCa lesions.

LEVEL OF EVIDENCE

2 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2020;52:552-564.

Cortical quantitative MRI parameters are related to the cognitive status in patients with relapsing-remitting multiple sclerosis

OBJECTIVES

We aimed to assess cortical damage in patients with relapsing-remitting multiple sclerosis (RRMS)/clinically isolated syndrome (CIS) with a multiparametric, surface-based quantitative MRI (qMRI) approach and to evaluate the correlation of imaging-derived parameters with cognitive scores, hypothesizing that qMRI parameters are correlated with cognitive abilities.

METHODS

Multiparametric qMRI-data (T1, T2 and T2* relaxation times and proton density (PD)) were obtained from 34 patients/24 matched healthy control subjects. Cortical qMRI values were analyzed on the reconstructed cortical surface with Freesurfer. We tested for group differences of cortical microstructural parameters between the healthy and patient collectives and for partial Pearson correlations of qMRI parameters with cognitive scores, correcting for age.

RESULTS

Cortical T2-/T2*-/PD values and four cognitive parameters differed between groups (p ≤ 0.046). These cognitive scores, reflecting information processing speed, verbal memory, visuospatial abilities, and attention, were correlated with cortical T2 (p ≤ 0.02) and T2* (p ≤ 0.03). Cortical changes appeared heterogeneous across the cortex and their distribution differed between the parameters. Vertex-wise correlation of T2 with neuropsychological parameters revealed specific patterns of cortical damage being related to distinct cognitive deficits.

CONCLUSIONS

Microstructural changes are distributed heterogeneously across the cortex in RRMS/CIS. QMRI has the potential to provide surrogate parameters for the assessment of cognitive impairment in these patients for clinical studies. The characteristics of cognitive impairment in RRMS might depend on the distribution of cortical changes.

KEY POINTS

• The goal of the presented study was to investigate cortical changes in RRMS/CIS and their relation to the cognitive status, using multiparametric quantitative MRI. • Cortical T2, T2*, and PD increases observed in patients appeared heterogeneous across the cortex and their distribution differed between the parameters. • Vertex-wise correlation of T2 with neuropsychological scores revealed specific patterns of cortical changes being related to distinct cognitive deficits.

Gray Matter Alterations in Early and Late Relapsing-Remitting Multiple Sclerosis Evaluated with Synthetic Quantitative Magnetic Resonance Imaging

Extensive gray matter (GM) involvement has been demonstrated in multiple sclerosis (MS) patients. This study was aimed to identify GM alterations in relapsing-remitting MS (RRMS) patients using synthetic quantitative MRI (qMRI). We assessed myelin volume fraction (MVF) in each voxel on the basis of R1 and R2 relaxation rates and proton density in 14 early and 28 late (disease duration ≤5 and >5 years, respectively) RRMS patients, and 15 healthy controls (HCs). The MVF and myelin volumes of GM (GM-MyVol) were compared between groups using GM-based spatial statistics (GBSS) and the Kruskal-Wallis test, respectively. Correlations between MVF or GM-MyVol and disease duration or expanded disability status scale were also evaluated. RRMS patients showed a lower MVF than HCs, predominantly in the limbic and para-limbic areas, with more extensive areas noted in late RRMS patients. Late-RRMS patients had the smallest GM-MyVol (20.44 mL; early RRMS, 22.77 mL; HCs, 23.36 mL). Furthermore, the GM-MyVol in the RRMS group was inversely correlated with disease duration (r = -0.43, p = 0.005). In conclusion, the MVF and MyVol obtained by synthetic qMRI can be used to evaluate GM differences in RRMS patients.

Multiparameter MRI quantification of microstructural tissue alterations in multiple sclerosis

Objectives

Conventional MRI is not sensitive to many pathological processes underpinning multiple sclerosis (MS) ongoing in normal appearing brain tissue (NABT). Quantitative MRI (qMRI) and a multiparameter mapping (MPM) protocol are used to simultaneously quantify magnetization transfer (MT) saturation, transverse relaxation rate R2* (1/T2*) and longitudinal relaxation rate R1 (1/T1), and assess differences in NABT microstructure between MS patients and healthy controls (HC).

Methods

This prospective cross-sectional study involves 36 MS patients (21 females, 15 males; age range 22–63 years; 15 relapsing-remitting MS - RRMS; 21 primary or secondary progressive MS - PMS) and 36 age-matched HC (20 females, 16 males); age range 21–61 years). The qMRI maps are computed and segmented in lesions and 3 normal appearing cerebral tissue classes: normal appearing cortical grey matter (NACGM), normal appearing deep grey matter (NADGM), normal appearing white matter (NAWM). Individual median values are extracted for each tissue class and MR parameter. MANOVAs and stepwise regressions assess differences between patients and HC.

Results

MS patients are characterized by a decrease in MT, R2* and R1 within NACGM (p < .0001) and NAWM (p < .0001). In NADGM, MT decreases (p < .0001) but R2* and R1 remain normal. These observations tend to be more pronounced in PMS. Quantitative MRI parameters are independent predictors of clinical status: EDSS is significantly related to R1 in NACGM and R2* in NADGM; the latter also predicts motor score. Cognitive score is best predicted by MT parameter within lesions.

Conclusions

Multiparametric data of brain microstructure concord with the literature, predict clinical performance and suggest a diffuse reduction in myelin and/or iron content within NABT of MS patients.

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We revisit microstructural alterations of NABT in MS patients by simultaneously quantifying three MRI parameters.

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Data suggest reduction of MT/R2*/R1 in NABT of MS patients, suggesting a reduction in myelin and/or iron content.

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Quantitative MRI parameters in NABT are independent predictors of clinical status.

7 T Magnetic Resonance Spectroscopic Imaging in Multiple Sclerosis: How Does Spatial Resolution Affect the Detectability of Metabolic Changes in Brain Lesions?

OBJECTIVES

The aim of this study was to assess the utility of increased spatial resolution of magnetic resonance spectroscopic imaging (MRSI) at 7 T for the detection of neurochemical changes in multiple sclerosis (MS)-related brain lesions.

MATERIALS AND METHODS

This prospective, institutional review board-approved study was performed in 20 relapsing-remitting MS patients (9 women/11 men; mean age ± standard deviation, 30.8 ± 7.7 years) after receiving written informed consent. Metabolic patterns in MS lesions were compared at 3 different spatial resolutions of free induction decay MRSI with implemented parallel imaging acceleration: 2.2 × 2.2 × 8 mm; 3.4 × 3.4 × 8 mm; and 6.8 × 6.8 × 8 mm voxel volumes, that is, matrix sizes of 100 × 100, 64 × 64, and 32 × 32, respectively. The quality of data was assessed by signal-to-noise ratio and Cramér-Rao lower bounds. Statistical analysis was performed using Wilcoxon signed-rank tests with correction for multiple testing.

RESULTS

Seventy-seven T2-hyperintense MS lesions were investigated (median volume, 155.7 mm; range, 10.8-747.0 mm). The mean metabolic ratios in lesions differed significantly between the 3 MRSI resolutions (ie, 100 × 100 vs 64 × 64, 100 × 100 vs 32 × 32, and 64 × 64 vs 32 × 32; P < 0.001). With the ultra-high resolution (100 × 100), we obtained 40% to 80% higher mean metabolic ratios and 100% to 150% increase in maximum metabolic ratios in the MS lesions compared with the lowest resolution (32 × 32), while maintaining good spectral quality (signal-to-noise ratio >12, Cramér-Rao lower bounds <20%) and measurement time of 6 minutes. There were 83% of MS lesions that showed increased myo-inositol/N-acetylaspartate with the 100 × 100 resolution, but only 66% were distinguishable with the 64 × 64 resolution and 35% with the 32 × 32 resolution.

CONCLUSIONS

Ultra-high-resolution MRSI (~2 × 2 × 8 mm voxel volume) can detect metabolic alterations in MS, which cannot be recognized by conventional MRSI resolutions, within clinically acceptable time.

Personalized translational epilepsy research - Novel approaches and future perspectives: Part I: Clinical and network analysis approaches

Despite the availability of more than 15 new "antiepileptic drugs", the proportion of patients with pharmacoresistant epilepsy has remained constant at about 20-30%. Furthermore, no disease-modifying treatments shown to prevent the development of epilepsy following an initial precipitating brain injury or to reverse established epilepsy have been identified to date. This is likely in part due to the polyetiologic nature of epilepsy, which in turn requires personalized medicine approaches. Recent advances in imaging, pathology, genetics and epigenetics have led to new pathophysiological concepts and the identification of monogenic causes of epilepsy. In the context of these advances, the First International Symposium on Personalized Translational Epilepsy Research (1st ISymPTER) was held in Frankfurt on September 8, 2016, to discuss novel approaches and future perspectives for personalized translational research. These included new developments and ideas in a range of experimental and clinical areas such as deep phenotyping, quantitative brain imaging, EEG/MEG-based analysis of network dysfunction, tissue-based translational studies, innate immunity mechanisms, microRNA as treatment targets, functional characterization of genetic variants in human cell models and rodent organotypic slice cultures, personalized treatment approaches for monogenic epilepsies, blood-brain barrier dysfunction, therapeutic focal tissue modification, computational modeling for target and biomarker identification, and cost analysis in (monogenic) disease and its treatment. This report on the meeting proceedings is aimed at stimulating much needed investments of time and resources in personalized translational epilepsy research. Part I includes the clinical phenotyping and diagnostic methods, EEG network-analysis, biomarkers, and personalized treatment approaches. In Part II, experimental and translational approaches will be discussed (Bauer et al., 2017) [1].

Volumetric reconstruction from printed films: Enabling 30 year longitudinal analysis in MR neuroimaging

Hospitals often hold historical MR image data printed on films without being able to make it accessible to modern image processing techniques. Having the possibility to recover geometrically consistent, volumetric images from scans acquired decades ago will enable more comprehensive, longitudinal studies to understand disease progressions. In this paper, we propose a consistent framework to reconstruct a volumetric representation from printed films holding thick single-slice brain MR image acquisitions dating back to the 1980's. We introduce a flexible framework based on semi-automatic slice extraction, followed by automated slice-to-volume registration with inter-slice transformation regularisation and slice intensity correction. Our algorithm is robust against numerous detrimental effects being present in archaic films. A subsequent, isotropic total variation deconvolution technique revitalises the visual appearance of the obtained volumes. We assess the accuracy and perform the validation of our reconstruction framework on a uniquely long-term MRI dataset where a ground-truth is available. This method will be used to facilitate a robust longitudinal analysis spanning 30 years of MRI scans.

Longitudinal quantitative MRI assessment of cortical damage in multiple sclerosis: A pilot study

PURPOSE

Quantitative MRI (qMRI) allows assessing cortical pathology in multiple sclerosis (MS) on a microstructural level, where cortical damage has been shown to prolong T₁ -relaxation time and increase proton density (PD) compared to controls. However, the evolution of these changes in MS over time has not been investigated so far. In this pilot study we used an advanced method for the longitudinal assessment of cortical tissue change in MS patients with qMRI in comparison to cortical atrophy, as derived from conventional MRI.

MATERIALS AND METHODS

Twelve patients with relapsing-remitting MS underwent 3T T₁ /PD-mapping at two timepoints with a mean interval of 12 months. The respective cortical T₁ /PD-values were extracted from the middle of the cortical layer and the cortical thickness was measured for surface-based identification of clusters with increasing/decreasing values.

RESULTS

Statistical analysis showed clusters with increasing PD- and T₁ -values over time (annualized rate for T₁ /PD increase in these clusters: 3.4 ± 2.56% for T₁ , P = 0.0007; 2.3 ± 2.59% for PD, P = 0.01). Changes are heterogeneous across the cortex and different patterns of longitudinal PD and T₁ increase emerged. Analysis of the cortical thickness yielded only one small cluster indicating a decrease of cortical thickness.

CONCLUSION

Changes of cortical tissue composition in MS seem to be reflected by a spatially inhomogeneous, multifocal increase of the PD values, indicating replacement of neural tissue by water, and of the T₁ -relaxation time, a surrogate of demyelination, axonal loss, and gliosis. qMRI changes were more prominent than cortical atrophy, showing the potential of qMRI techniques to quantify microstructural alterations that remain undetected by conventional MRI.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 1 J. Magn. Reson. Imaging 2017;46:1485-1490.

Comparison of two quantitative proton density mapping methods in multiple sclerosis

OBJECTIVE

Proton density (PD) mapping requires correction for the receive profile (RP), which is frequently performed via bias-field correction. An alternative RP-mapping method utilizes a comparison of uncorrected PD-maps and a value ρ(T1) directly derived from T1-maps via the Fatouros equation. This may be problematic in multiple sclerosis (MS), if respective parameters are only valid for healthy brain tissue. We aimed to investigate whether the alternative method yields correct PD values in MS patients.

MATERIALS/METHODS

PD mapping was performed on 27 patients with relapsing-remitting MS and 27 healthy controls, utilizing both methods, yielding reference PD values (PD_ref, bias-field method) and PD_alt (alternative method).

RESULTS

PD_alt-values closely matched PD_ref, both for patients and controls. In contrast, ρ(T1) differed by up to 3 % from PD_ref, and the voxel-wise correlation between PD_ref and ρ(T1) was reduced in a patient subgroup with a higher degree of disability. Still, discrepancies between ρ(T1) and PD_ref were almost identical across different tissue types, thus translating into a scaling factor, which cancelled out during normalization to 100 % in CSF, yielding a good agreement between PD_alt and PD_ref.

CONCLUSION

RP correction utilizing the auxiliary parameter ρ(T1) derived via the Fatouros equation provides accurate PD results in MS patients, in spite of discrepancies between ρ(T1) and actual PD values.

The Relationship between Gray Matter Quantitative MRI and Disability in Secondary Progressive Multiple Sclerosis

PURPOSE

In secondary progressive Multiple Sclerosis (SPMS), global neurodegeneration as a driver of disability gains importance in comparison to focal inflammatory processes. However, clinical MRI does not visualize changes of tissue composition outside MS lesions. This quantitative MRI (qMRI) study investigated cortical and deep gray matter (GM) proton density (PD) values and T1 relaxation times to explore their potential to assess neuronal damage and its relationship to clinical disability in SPMS.

MATERIALS AND METHODS

11 SPMS patients underwent quantitative T1 and PD mapping. Parameter values across the cerebral cortex and deep GM structures were compared with 11 healthy controls, and correlation with disability was investigated for regions exhibiting significant group differences.

RESULTS

PD was increased in the whole GM, cerebral cortex, thalamus, putamen and pallidum. PD correlated with disability in the whole GM, cerebral cortex, putamen and pallidum. T1 relaxation time was prolonged and correlated with disability in the whole GM and cerebral cortex.

CONCLUSION

Our study suggests that the qMRI parameters GM PD (which likely indicates replacement of neural tissue with water) and cortical T1 (which reflects cortical damage including and beyond increased water content) are promising qMRI candidates for the assessment of disease status, and are related to disability in SPMS.

Evaluation of brain ageing: a quantitative longitudinal MRI study over 7 years

OBJECTIVES

T1 relaxometry is a promising tool for the assessment of microstructural changes during brain ageing. Previous cross-sectional studies demonstrated increasing T1 values in white and decreasing T1 values in grey matter over the lifetime. However, these findings have not yet been confirmed on the basis of a longitudinal study. In this longitudinal study over 7 years, T1 relaxometry was used to investigate the dynamics of age-related microstructural changes in older healthy subjects.

METHODS

T1 mapping was performed in 17 healthy subjects (range 51-77 years) at baseline and after 7 years. Advanced cortical and white matter segmentation was used to determine mean T1 values in the cortex and white matter.

RESULTS

The analysis revealed a decrease of mean cortical T1 values over 7 years, the rate of T1 reduction being more prominent in subjects with higher age. T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. In contrast, mean white matter T1 values remained stable.

CONCLUSIONS

T1 mapping is shown to be sensitive to age-related microstructural changes in healthy ageing subjects in a longitudinal setting. Data of a cohort in late adulthood and the senescence period demonstrate a decrease of cortical T1 values over 7 years, most likely reflecting decreasing water content and increased iron concentrations.

KEY POINTS

• T1 mapping is sensitive to age-related microstructural changes in a longitudinal setting. • T1 decreases were predominantly localized in the lateral frontal, parietal and temporal cortex. • The rate of T1 reduction was more prominent in subjects with higher age. • These changes most likely reflect decreasing cortical water and increasing iron concentrations.

Assessment of cortical damage in early multiple sclerosis with quantitative T2 relaxometry

T2 relaxation time is a quantitative MRI in vivo surrogate of cerebral tissue damage in multiple sclerosis (MS) patients. Cortical T2 prolongation is a known feature in later disease stages, but has not been demonstrated in the cortical normal appearing gray matter (NAGM) in early MS. This study centers on the quantitative evaluation of the tissue parameter T2 in cortical NAGM in a collective of early MS and clinically isolated syndrome (CIS) patients, hypothesizing that T2 prolongation is already present at early disease stages and variable over space, in line with global and focal inflammatory processes in MS. Additionally, magnetization transfer ratio (MTR) mapping was performed for further characterization of the expected cortical T2 alteration. Quantitative T2 and MTR maps were acquired from 12 patients with CIS and early MS, and 12 matched healthy controls. The lesion-free part of the cortical volume was identified, and the mean T2 and MTR values and their standard deviations within the cortical volume were determined. For evaluation of spatial specificity, cortical lobar subregions were tested separately for differences of mean T2 and T2 standard deviation. We detected significantly prolonged T2 in cortical NAGM in patients. T2 prolongation was found across the whole cerebral cortex and in all individual lobar subregions. Significantly higher standard deviations across the respective region of interest were found for the whole cerebral cortex and all subregions, suggesting the occurrence of spatially inhomogeneous cortical damage in all regions studied. A trend was observed for MTR reduction and increased MTR variability across the whole cortex in the MS group, suggesting demyelination. In conclusion, our results suggest that cortical damage in early MS is evidenced by spatially inhomogeneous T2 prolongation which goes beyond demyelination. Iron deposition, which is known to decrease T2, seems less prominent.

PET/MRI of central nervous system: current status and future perspective

Imaging plays an increasingly important role in the early diagnosis, prognosis prediction and therapy response evaluation of central nervous system (CNS) diseases. The newly emerging hybrid positron emission tomography/magnetic resonance imaging (PET/MRI) can perform "one-stop-shop" evaluation, including anatomic, functional, biochemical and metabolic information, even at the molecular level, for personalised diagnoses and treatments of CNS diseases. However, there are still several problems to be resolved, such as appropriate PET detectors, attenuation correction and so on. This review will introduce the basic physical principles of PET/MRI and its potential clinical applications in the CNS. We also provide the future perspectives for this field.

KEY POINTS

• PET/MRI can simultaneously provide anatomic, functional, biochemical and metabolic information. • PET/MRI has promising potential in various central nervous system diseases. • Research on the future implementation of PET/MRI is challenging and encouraging.