Lesion Indexes Predict Early Neurologic Deterioration in Lenticulostriate Single Small Subcortical Infarction.

BACKGROUND AND PURPOSE: Early neurologic deterioration (END) often occurs during hospitalization in single small subcortical infarction (SSSI). The objective was to identify imaging predictors of END. MATERIALS AND METHODS: SSSIs in the lenticulostriate artery within 72 hours of stroke onset from January 2015 to June 2021 were consecutively enrolled. The posteriority and laterality indexes were assessed on the second section from the top of the corona radiata section showing the lateral ventricle on DWI. A multivariate logistic analysis was used to explore the predictors of END. RESULTS: A total of 402 patients were included in this study, among whom 93 (23.1%) experienced END. The optimal cutoff points of the posteriority and laterality indexes for predicting END were given by a receiver operating characteristic curve. A multivariate logistic analysis showed that the posteriority index of ≥0.669 (OR: 2.53; 95% CI: 1.41-4.56; P = .002) and the laterality index of ≥0.950 (OR: 2.03; 95% CI: 1.03-4.00; P = .042) were independently associated with the risk of END. Accordingly, the SSSIs were further divided into 4 types: anterior lateral type (AL-type), anterior medial type (AM-type), posterior lateral type (PL-type), and posterior medial type (PM-type). After the multivariate analysis, in comparison with the AL-type, the AM-type (OR: 3.26; 95% CI: 1.10-9.65), PL-type (OR: 4.68; 95% CI: 1.41-15.56), and PM-type (OR: 6.77; 95% CI: 2.53-18.04) carried significantly elevated risks of END. The PM-type was associated with the highest risk of END. CONCLUSIONS: The PM-type was found to be associated with the highest risk of END.

Comparison of two region-of-interest placement methods for histogram analysis of apparent diffusion coefficient maps for glioma grading.

Objectives: We assessed the value of histogram analysis (HA) of apparent diffusion coefficient (ADC) maps for grading low-grade (LGG) and high-grade (HGG) gliomas. Methods: We compared the diagnostic performance of two region-of-interest (ROI) placement methods (ROI 1: the entire tumor; ROI 2: the tumor excluding cystic and necrotic portions). We retrospectively evaluated 54 patients with supratentorial gliomas (18 LGG and 36 HGG). All subjects underwent standard 3T contrast-enhanced magnetic resonance imaging. Histogram parameters of ADC maps calculated with the two segmentation methods comprised mean, median, maxi-mum, minimum, kurtosis, skewness, entropy, standard deviation (sd), mean of positive pixels (mpp), uniformity of positive pixels, and their ratios (r) between lesion and normal white matter. They were compared using the independent t-test, chi-square test, or Mann-Whitney U test. For statistically significant results, receiver operating characteristic curves were constructed, and the optimal cutoff value, sensitivity, and specificity were determined by maximizing Youden's index. Results: The ROI 1 method resulted in significantly higher rADC mean, rADC median, and rADC mpp for LGG than for HGG; these parameters had value for predicting the histological glioma grade with a cutoff (sensitivity, specificity) of 1.88 (77.8%, 61.1%), 2.25 (44.4%, 97.2%), and 1.88 (77.8%, 63.9%), respectively. The ROI 2 method resulted in significantly higher ADC mean, ADC median, ADC mpp, ADC sd, ADC max, rADC median, rADC mpp, rADC mean, rADC sd, and rADC max for LGG than for HGG, while skewness was lower for LGG than for HGG (0.27 [0.98] vs 0.91 [0.81], p = 0.014). In ROI 2, ADC median, ADC mpp, ADC mean, rADC median, rADC mpp, and rADC mean performed well in differentiating glioma grade with cutoffs (sensitivity, specificity) of 1.28 (77.8%, 88.9%), 1.28 (77.8%, 88.9%), 1.25 (77.8%, 91.7%), 1.81 (83.3%, 91.7%), 1.74 (83.3%, 91.7%), and 1.81 (83.3%, 91.7%), respectively. Conclusions: HA parameters had value for grading gliomas. Ex-cluding cystic and necrotic portions of the tumor for measuring HA parameters was preferable to using the entire tumor as the ROI. In this segmentation, rADC median showed the highest performance in predicting histological glioma grade, followed by rADC mpp, rADC mean, ADC median, ADC mpp, and ADC mean.

Utility of Chemical Shift Imaging and Diffusion-weighted Images/Apparent Diffusion Coefficient Maps as a Tool for Evaluation of Solid Renal Tumors.

OBJECTIVES: To study the utility of chemical shift imaging (CSI) and diffusion-weighted images (DWI)/apparent diffusion coefficient (ADC) maps for the evaluation of solid renal tumors. METHODS: Magnetic resonance imaging (MRI) has an equivalent application as computerized tomography (CT) in the characterization of renal masses. It offers a radiation-free imaging technique and has a better soft tissue contrast than CT. Also, MRI is favored in patients with chronic kidney disease. MRI is useful when findings on CT are equivocal. The role of DWI in characterizing solid renal lesions as malignant is encouraging, and DWI can be particularly useful when gadolinium is contraindicated. CSI is useful in differentiating angiomyolipoma (AML) from clear cell (cc) renal cell carcinoma (RCC). We did a cross-sectional study on 24 patients with solid renal masses. MRI of the upper abdomen (from the dome of the diaphragm to the iliac crest) will be done on an MRI machine in our department (1.5T, ACHIEVA, Phillips medical system) using the torso coil. RESULT: There was no significant association seen in terms of ADC values and histological subtypes (χ2 = 11.222, p = 0.082). In our study, 50% (one out of two) of AML showed a signal drop, whereas 40% of cases (6 out of 15) of ccRCC and 66% (two out of three) of papillary RCC showed a signal drop. CONCLUSION: In this article, we concluded CSI, although a useful tool to look for microscopic fat, can't be used as a reliable marker to rule in cc-carcinoma as both AML and papillary cell carcinoma have microscopic fat. Further, no histological classification can be done on the basis of DWI/ADC images.

An International Expert-Based Consensus on the Definition of a Clinical Near-Complete Response After Neoadjuvant (Chemo)radiotherapy for Rectal Cancer.

BACKGROUND: A variety of definitions for a clinical near-complete response after neoadjuvant (chemo) radiotherapy for rectal cancer are currently used. This variety leads to inconsistency in clinical practice, long-term outcome, and trial enrollment. OBJECTIVE: The aim of this study was to reach expert-based consensus on the definition of a clinical near-complete response after (chemo) radiotherapy. DESIGN: A modified Delphi process, including a systematic review, 3 surveys, and 2 meetings, was performed with an international expert panel consisting of 7 surgeons and 4 radiologists. The surveys consisted of individual features, statements, and feature combinations (endoscopy, T2-weighted MRI, and diffusion-weighted MRI). SETTING: The modified Delphi process was performed in an online setting; all 3 surveys were completed online by the expert panel, and both meetings were hosted online. MAIN OUTCOME MEASURES: The main outcome was to reach consensus (80% or more agreement). RESULTS: The expert panel reached consensus on a 3-tier categorization of the near-complete response category based on the likelihood of the response to evolve into a clinical complete response after a longer waiting interval. The panelists agreed that a near-complete response is a temporary entity only to be used in the first 6 months after (chemo)radiotherapy. Furthermore, consensus was reached that the lymph node status should be considered when deciding on a near-complete response and that biopsies are not always needed when a near-complete response is found. No consensus was reached on whether primary staging characteristics have to be taken into account when deciding on a near-complete response. LIMITATIONS: This 3-tier subcategorization is expert-based; therefore, there is no supporting evidence for this subcategorization. Also, it is unclear whether this subcategorization can be generalized into clinical practice. CONCLUSIONS: Consensus was reached on the use of a 3-tier categorization of a near-complete response, which can be helpful in daily practice as guidance for treatment and to inform patients with a near-complete response on the likelihood of successful organ preservation. See Video Abstract. UN CONSENSO INTERNACIONAL BASADO EN EXPERTOS ACERCA DE LA DEFINICIN DE UNA RESPUESTA CLNICA CASI COMPLETA DESPUS DE QUIMIORADIOTERAPIA NEOADYUVANTE CONTRA EL CNCER DE RECTO: ANTECEDENTES:Actualmente, se utilizan una variedad de definiciones para una respuesta clínica casi completa después de quimioradioterapia neoadyuvante contra el cáncer de recto. Esta variedad resulta en inconsistencia en la práctica clínica, los resultados a largo plazo y la inscripción en ensayos.OBJETIVO:El objetivo de este estudio fue llegar a un consenso de expertos sobre la definición de una respuesta clínica casi completa después de quimioradioterapia.DISEÑO:Se realizó un proceso Delphi modificado que incluyó una revisión sistemática, 3 encuestas y 2 reuniones con un panel internacional de expertos compuesto por siete cirujanos y 4 radiólogos. Las encuestas consistieron en características individuales, declaraciones y combinaciones de características (endoscopía, T2W-MRI y DWI).AJUSTE:El proceso Delphi modificado se realizó en un entorno en línea; el panel de expertos completó las tres encuestas en línea y ambas reuniones se realizaron en línea.PRINCIPALES MEDIDAS DE RESULTADO:El resultado principal fue llegar a un consenso (≥80% de acuerdo).RESULTADOS:El panel de expertos llegó a un consenso sobre una categorización de tres niveles de la categoría de respuesta casi completa basada en la probabilidad de que la respuesta evolucione hacia una respuesta clínica completa después de un intervalo de espera más largo. Los panelistas coincidieron en que una respuesta casi completa es una entidad temporal que sólo debe utilizarse en los primeros 6 meses después de la quimioradioterapia. Además, se llegó a un consenso en que se debe considerar el estado de los nódulos linfáticos al decidir sobre una respuesta casi completa y que no siempre se necesitan biopsias cuando se encuentra una respuesta casi completa. No se llegó a un consenso sobre si se deben tener en cuenta las características primarias de estadificación al decidir una respuesta casi completa.LIMITACIONES:Esta subcategorización de 3 niveles está basada en expertos; por lo tanto, no hay evidencia que respalde esta subcategorización. Además, no está claro si esta subcategorización puede generalizarse a la práctica clínica.CONCLUSIONES:Se alcanzó consenso sobre el uso de una categorización de 3 niveles de una respuesta casi completa que puede ser útil en la práctica diaria como guía para el tratamiento y para informar a los pacientes con una respuesta casi completa sobre la probabilidad de una preservación exitosa del órgano. (Traducción - Dr. Aurian Garcia Gonzalez).

Performance of Diffusion-weighted Imaging-based Noncontrast MRI Protocols for Diagnosis of Breast Cancer: A Systematic Review and Meta-Analysis.

Background Diffusion-weighted imaging (DWI) is increasingly recognized as a powerful diagnostic tool and tested alternative to contrast-enhanced (CE) breast MRI. Purpose To perform a systematic review and meta-analysis that assesses the diagnostic performance of DWI-based noncontrast MRI protocols (ncDWI) for the diagnosis of breast cancer. Materials and Methods A systematic literature search in PubMed for articles published from January 1985 to September 2023 was performed. Studies were excluded if they investigated malignant lesions or selected patients and/or lesions only, used DWI as an adjunct technique to CE MRI, or were technical studies. Statistical analysis included pooling of diagnostic accuracy and investigating between-study heterogeneity. Additional subgroup comparisons of ncDWI to CE MRI and standard mammography were performed. Results A total of 28 studies were included, with 4406 lesions (1676 malignant, 2730 benign) in 3787 patients. The pooled sensitivity and specificity of ncDWI were 86.5% (95% CI: 81.4, 90.4) and 83.5% (95% CI: 76.9, 88.6), and both measures presented with high between-study heterogeneity (I 2 = 81.6% and 91.6%, respectively; P < .001). CE MRI (18 studies) had higher sensitivity than ncDWI (95.1% [95% CI: 92.9, 96.7] vs 88.9% [95% CI: 82.4, 93.1], P = .004) at similar specificity (82.2% [95% CI: 75.0, 87.7] vs 82.0% [95% CI: 74.8, 87.5], P = .97). Compared with ncDWI, mammography (five studies) showed no evidence of a statistical difference for sensitivity (80.3% [95% CI: 56.3, 93.3] vs 56.7%; [95% CI: 41.9, 70.4], respectively; P = .09) or specificity (89.9% [95% CI: 85.5, 93.1] vs 90% [95% CI: 61.3, 98.1], respectively; P = .62), but ncDWI had a higher area under the summary receiver operating characteristic curve (0.93 [95% CI: 0.91, 0.95] vs 0.78 [95% CI: 0.74, 0.81], P < .001). Conclusion A direct comparison with CE MRI showed a modestly lower sensitivity at similar specificity for ncDWI, and higher diagnostic performance indexes for ncDWI than standard mammography. Heterogeneity was high, thus these results must be interpreted with caution. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Kataoka and Iima in this issue.

Deep learning with diffusion MRI as in vivo microscope reveals sex-related differences in human white matter microstructure.

Biological sex is a crucial variable in neuroscience studies where sex differences have been documented across cognitive functions and neuropsychiatric disorders. While gross statistical differences have been previously documented in macroscopic brain structure such as cortical thickness or region size, less is understood about sex-related cellular-level microstructural differences which could provide insight into brain health and disease. Studying these microstructural differences between men and women paves the way for understanding brain disorders and diseases that manifest differently in different sexes. Diffusion MRI is an important in vivo, non-invasive methodology that provides a window into brain tissue microstructure. Our study develops multiple end-to-end classification models that accurately estimates the sex of a subject using volumetric diffusion MRI data and uses these models to identify white matter regions that differ the most between men and women. 471 male and 560 female healthy subjects (age range, 22-37 years) from the Human Connectome Project are included. Fractional anisotropy, mean diffusivity and mean kurtosis are used to capture brain tissue microstructure characteristics. Diffusion parametric maps are registered to a standard template to reduce bias that can arise from macroscopic anatomical differences like brain size and contour. This study employ three major model architectures: 2D convolutional neural networks, 3D convolutional neural networks and Vision Transformer (with self-supervised pretraining). Our results show that all 3 models achieve high sex classification performance (test AUC 0.92-0.98) across all diffusion metrics indicating definitive differences in white matter tissue microstructure between males and females. We further use complementary model architectures to inform about the pattern of detected microstructural differences and the influence of short-range versus long-range interactions. Occlusion analysis together with Wilcoxon signed-rank test is used to determine which white matter regions contribute most to sex classification. The results indicate that sex-related differences manifest in both local features as well as global features / longer-distance interactions of tissue microstructure. Our highly consistent findings across models provides new insight supporting differences between male and female brain cellular-level tissue organization particularly in the central white matter.

Reduced cerebrospinal fluid motion in patients with Parkinson's disease revealed by magnetic resonance imaging with low b-value diffusion weighted imaging.

BACKGROUND: Parkinson's disease is characterized by dopamine-responsive symptoms as well as aggregation of α-synuclein protofibrils. New diagnostic methods assess α-synuclein aggregation characteristics from cerebrospinal fluid (CSF) and recent pathophysiologic mechanisms suggest that CSF circulation disruptions may precipitate α-synuclein retention. Here, diffusion-weighted MRI with low-to-intermediate diffusion-weightings was applied to test the hypothesis that CSF motion is reduced in Parkinson's disease relative to healthy participants. METHODS: Multi-shell diffusion weighted MRI (spatial resolution = 1.8 × 1.8 × 4.0 mm) with low-to-intermediate diffusion weightings (b-values = 0, 50, 100, 200, 300, 700, and 1000 s/mm2) was applied over the approximate kinetic range of suprasellar cistern fluid motion at 3 Tesla in Parkinson's disease (n = 27; age = 66 ± 6.7 years) and non-Parkinson's control (n = 32; age = 68 ± 8.9 years) participants. Wilcoxon rank-sum tests were applied to test the primary hypothesis that the noise floor-corrected decay rate of CSF signal as a function of b-value, which reflects increasing fluid motion, is reduced within the suprasellar cistern of persons with versus without Parkinson's disease and inversely relates to choroid plexus activity assessed from perfusion-weighted MRI (significance-criteria: p < 0.05). RESULTS: Consistent with the primary hypothesis, CSF decay rates were higher in healthy (D = 0.00673 ± 0.00213 mm2/s) relative to Parkinson's disease (D = 0.00517 ± 0.00110 mm2/s) participants. This finding was preserved after controlling for age and sex and was observed in the posterior region of the suprasellar cistern (p < 0.001). An inverse correlation between choroid plexus perfusion and decay rate in the voxels within the suprasellar cistern (Spearman's-r=-0.312; p = 0.019) was observed. CONCLUSIONS: Multi-shell diffusion MRI was applied to identify reduced CSF motion at the level of the suprasellar cistern in adults with versus without Parkinson's disease; the strengths and limitations of this methodology are discussed in the context of the growing literature on CSF flow.

In vivo disentanglement of diffusion frequency-dependence, tensor shape, and relaxation using multidimensional MRI.

Diffusion MRI with free gradient waveforms, combined with simultaneous relaxation encoding, referred to as multidimensional MRI (MD-MRI), offers microstructural specificity in complex biological tissue. This approach delivers intravoxel information about the microstructure, local chemical composition, and importantly, how these properties are coupled within heterogeneous tissue containing multiple microenvironments. Recent theoretical advances incorporated diffusion time dependency and integrated MD-MRI with concepts from oscillating gradients. This framework probes the diffusion frequency, ω $$ \omega $$ , in addition to the diffusion tensor, D $$ \mathbf{D} $$ , and relaxation, R 1 $$ {R}_1 $$ , R 2 $$ {R}_2 $$ , correlations. A D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ clinical imaging protocol was then introduced, with limited brain coverage and 3 mm3 voxel size, which hinder brain segmentation and future cohort studies. In this study, we introduce an efficient, sparse in vivo MD-MRI acquisition protocol providing whole brain coverage at 2 mm3 voxel size. We demonstrate its feasibility and robustness using a well-defined phantom and repeated scans of five healthy individuals. Additionally, we test different denoising strategies to address the sparse nature of this protocol, and show that efficient MD-MRI encoding design demands a nuanced denoising approach. The MD-MRI framework provides rich information that allows resolving the diffusion frequency dependence into intravoxel components based on their D ω - R 1 - R 2 $$ \mathbf{D}\left(\omega \right)-{R}_1-{R}_2 $$ distribution, enabling the creation of microstructure-specific maps in the human brain. Our results encourage the broader adoption and use of this new imaging approach for characterizing healthy and pathological tissues.

Value of turbo spin echo-based diffusion-weighted imaging in the differential diagnosis of benign and malignant solitary pulmonary lesions.

To quantitatively assess the diagnostic efficacy of multiple parameters derived from multi-b-value diffusion-weighted imaging (DWI) using turbo spin echo (TSE)-based acquisition techniques in patients with solitary pulmonary lesions (SPLs). A total of 105 patients with SPLs underwent lung DWI using single-shot TSE-based acquisition techniques and multiple b values. The apparent diffusion coefficient (ADC), intravoxel incoherent motion (IVIM) parameters, and lesion-to-spinal cord signal intensity ratio (LSR), were analyzed to compare the benign and malignant groups using the Mann-Whitney U test and receiver operating characteristic analysis. The Dstar values observed in lung cancer were slightly lower than those observed in pulmonary benign lesions (28.164 ± 31.950 versus 32.917 ± 34.184; Z = -2.239, p = 0.025). The LSR values were significantly higher in lung cancer than in benign lesions (1.137 ± 0.581 versus 0.614 ± 0.442; Z = - 4.522, p < 0.001). Additionally, the ADC800, ADCtotal, and D values were all significantly lower in lung cancer than in the benign lesions (Z = - 5.054, -5.370, and -6.047, respectively, all p < 0.001), whereas the f values did not exhibit any statistically significant difference between the two groups. D had the highest area under the curve (AUC = 0.887), followed by ADCtotal (AUC = 0.844), ADC800 (AUC = 0.824), and LSR (AUC = 0.789). The LSR, ADC800, ADCtotal, and D values did not differ statistically significantly in diagnostic effectiveness. Lung DWI using TSE is feasible for differentiating SPLs. The LSR method, conventional DWI, and IVIM have comparable diagnostic efficacy for assessing SPLs.

Renal interstitial fibrotic assessment using non-Gaussian diffusion kurtosis imaging in a rat model of hyperuricemia.

BACKGROUND: To investigate the feasibility of Diffusion Kurtosis Imaging (DKI) in assessing renal interstitial fibrosis induced by hyperuricemia. METHODS: A hyperuricemia rat model was established, and the rats were randomly split into the hyperuricemia (HUA), allopurinol (AP), and AP + empagliflozin (AP + EM) groups (n = 19 per group). Also, the normal rats were selected as controls (CON, n = 19). DKI was performed before treatment (baseline) and on days 1, 3, 5, 7, and 9 days after treatment. The DKI indicators, including mean kurtosis (MK), fractional anisotropy (FA), and mean diffusivity (MD) of the cortex (CO), outer stripe of the outer medulla (OS), and inner stripe of the outer medulla (IS) were acquired. Additionally, hematoxylin and eosin (H&E) staining, Masson trichrome staining, and nuclear factor kappa B (NF-κB) immunostaining were used to reveal renal histopathological changes at baseline, 1, 5, and 9 days after treatment. RESULTS: The HUA, AP, and AP + EM group MKOS and MKIS values gradually increased during this study. The HUA group exhibited the highest MK value in outer medulla. Except for the CON group, all the groups showed a decreasing trend in the FA and MD values of outer medulla. The HUA group exhibited the lowest FA and MD values. The MKOS and MKIS values were positively correlated with Masson's trichrome staining results (r = 0.687, P < 0.001 and r = 0.604, P = 0.001, respectively). The MDOS and FAIS were negatively correlated with Masson's trichrome staining (r = -626, P < 0.0014 and r = -0.468, P = 0.01, respectively). CONCLUSION: DKI may be a non-invasive method for monitoring renal interstitial fibrosis induced by hyperuricemia.

Prognostic value of preoperative diffusion restriction in glioblastoma.

INTRODUCTION: Although glioblastoma (GBM) has a very poor prognosis, overall survival (OS) in treated patients shows great difference varying from few days to several months. Identifying factors explaining this difference would improve management of patient treatment. AIM: To determine the relevance of diffusion restriction in newly diagnosed treatment-naïve GBM patients. METHODS: Preoperative magnetic resonance scans of 33 patients with GBM were reviewed. Regions of interest including all the T2 hyperintense lesion were drawn on diffusion weighted B0 images and transferred to the apparent diffusion coefficient (ADC) map. For each patient, a histogram displaying the ADC values within in the regions of interest was generated. Volumetric parameters including tumor regions with restricted diffusion, parameters derived from histogram and mean ADC value of the tumor were calculated. Their relationship with OS was analyzed. RESULTS: Patients with mean ADC value < 1415x10-6 mm2/s had a significantly shorter OS (p=0.021). Among volumetric parameters, the percentage of volume within T2 lesion with a normalized ADC value <1.5 times that in white matter was significantly associated with OS (p=0.0045). Patients with a percentage>23.92% had a shorter OS. Among parameters derived from histogram, the 50th percentile showed a trend towards significance for OS (p=0.055) with patients living longer when having higher values of 50th percentile. A difference in OS was observed between patients according to ADC peak of histogram but this difference did not reach statistical significance (p=0.0959). CONCLUSION: Diffusion magnetic resonance imaging may provide useful information for predicting GBM prognosis.

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OBJECTIVES: To explore the value of functional magnetic resonance imaging (MRI) techniques, including intravoxel incoherent motion (IVIM), T1 mapping, and T2 mapping, in assessing the microstructural and perfusion changes in the kidneys of rats with intrauterine growth restriction (IUGR). METHODS: An IUGR rat model was established through a low-protein diet during pregnancy. Offspring from pregnant rats on a low-protein diet were randomly divided into an IUGR 8-week group and an IUGR 12-week group, while offspring from pregnant rats on a normal diet were divided into a normal 8-week group and a normal 12-week group (n=8 for each group). The apparent diffusion coefficient (ADC), true diffusion coefficient (Dt), pseudo-diffusion coefficient (D*), perfusion fraction (f), T1 value, and T2 value of the renal cortex and medulla were compared, along with serum creatinine and blood urea nitrogen levels among the groups. RESULTS: The Dt value in the renal medulla was higher in the IUGR 12-week group than in the IUGR 8-week group, and the D* value in the renal medulla was lower in the IUGR 12-week group than in both the normal 12-week group and the IUGR 8-week group (P<0.05). The T1 value in the renal medulla was higher than in the cortex in the IUGR 8-week group, and the T1 value in the renal medulla was higher in the IUGR 12-week group than in both the IUGR 8-week group and the normal 12-week group, with the cortical T1 value in the IUGR 12-week group also being higher than that in the normal 12-week group (P<0.05). The T2 values in the renal medulla were higher than those in the cortex across all groups (P<0.05). There were no significant differences in the T2 values of either the cortex or medulla among the groups (P>0.05). There were no significant differences in serum creatinine and blood urea nitrogen levels among the groups (P>0.05). Glomerular hyperplasia and hypertrophy without significant fibrotic changes were observed in the IUGR 8-week group, whereas glomerular atrophy, cystic stenosis, and interstitial inflammatory infiltration and fibrosis were seen in the IUGR 12-week group. CONCLUSIONS: IVIM MRI can be used to assess and dynamically observe the microstructural and perfusion damage in the kidneys of IUGR rats. MRI T1 mapping can be used to evaluate kidney damage in IUGR rats, and the combination of MRI T1 mapping and T2 mapping can further differentiate renal fibrosis in IUGR rats.

A large normative connectome for exploring the tractographic correlates of focal brain interventions.

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

Quantitative analysis of apparent diffusion coefficients to predict neurological prognosis in cardiac arrest survivors: an observational derivation and internal-external validation study.

BACKGROUND: This study aimed to validate apparent diffusion coefficient (ADC) values and thresholds to predict poor neurological outcomes in out-of-hospital cardiac arrest (OHCA) survivors by quantitatively analysing the ADC values via brain magnetic resonance imaging (MRI). METHODS: This observational study used prospectively collected data from two tertiary academic hospitals. The derivation cohort comprised 70% of the patients randomly selected from one hospital, whereas the internal validation cohort comprised the remaining 30%. The external validation cohort used the data from another hospital, and the MRI data were restricted to scans conducted at 3 T within 72-96 h after an OHCA experience. We analysed the percentage of brain volume below a specific ADC value at 50-step intervals ranging from 200 to 1200 × 10-6 mm2/s, identifying thresholds that differentiate between good and poor outcomes. Poor neurological outcomes were defined as cerebral performance categories 3-5, 6 months after experiencing an OHCA. RESULTS: A total of 448 brain MRI scans were evaluated, including a derivation cohort (n = 224) and internal/external validation cohorts (n = 96/128, respectively). The proportion of brain volume with ADC values below 450, 500, 550, 600, and 650 × 10-6 mm2/s demonstrated good to excellent performance in predicting poor neurological outcomes in the derivation group (area under the curve [AUC] 0.89-0.91), and there were no statistically significant differences in performances among the derivation, internal validation, and external validation groups (all P > 0.5). Among these, the proportion of brain volume with an ADC below 600 × 10-6 mm2/s predicted a poor outcome with a 0% false-positive rate (FPR) and 76% (95% confidence interval [CI] 68-83) sensitivity at a threshold of > 13.2% in the derivation cohort. In both the internal and external validation cohorts, when using the same threshold, a specificity of 100% corresponded to sensitivities of 71% (95% CI 58-81) and 78% (95% CI 66-87), respectively. CONCLUSIONS: In this validation study, by consistently restricting the MRI types and timing during quantitative analysis of ADC values in brain MRI, we observed high reproducibility and sensitivity at a 0% FPR. Prospective multicentre studies are necessary to validate these findings.

Structural changes in corticospinal tract profiling via multishell diffusion models and their relation to overall survival in glioblastoma.

PURPOSE: Advanced MR fiber tracking imaging reflects fiber bundle invasion by glioblastoma, particularly of the corticospinal tract (CST), which is more susceptible as the largest downstream fiber tracts. We aimed to investigate whether CST features can predict the overall survival of glioblastoma. METHODS: In this prospective secondary analysis, 40 participants (mean age, 58 years; 16 male) pathologically diagnosed with glioblastoma were enrolled. Diffusion spectrum MRI was used for CST reconstruction. Fifty morphological and diffusion indicators (DTI, DKI, NODDI, MAP and Q-space) were used to characterize the CST. Optimal parameters capturing fiber bundle damage were obtained through various grouping methods. Eventually, the correlation with overall survival was determined by the hazard ratios (HRs) from various Cox proportional hazard model combinations. RESULTS: Only intracellular volume fraction (ICVF) and non-Gaussianity (NG) values on the affected tumor level were significant in all four groups or stratified comparisons (all P < .05). During the median follow-up 698 days, only the ICVF on the affected tumor level was independently associated with overall survival, even after adjusting for all classic prognostic factors (HR [95 % CI]: 0.611 [0.403, 0.927], P = .021). Moreover, stratification by the ICVF on the affected tumor level successfully predicted risk (P < .01) and improved the C-index of the multivariate model (from 0.695 to 0.736). CONCLUSIONS: This study demonstrates a relationship between NODDI-derived CST features, ICVF on the affected tumor level, and overall survival in glioblastoma. Independent of classical prognostic factors for glioblastoma, a lower ICVF on the affected tumor level might predict a lower overall survival.

High-fidelity intravoxel incoherent motion parameter mapping using locally low-rank and subspace modeling.

PURPOSE: Intravoxel incoherent motion (IVIM) is a quantitative magnetic resonance imaging (MRI) method used to quantify perfusion properties of tissue non-invasively without contrast. However, clinical applications are limited by unreliable parameter estimates, particularly for the perfusion fraction (f) and pseudodiffusion coefficient (D*). This study aims to develop a high-fidelity reconstruction for reliable estimation of IVIM parameters. The proposed method is versatile and amenable to various acquisition schemes and fitting methods. METHODS: To address current challenges with IVIM, we adapted several advanced reconstruction techniques. We used a low-rank approximation of IVIM images and temporal subspace modeling to constrain the magnetization dynamics of the bi-exponential diffusion signal decay. In addition, motion-induced phase variations were corrected between diffusion directions and b-values, facilitating the use of high SNR real-valued diffusion data. The proposed method was evaluated in simulations and in vivo brain acquisitions in six healthy subjects and six individuals with a history of SARS-CoV-2 infection and compared with the conventionally reconstructed magnitude data. Following reconstruction, IVIM parameters were estimated voxel-wise. RESULTS: Our proposed method reduced noise contamination in simulations, resulting in a 60%, 58.9%, and 83.9% reduction in the NRMSE for D, f, and D*, respectively, compared to the conventional reconstruction. In vivo, anisotropic properties of D, f, and D* were preserved with the proposed method, highlighting microvascular differences in gray matter between individuals with a history of COVID-19 and those without (p = 0.0210), which wasn't observed with the conventional reconstruction. CONCLUSION: The proposed method yielded a more reliable estimation of IVIM parameters with less noise than the conventional reconstruction. Further, the proposed method preserved anisotropic properties of IVIM parameter estimates and demonstrated differences in microvascular perfusion in COVID-affected subjects, which weren't observed with conventional reconstruction methods.

Influence of diffusion weighted imaging and contrast enhanced T1 sequences on the diagnostic accuracy of magnetic resonance enterography for Crohn's disease.

OBJECTIVES: To evaluate the additional diagnostic benefit of diffusion weighted imaging (DWI) and contrast enhanced (CE) images during MR enterography (MRE) of Crohn's disease. METHODS: Datasets from 73 patients (mean age 32; 40 male) (28 new-diagnosis, 45 relapsed) were read independently by two radiologists selected from a pool of 13. Radiologists interpreted datasets using three sequential sequence blocks: (1) T2 weighted and steady state free precession gradient echo (SSFP) images alone (T2^); (2) T2 weighted and SSFP images with DWI (T2 + DWI^) and; (3) T2 weighted images, SSFP, DWI and post-contrast enhanced (CE) T1 images (T2 + DWI + CE^), documenting presence, location, and activity of small bowel disease. For each sequence block, sensitivity and specificity (readers combined) was calculated against an outcome-based construct reference standard. RESULTS: 59/73 patients had small bowel disease. Per-patient sensitivity for disease detection was essentially identical (80 % [95 % CI 72, 86], 81 % [73,87], and 79 % [71,86] for T2^, T2 + DWI^and T2 + DWI + CE^respectively). Specificity was identical (82 % [64 to 92]). Per patient sensitivity for disease extent was 56 % (47,65), 56 % (47,65) and 52 % (43 to 61) respectively, and specificity was 82 % (64 to 92) for all blocks. Sensitivity for active disease was 97 % (90,99), 97 % (90,99) and 98 % (92,99), and specificity was also comparable between all sequence combination reads. Results were consistent across segments and newly diagnosed/relapse patients. CONCLUSION: There is no additional diagnostic benefit of adding either DWI or CE to T2 FSE and SSFP sequences for evaluating small bowel Crohn's disease, suggesting MRE protocols can be simplified safely.

The diagnostic value of abbreviated MRI protocol in the surveillance of Branch-Duct intraductal papillary mucinous neoplasm.

PURPOSE: To assess the diagnostic value of abbreviated protocol (AP) MRI to detect the degeneration signs in branch-duct intraductal papillary mucinous neoplasms (BD-IPMNs) in patients undergoing a routine MRI follow-up. METHODS: This dual-center retrospective study include patients with BD-IPMN diagnosed on initial comprehensive protocol (CP) MRI who underwent routine MRI follow-up. CP included axial and coronal T2-weighted images (T2WI), axial T1-weighted images (T1WI) before and after contrast administration, 3D MR cholangiopancreatography (MRCP) and diffusion-weighted images (DWI). Two APs, eliminating dynamic sequences ± DWI, were extracted from CP. Two radiologists evaluated the APs separately for IPMN degeneration signs according to Fukuoka criteria and compared the results to the follow-up CP. In patients who underwent EUS, imaging findings were correlated with pathological results. Per-patient and per-lesion sensitivity, specificity, PPV, NPV, and accuracy of APs were calculated. Additionally, the acquisition time for different protocols was calculated. RESULTS: One hundred-fourteen patients (56.1 % women, median age: 71 years) with 256 lesions were included. Degeneration signs were observed in 24.6 % and 12.1 % per-patient and per-lesion, respectively. Regarding APs, the per patient sensitivity, specificity, PPV, NPV, and accuracy in the detection of the degeneration signs were 100 %, 93.5 %, 83.3 %, 100 %, and 95.1 %, respectively. No additional role for DWI was detected. AP without DWI economized nearly half of CP acquisition time (388 versus 663 s, respectively). CONCLUSION: AP can confidently replace CP for BD-IPMN follow-up with high sensitivity and PPV while offering benefits such as patient comfort, improved MRI accessibility, and reduced dedicated time for image analysis. DWI necessitates special consideration. CLINICAL RELEVANCE STATEMENT: Our data suggest that APs safely detect all degeneration signs of IPMN. While there is an overestimation of mural nodules due to the lack of contrast injection, this occurs in a negligible number of patients.

A genetic optimisation and iterative reconstruction framework for sparse multi-dimensional diffusion-relaxation correlation MRI.

Multi-dimensional diffusion-relaxation correlation (DRC) magnetic resonance imaging (MRI) techniques have recently been developed to investigate tissue microstructures. Sub-voxel tissue heterogeneity is resolved from the local correlation distributions of relaxation time and molecular diffusivity. However, the implementation of these techniques considerably increases the total acquisition time, and simply reducing the scan time may be at the expense of detailed structural resolution. To overcome these limitations, an optimised framework was proposed for acquiring microstructural maps of the human brain on a clinically feasible timescale. First, the acquisition parameters of the multi-dimensional DRC MRI method were sparsely optimised using a genetic algorithm with a fitness function according to the spectral resolution of the correlation map, hardware requirements, and total scan time. Next, the acquired DRC MRI data were processed using a proposed numerical algorithm based on the dynamic inverse Laplace transform (ILT). Prior knowledge from one-dimensional data was then utilised in the iterative procedure to improve the spectral resolution. Finally, the proposed framework was validated using Monte Carlo simulations and experimental data acquired from healthy participants on an MRI scanner. The results demonstrated that the suggested approach is feasible for offering high-resolution DRC maps that correspond to distinct microstructures with a limited amount of optimised acquisition data from two-dimensional DRC sampling space. By significantly reducing scan time while retaining structural resolution, this approach may enable multi-dimensional DRC MRI to be more widely used for quantitative evaluation in biological and medical settings.