Corrigendum: Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics.

[This corrects the article DOI: 10.3389/fnins.2024.1356241.].

Advancing gastrointestinal stromal tumor management: The role of imagomics features in precision risk assessment.

BACKGROUND: Gastrointestinal stromal tumors (GISTs) vary widely in prognosis, and traditional pathological assessments often lack precision in risk stratification. Advanced imaging techniques, especially magnetic resonance imaging (MRI), offer potential improvements. This study investigates how MRI imagomics can enhance risk assessment and support personalized treatment for GIST patients. AIM: To assess the effectiveness of MRI imagomics in improving GIST risk stratification, addressing the limitations of traditional pathological assessments. METHODS: Analyzed clinical and MRI data from 132 GIST patients, categorizing them by tumor specifics and dividing into risk groups. Employed dimension reduction for optimal imagomics feature selection from diffusion-weighted imaging (DWI), T1-weighted imaging (T1WI), and contrast enhanced T1WI with fat saturation (CE-T1WI) fat suppress (fs) sequences. RESULTS: Age, lesion diameter, and mitotic figures significantly correlated with GIST risk, with DWI sequence features like sphericity and regional entropy showing high predictive accuracy. The combined T1WI and CE-T1WI fs model had the best predictive efficacy. In the test group, the DWI sequence model demonstrated an area under the curve (AUC) value of 0.960 with a sensitivity of 80.0% and a specificity of 100.0%. On the other hand, the combined performance of the T1WI and CE-T1WI fs models in the test group was the most robust, exhibiting an AUC value of 0.834, a sensitivity of 70.4%, and a specificity of 85.2%. CONCLUSION: MRI imagomics, particularly DWI and combined T1WI/CE-T1WI fs models, significantly enhance GIST risk stratification, supporting precise preoperative patient assessment and personalized treatment plans. The clinical implications are profound, enabling more accurate surgical strategy formulation and optimized treatment selection, thereby improving patient outcomes. Future research should focus on multicenter studies to validate these findings, integrate advanced imaging technologies like PET/MRI, and incorporate genetic factors to achieve a more comprehensive risk assessment.

A controlled study of MR DWI, FS-PDW, and CE-T1W imaging for the evaluation of the internal opening of anal fistulas.

BACKGROUND: Anal fistula (AF) is an abnormal tunnel under the skin connecting the anal canal in the colon to the skin of buttocks. Fat-suppressed (FS) proton density-weighted (PDW) imaging is mainly used for the diagnosis of diseases involving bones and joints. Until now, its value in the diagnosis of anal fistula has been rarely reported. PURPOSE: To compare three magnetic resonance imaging (MRI) sequences - diffusion-weighted imaging (DWI), FS-PDW), and contrast-enhanced (CE) T1-weighted (T1W) imaging - for the diagnostic value of the internal opening of AF. MATERIAL AND METHODS: MRI scans of 132 patients suspected of having AF between December 2021 and April 2023 were retrospectively analyzed. In total, 65 patients who underwent preoperative MRI and were treated surgically were included. The lesion conspicuity and accuracy for featuring AF were calculated by evaluating the three imaging datasets DWI, FS-PDW, and CE-T1W imaging, with surgical findings serving as the reference standard for the presence of fistulas. The statistical analysis included the application of the chi-square test and Kruskal-Wallis test. RESULTS: In 65 patients with AF, 87 internal openings of AF were confirmed. In terms of the diagnostic accuracy of the internal openings, both FS-PDW and CE-T1W imaging sequences were significantly better than DWI sequences, and the difference was statistically significant (P < 0.05). CONCLUSION: The FS-PDW imaging sequence showed comparable diagnostic performance of the internal opening of AF to CE-T1W imaging, which can provide an important diagnostic basis for clinical procedures.

Enhancement of the lymphatic system following intravenous administration of ferumoxytol.

BACKGROUND: Lymphatic imaging is becoming increasingly important in the management of patients with congenital heart disease. However, the influence of the intravenous contrast agent ferumoxytol on lymphatic imaging is not well understood. OBJECTIVE: To evaluate the impact of intravenous ferumoxytol on T1-weighted and T2-weighted lymphatic imaging in patients with congenital heart disease. MATERIALS AND METHODS: We included consecutive patients receiving ferumoxytol-enhanced 3D angiography for congenital heart disease evaluation. The visibility of the thoracic duct was reviewed on the T1-weighted 3D inversion recovery balanced-steady-state free precession (SSFP) with respiratory navigator gating sequence which is routinely used for angiography and the heavily T2-weighted turbo spin echo sequence which is employed for lymphatic imaging. Data on demographics and time interval between contrast administration and imaging were collected. Statistical analyses were performed using t-tests for continuous variables and chi-squared tests for categorical variables. RESULTS: One hundred nineteen consecutive patients with a mean age of 12.46 years±7.7 years were included. Of these, 45 cases underwent both T1-weighted and T2-weighted imaging; the other 74 underwent only T1-weighted imaging. Of the 45 patients, 20 had thoracic duct enhancement on T1-weighted imaging; among the 26 sedated, only 2 showed enhancement, while 18 of 19 non-sedated patients showed enhancement (P<0.001), indicating a strong association between sedation and reduced thoracic duct visibility. If T2-weighted imaging was performed after contrast administration, the thoracic duct was not visible on those images. For all 45 cases of visible thoracic duct in the entire cohort, the time from contrast administration to imaging ranged from 8 min up to 75 min. CONCLUSION: The enhancement of the thoracic lymphatic duct on T1-weighted imaging, coupled with degradation observed on T2-weighted imaging, suggests that intravenously administered ferumoxytol rapidly enters the lymphatic fluid. To prevent T2 shortening from degrading the imaging results, T2-weighted imaging for lymphatic evaluation should be performed prior to the administration of ferumoxytol. Sedation and, by inference, fasting may influence this property and warrant further investigation in future studies.

Comparative effectiveness of two abbreviated rectal MRI protocols in assessing tumor response to neoadjuvant chemoradiotherapy in patients with rectal cancer.

The present study aimed to compare the effectiveness of two abbreviated magnetic resonance imaging (MRI) protocols in assessing the response to neoadjuvant chemoradiotherapy (CRT) in patients with rectal cancer. Data from the examinations of 62 patients with rectal cancer who underwent neoadjuvant CRT and standard contrast-enhanced rectal MRI were retrospectively evaluated. Standard contrast-enhanced T2-weighted imaging (T2-WI), post-contrast T1-weighted imaging (T1-WI) and diffusion-weighted imaging (DWI) MRI, as well as two abbreviated protocols derived from these images, namely protocol AB1 (T2-WI and DWI) and protocol AB2 (post-contrast fat-suppressed (FS) T1-WI and DWI), were assessed. Measurements of lesion length and width, lymph node short-axis length, tumor staging, circumferential resection margin (CRM), presence of extramural venous invasion (EMVI), luminal mucin accumulation (MAIN), mucinous response, mesorectal fascia (MRF) involvement, and MRI-based tumor regression grade (mrTRG) were obtained. The reliability and compatibility of the AB1 and AB2 protocols in the evaluation of tumor response were analyzed. The imaging performed according to the AB1 and AB2 protocols revealed significant decreases in lesion length, width and lymph node size after CRT. These protocols also showed reductions in lymph node positivity, CRM, MRF, EMVI.Furthermore, both protocols were found to be reliable in determining lesion length and width. Additionally, compliance was observed between the protocols in determining lymph node size and positivity, CRM involvement, and EMVI after CRT. In conclusion, the use of abbreviated MRI protocols, specifically T2-WI with DWI sequences or post-contrast FS T1-WI with DWI sequences, is effective for evaluating tumor response in patients with rectal cancer following neoadjuvant CRT. The AB protocols examined in this study yielded similar results in terms of lesion length and width, lymph node positivity, CRM involvement, EMVI, MAIN, and MRF involvement.

T1- and T2-weighted MRI signal and histology findings in suboptimally fixed human brains.

Neuroscientific research that requires brain tissue depends on brain banks that provide very small tissue samples fixed by immersion in neutral-buffered formalin (NBF), while anatomy laboratories could provide full brain specimens. However, these brains are generally fixed by perfusion of the full body with solutions other than NBF generally used by brain banks, such as an alcohol-formaldehyde solution (AFS) that is typically used for dissection and teaching. Therefore, fixation quality of these brains needs to be assessed to determine their usefulness in post-mortem investigations through magnetic resonance imaging (MRI) and histology, two common neuroimaging modalities. Here, we report the characteristics of five brains fixed by full body perfusion of an AFS from our Anatomy Laboratory suspected of being poorly fixed, given the altered signal seen on T1w MRI scans in situ. We describe 1- the characteristics of the donors; 2- the fixation procedures applied for each case; 3- the tissue contrast characteristics of the T1w and T2w images; 4- the macroscopic tissue quality after extraction of the brains; 5- the macroscopic arterial characteristics and presence or absence of blood clots; and 6- four histological stains of the areas that we suspected were poorly fixed. We conclude that multiple factors can affect the fixation quality of the brain. Nevertheless, cases in which brain fixation is suboptimal, consequently altering the T1w signal, still have T2w of adequate gray-matter to white-matter contrast and may also be used for histology stains with sufficient quality.

Training robust T1-weighted magnetic resonance imaging liver segmentation models using ensembles of datasets with different contrast protocols and liver disease etiologies.

Image segmentation of the liver is an important step in treatment planning for liver cancer. However, manual segmentation at a large scale is not practical, leading to increasing reliance on deep learning models to automatically segment the liver. This manuscript develops a generalizable deep learning model to segment the liver on T1-weighted MR images. In particular, three distinct deep learning architectures (nnUNet, PocketNet, Swin UNETR) were considered using data gathered from six geographically different institutions. A total of 819 T1-weighted MR images were gathered from both public and internal sources. Our experiments compared each architecture's testing performance when trained both intra-institutionally and inter-institutionally. Models trained using nnUNet and its PocketNet variant achieved mean Dice-Sorensen similarity coefficients>0.9 on both intra- and inter-institutional test set data. The performance of these models suggests that nnUNet and PocketNet liver segmentation models trained on a large and diverse collection of T1-weighted MR images would on average achieve good intra-institutional segmentation performance.

Systemic inflammatory markers and volume of enhancing tissue on post-contrast T1w MRI images in differentiating true tumor progression from pseudoprogression in high-grade glioma.

Background: High-grade glioma (HGG) patients post-radiotherapy often face challenges distinguishing true tumor progression (TTP) from pseudoprogression (PsP). This study evaluates the effectiveness of systemic inflammatory markers and volume of enhancing tissue on post-contrast T1 weighted (T1WCE) MRI images for this differentiation within the first six months after treatment. Material and Methods: We conducted a retrospective analysis on a cohort of HGG patients from 2015 to 2021, categorized per WHO 2016 and 2021 criteria. We analyzed treatment responses using modified RANO criteria and conducted volumetry on T1WCE and T2W/FLAIR images.Blood parameters assessed included neutrophil/lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI). We employed Chi-square, Fisher's exact test, and Mann-Whitney U test for statistical analyses, using log-transformed predictors due to multicollinearity. A Cox regression analysis assessed the impact of PsP- and TTP-related factors on overall survival (OS). Results: The cohort consisted of 39 patients, where 16 exhibited PsP and 23 showed TTP. Univariate analysis revealed significantly higher NLR and SII in the TTP group [NLR: 4.1 vs 7.3, p = 0.002; SII 546.5 vs 890.5p = 0.009]. T1WCE volume distinctly differentiated PsP from TTP [2.2 vs 11.7, p < 0.001]. In multivariate regression, significant predictors included NLR and T1WCE volume in the "NLR Model," and T1WCE volume and SII in the "SII Model." The study also found a significantly lower OS rate in TTP patients compared to those with PsP [HR 3.97, CI 1.59 to 9.93, p = 0.003]. Conclusion: Elevated both, SII and NLR, and increased T1WCE volume were effective in differentiating TTP from PsP in HGG patients post-radiotherapy. These results suggest the potential utility of incorporating these markers into clinical practice, though further research is necessary to confirm these findings in larger patient cohorts.

Occipital condyle syndrome due to small-cell lung carcinoma: A case report.

Skull base metastases, including those from small-cell lung carcinoma (SCLC), can present with various syndromes depending on the site of involvement, such as orbital syndrome, parasellar syndrome, middle fossa syndrome, jugular foramen syndrome, and occipital condyle syndrome (OCS). One such example is OCS, which consists of unilateral occipital headache accompanied with ipsilateral hypoglossal palsy. This case report describes a 51-year-old man initially diagnosed with OCS, which led to the discovery of systemic bone metastases from SCLC. Magnetic resonance imaging showed lesions in the occipital condyle and hypoglossal canal, while positron emission tomography-computed tomography identified a lung mass and widespread metastases. SCLC is highly aggressive and metastatic, with the bone being a common site of spread. In this case, the OCS preceded the diagnosis of the underlying malignancy. Prompt diagnosis and treatment are crucial, as patients with OCS often have advanced disease. This case highlights the importance of considering SCLC as a potential etiology for OCS, given the propensity for bone metastases. Early recognition and evaluation of OCS is essential to initiate appropriate management.

Radiomics based on diffusion tensor imaging and 3D T1-weighted MRI for essential tremor diagnosis.

Background: Due to the absence of biomarkers, the misdiagnosis of essential tremor (ET) with other tremor diseases and enhanced physiologic tremor is very common in practice. Combined radiomics based on diffusion tensor imaging (DTI) and three-dimensional T1-weighted imaging (3D-T1) with machine learning (ML) give a most promising way to identify essential tremor (ET) at the individual level and further reveal the potential imaging biomarkers. Methods: Radiomics features were extracted from 3D-T1 and DTI in 103 ET patients and 103 age-and sex-matched healthy controls (HCs). After data dimensionality reduction and feature selection, five classifiers, including the support vector machine (SVM), random forest (RF), logistic regression (LR), extreme gradient boosting (XGBoost) and multi-layer perceptron (MLP), were adopted to discriminate ET from HCs. The mean values of the area under the curve (mAUC) and accuracy were used to assess the model's performance. Furthermore, a correlation analysis was conducted between the most discriminative features and clinical tremor characteristics. Results: All classifiers achieved good classification performance (with mAUC at 0.987, 0.984, 0.984, 0.988 and 0.981 in the test set, respectively). The most powerful discriminative features mainly located in the cerebella-thalamo-cortical (CTC) and visual pathway. Furthermore, correlation analysis revealed that some radiomics features were significantly related to the clinical tremor characteristics in ET patients. Conclusion: These results demonstrated that combining radiomics with ML algorithms could not only achieve high classification accuracy for identifying ET but also help us to reveal the potential brain microstructure pathogenesis in ET patients.

Psychological resilience is positively correlated with Habenula volume.

BACKGROUND: Psychological resilience is defined as the process and outcome of individuals' successful adaptation to challenging life experiences. The Habenula (Hb) is known to be involved in the stress response; however, the relationship between Hb volume and resilience in humans remains unclear. This study investigated the correlation among resilience, Hb volume, and depressive tendencies in adults. METHODS: Hb volumes were assessed using deep learning techniques applied to 110 healthy participants. Resilience and depression were evaluated using the Connor-Davidson Resilience Scale and Beck Depression Inventory-II, respectively. We examined the relationship between Hb volume and resilience and assessed the mediating effects of resilience on the relationship between Hb volume and depressive tendencies. RESULTS: Correlation analysis revealed a positive correlation between resilience and Hb volume (partial r = 0.176, p = 0.001), which was more pronounced in women (partial r = 0.353, p = 0.003). Hb volumes on the left and right sides exhibited significant lateralization (LI = 0.031, 95 % CI = [0.016, 0.046]). Despite Hb asymmetry, lateralization was not significantly associated with resilience. The mediation analysis shows significant indirect effect of resilience on the relationship between Hb volume and depressive tendencies (ß = -0.093, 95%CI = [-0.189, -0.019]). CONCLUSION: This study found that populations with lower resilience have smaller Hb volume. Previous research has shown that Hb volume decreased with the increasing severity of depression symptoms in patients. Our findings support this view and extend it to a population that has not been clinically diagnosed with depression. Additionally, we found that psychological resilience can be predicted by Hb volume and may serve as a mediating factor indirectly affecting depressive tendencies, even in healthy individuals. LIMITATIONS: Due to its cross-sectional design, this study was unable to analyze dynamic changes in Hb volume during the process of resilience adaptation.

Deep learning-based quantification of brain atrophy using 2D T1-weighted MRI for Alzheimer's disease classification.

Background: Determining brain atrophy is crucial for the diagnosis of neurodegenerative diseases. Despite detailed brain atrophy assessments using three-dimensional (3D) T1-weighted magnetic resonance imaging, their practical utility is limited by cost and time. This study introduces deep learning algorithms for quantifying brain atrophy using a more accessible two-dimensional (2D) T1, aiming to achieve cost-effective differentiation of dementia of the Alzheimer's type (DAT) from cognitively unimpaired (CU), while maintaining or exceeding the performance obtained with T1-3D individuals and to accurately predict AD-specific atrophy similarity and atrophic changes [W-scores and Brain Age Index (BAI)]. Methods: Involving 924 participants (478 CU and 446 DAT), our deep learning models were trained on cerebrospinal fluid (CSF) volumes from 2D T1 images and compared with 3D T1 images. The performance of the models in differentiating DAT from CU was assessed using receiver operating characteristic analysis. Pearson's correlation analyses were used to evaluate the relations between 3D T1 and 2D T1 measurements of cortical thickness and CSF volumes, AD-specific atrophy similarity, W-scores, and BAIs. Results: Our deep learning models demonstrated strong correlations between 2D and 3D T1-derived CSF volumes, with correlation coefficients r ranging from 0.805 to 0.971. The algorithms based on 2D T1 accurately distinguished DAT from CU with high accuracy (area under the curve values of 0.873), which were comparable to those of algorithms based on 3D T1. Algorithms based on 2D T1 image-derived CSF volumes showed high correlations in AD-specific atrophy similarity (r = 0.915), W-scores for brain atrophy (0.732 ≤ r ≤ 0.976), and BAIs (r = 0.821) compared with those based on 3D T1 images. Conclusion: Deep learning-based analysis of 2D T1 images is a feasible and accurate alternative for assessing brain atrophy, offering diagnostic precision comparable to that of 3D T1 imaging. This approach offers the advantage of the availability of T1-2D imaging, as well as reduced time and cost, while maintaining diagnostic precision comparable to T1-3D.

A Characteristic Magnetic Resonance Imaging Finding to Identify Morton Neuroma: The Slug Sign.

Background: Morton neuroma is a common cause of forefoot pain and sensory disturbances, but it is difficult to identify on magnetic resonance imaging (MRI). The aim of this study was to verify the usefulness of a characteristic MRI finding (slug sign) for identifying Morton neuroma and to clarify the relationship between excised neuroma characteristics and preoperative MRI findings. Methods: Twenty-two web spaces were retrospectively assessed from the second and third intermetatarsal spaces of 11 feet of 10 patients (7 women and 3 men, aged average 59.5 years) who underwent surgical excision of Morton neuroma between 2017 and 2022. Asymptomatic web spaces were used as control. Neuromas with 2 branches of the plantar digital nerves on axial T1-weighted MRI (MRI-T1WI) were considered the slug sign. We investigated the preoperative presence of the slug sign in Morton neuroma and asymptomatic control web spaces. We also investigated the relationship between the maximum transverse diameter of the excised specimen and that estimated on coronal MRI-T1WI. Results: A total of 15 Morton neuromas were excised and assessed. The slug signs were present in 10 intermetatarsal spaces in 15 web spaces with Morton neuroma whereas the sign was found in 1 intermetatarsal space in 7 asymptomatic web spaces. The sensitivity and specificity for the slug sign to diagnose Morton neuroma was 66.7% and 85.7%, respectively. The positive and negative predictive values were 90.9% and 54.5%, respectively. The mean maximum transverse diameter of excised neuromas was 4.7 mm. The mean maximum transverse diameter of neuromas on coronal MRI-T1WI was 3.4 mm. A significant positive correlation was found between the maximum transverse diameters of excised specimens and diameters estimated on coronal MRI-T1WI (r = 0.799, P < .001). Conclusion: The slug sign may be a useful indicator of Morton neuroma on MRI to confirm nerve involvement after bifurcation. Level of Evidence: Level IV, retrospective series.

Voxel-Based Morphometry of Progressive Supranuclear Palsy Using a 3D Fast Low-angle Shot Localizer Image: A Comparison with Magnetization-Prepared Rapid Gradient Echo.

PURPOSE: Voxel-based morphometry (VBM) is widely used to investigate white matter (WM) atrophy in patients with progressive supranuclear palsy (PSP). In contrast to high-resolution 3D T1-weighted imaging such as magnetization-prepared rapid acquisition with gradient echo (MPRAGE) sequences, the utility of other 3D sequences has not been sufficiently evaluated. This study aimed to assess the feasibility of using a 3D fast low-angle shot sequence captured as a localizer image (L3DFLASH) for VBM analysis of WM atrophy patterns in patients with PSP. METHODS: This retrospective study included 12 patients with pathologically or clinically confirmed PSP, and 18 age- and sex-matched healthy controls scanned with both L3DFLASH and MPRAGE sequences. Image processing was conducted with the Computational Anatomy Toolbox 12 in statistical parametric mapping 12. In addition to the atrophic WM pattern of PSP on VBM, we assessed the WM volume agreement between the two sequences using simple linear regression and Bland-Altman plots. RESULTS: Despite the slightly larger clusters on MPRAGE, VBM using both sequences showed similar characteristics of PSP-related WM atrophy, including in the midbrain, pons, thalamus, and precentral gyrus. In contrast, VBM showed gray matter (GM) atrophy of the precuneus and right superior parietal lobule exclusively on L3DFLASH. Unlike the measured values of total intracranial volume, GM, and cerebrospinal fluid on MPRAGE, the value of WM was larger on L3DFLASH. In contrast to the total intracranial volume, brainstem, and frontal and occipital lobes, the correlation with WM volume in other regions was relatively low. However, the Bland-Altman plots demonstrated strong agreement, with over 90% of the values falling within the agreement limits. CONCLUSION: Both MPRAGE and L3DFLASH are useful for detecting PSP-related WM atrophy using VBM.

Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.

A three-dimensional convolutional neural network model was developed to classify the severity of chronic kidney disease (CKD) using magnetic resonance imaging (MRI) Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) imaging. Seventy-three patients with severe renal dysfunction (estimated glomerular filtration rate [eGFR] < 30 mL/min/1.73 m2, CKD stage G4-5); 172 with moderate renal dysfunction (30 ≤ eGFR < 60 mL/min/1.73 m2, CKD stage G3a/b); and 76 with mild renal dysfunction (eGFR ≥ 60 mL/min/1.73 m2, CKD stage G1-2) participated in this study. The model was applied to the right, left, and both kidneys, as well as to each imaging method (T1-weighted IP/OP/WO images). The best performance was obtained when using bilateral kidneys and IP images, with an accuracy of 0.862 ± 0.036. The overall accuracy was better for the bilateral kidney models than for the unilateral kidney models. Our deep learning approach using kidney MRI can be applied to classify patients with CKD based on the severity of kidney disease.

Employing antagonistic C-X-C motif chemokine receptor 4 antagonistic peptide functionalized NaGdF4 nanodots for magnetic resonance imaging-guided biotherapy of breast cancer.

C-X-C motif chemokine receptor 4 (CXCR4) is a promising therapeutic target of breast cancer because it is overexpressed on cell surface of all molecular subtypes of breast cancer including triplenegative breast cancer (TNBC). Herein, CXCR4 antagonistic peptide-NaGdF4 nanodot conjugates (termed as anti-CXCR4-NaGdF4 NDs) have been constructed for magnetic resonance imaging (MRI)-guided biotherapy of TNBC through conjugation of the C-X-C Motif Chemokine 12 (CXCL12)-derived cyclic peptide with tryptone coated NaGdF4 nanodots (5 ± 0.5 nm in diameter, termed as Try-NaGdF4 NDs). The as-prepared anti-CXCR4-NaGdF4 NDs exhibits high longitudinal relaxivity (r1) value (21.87 mM-1S-1), reasonable biocompatibility and good tumor accumulation ability. The features of anti-CXCR4-NaGdF4 NDs improve the tumor-MRI sensitivity and facilitate tumor biotherapy after injection in mouse-bearing MDA-MB-231 tumor model in vivo. MRI-guided biotherapy using anti-CXCR4-NaGdF4 NDs enables to suppress 46% tumor growth. In addition, about 47% injection dose of anti-CXCR4-NaGdF4 NDs is found in the mouse urine at 24 h post-injection. These findings demonstrate that anti-CXCR4-NaGdF4 NDs enable to be used as renal clearable nanomedicine for biotherapy and MRI of breast cancer.

Comparison of lung lesion assessment using free-breathing dynamic contrast-enhanced 1.5-T MRI with a golden-angle radial stack-of-stars VIBE sequence and CT.

BACKGROUND: Few studies have investigated the feasibility of dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) using a free-breathing golden-angle radial stack-of-stars volume-interpolated breath-hold examination (FB radial VIBE) sequence in the lung. PURPOSE: To investigate whether DCE-MRI using the FB radial VIBE sequence can assess morphological and kinetic parameters in patients with pulmonary lesions, with computed tomography (CT) as the reference. MATERIAL AND METHODS: In total, 43 patients (30 men; mean age = 64 years) with one lesion each were prospectively enrolled. Morphological and kinetic features on MRI were calculated. The diagnostic performance of morphological MR features was evaluated using a receiver operating characteristic (ROC) curve. Kinetic features were compared among subgroups based on histopathological subtype, lesion size, and lymph node metastasis. RESULTS: The maximum diameter was not significantly different between CT and MRI (3.66 ± 1.62 cm vs. 3.64 ± 1.72 cm; P = 0.663). Spiculation, lobulation, cavitation or bubble-like areas of low attenuation, and lymph node enlargement had an area under the ROC curve (AUC) >0.9, while pleural indentation yielded an AUC of 0.788. The lung cancer group had significantly lower Ktrans, Ve, and initial AUC values than the other cause inflammation group (0.203, 0.158, and 0.589 vs. 0.597, 0.385, and 1.626; P < 0.05) but significantly higher values than the tuberculosis group (P < 0.05). CONCLUSION: Morphology features derived from FB radial VIBE have high correlations with CT, and kinetic analyses show significant differences between benign and malignant lesions. DCE-MRI with FB radial VIBE could serve as a complementary quantification tool to CT for radiation-free assessments of lung lesions.

Diagnosis for autism spectrum disorder children using T1-based gray matter and arterial spin labeling-based cerebral blood flow network metrics.

Introduction: Autism Spectrum Disorder (ASD) is a complex neurodevelopmental condition characterized by impairments in motor skills, communication, emotional expression, and social interaction. Accurate diagnosis of ASD remains challenging due to the reliance on subjective behavioral observations and assessment scales, lacking objective diagnostic indicators. Methods: In this study, we introduced a novel approach for diagnosing ASD, leveraging T1-based gray matter and ASL-based cerebral blood flow network metrics. Thirty preschool-aged patients with ASD and twenty-two typically developing (TD) individuals were enrolled. Brain network features, including gray matter and cerebral blood flow metrics, were extracted from both T1-weighted magnetic resonance imaging (MRI) and ASL images. Feature selection was performed using statistical t-tests and Minimum Redundancy Maximum Relevance (mRMR). A machine learning model based on random vector functional link network was constructed for diagnosis. Results: The proposed approach demonstrated a classification accuracy of 84.91% in distinguishing ASD from TD. Key discriminating network features were identified in the inferior frontal gyrus and superior occipital gyrus, regions critical for social and executive functions in ASD patients. Discussion: Our study presents an objective and effective approach to the clinical diagnosis of ASD, overcoming the limitations of subjective behavioral observations. The identified brain network features provide insights into the neurobiological mechanisms underlying ASD, potentially leading to more targeted interventions.

Can Three-Dimensional T1-weighted MR Imaging Visualize the Vascular Lumen after Carotid Artery Stenting?

PURPOSE: We aimed to evaluate the quality of various 3D T1-weighted images (T1WIs) of the stent lumen using a carotid stent phantom and determine the suitable T1WI sequence for visualization of the stent lumen after carotid artery stenting. METHODS: The carotid stent phantom consisted of polypropylene tubes that mimicked common carotid arteries with and without stenting. On 1.5T and 3.0T MRI scanners, transverse T1WIs of the carotid stent phantom were obtained using 3D turbo spin-echo (TSE), 3D fast field-echo (3D-FFE), and 3D turbo field echo volumetric interpolated breath-hold examination (VIBE) under clinical conditions. The signal intensity ratio (SIR) was determined using the mean signal intensity of the stent lumen (SIstent) divided by the lumen without a stent in each T1WI. The SNR of the stent lumen (SNRstent) was calculated from SIstent divided by the standard deviation of the uniform region near the stent lumen. RESULTS: The 3D-FFE and VIBE had higher SNRstent than other T1WIs and clearly visualized the stent lumen. The 3D-TSE had the lowest SIR and SNRstent, preventing stent lumen visualization. CONCLUSION: T1WIs obtained using 3D-FFE and VIBE allows stent lumen visualization.

Longitudinal assessment of syringomyelia in Pomeranians.

Introduction: Chiari-like malformation (CM) and syringomyelia (SM) are disorders that, in dogs, affect mainly small and toy breeds, including the Pomeranian. These disorders are linked to a great number of (owner-reported) clinical signs (ORCS) suggestive of pain. Aging was associated with an increased risk of having SM in several studies. However, there are only a few longitudinal studies that assess the presence and severity of CM/SM over time in CKCS dogs and progression of SM was linked to progression of clinical signs. The aim of this study was to investigate ORCS, CM/SM classification, and quantitative syrinx parameters in relation to progression of time (age) within individual Pomeranians. Materials and methods: Pomeranians with or without ORCS and with or without diagnoses of CM/SM were included that had undergone two (or more) MRI studies of the craniocervicothoracic region between January 2020 and June 2023. Classification of CM/SM and quantitative syrinx measurements were performed. Absolute values as well as ratios for syrinx height, width, and cross-sectional area were included for analysis. Results: A total of 19 Pomeranians were included in the study, of which 11 were male (58%) and 8 were female (42%). The median age at the time of MRI1 was 26 months (range 7-44 months). The median scan interval was 26 months (range 11-49 months). Eleven dogs (58%) were presented with ORCS at the time of MRI1, whereas the other 8 dogs (42%) had no ORCS at that time. At the time of MRI2, there were 17/19 dogs (89%) with ORCS and 2/19 dogs without ORCS (11%). Dogs were significantly more likely to have ORCS at MRI2 than MRI1 (p = 0. 0411). There was no significant difference between CM/SM classification at the time of MRI1 and MRI2. Significant differences were found between MRI1 and MRI2 for syrinx height (based on transverse images) (absolute value and ratio P = 0.0059), syrinx width (absolute value P = 0.1055, ratio P = 0.0039), and syrinx cross sectional area (absolute value P = 0.0195, ratio P = 0.0217). Discussion: There are differences in the presence or absence of ORCS as well as quantitative syrinx measurements in Pomeranians at different ages. This finding supports that longitudinal changes occur in the SM status of Pomeranians.