Magnetic resonance imaging-based prediction models for differentiating intraspinal schwannomas from meningiomas: classification and regression tree and random forest analysis.

Background: Due to the variations in surgical approaches and prognosis between intraspinal schwannomas and meningiomas, it is crucial to accurately differentiate between the two prior to surgery. Currently, there is limited research exploring the implementation of machine learning (ML) methods for distinguishing between these two types of tumors. This study aimed to establish a classification and regression tree (CART) model and a random forest (RF) model for distinguishing schwannomas from meningiomas. Methods: We retrospectively collected 88 schwannomas (52 males and 36 females) and 51 meningiomas (10 males and 41 females) who underwent magnetic resonance imaging (MRI) examinations prior to the surgery. Simple clinical data and MRI imaging features, including age, sex, tumor location and size, T1-weighted images (T1WI) and T2-weighted images (T2WI) signal characteristics, degree and pattern of enhancement, dural tail sign, ginkgo leaf sign, and intervertebral foramen widening (IFW), were reviewed. Finally, a CART model and RF model were established based on the aforementioned features to evaluate their effectiveness in differentiating between the two types of tumors. Meanwhile, we also compared the performance of the ML models to the radiologists. The receiver operating characteristic (ROC) curve, accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to evaluate the models and clinicians' discrimination performance. Results: Our investigation reveals significant variations in ten out of 11 variables in the training group and five out of 11 variables in the test group when comparing schwannomas and meningiomas (P<0.05). Ultimately, the CART model incorporated five variables: enhancement pattern, the presence of IFW, tumor location, maximum diameter, and T2WI signal intensity (SI). The RF model combined all 11 variables. The CART model, RF model, radiologist 1, and radiologist 2 achieved an area under the curve (AUC) of 0.890, 0.956, 0.681, and 0.723 in the training group, and 0.838, 0.922, 0.580, and 0.659 in the test group, respectively. Conclusions: The RF prediction model exhibits more exceptional performance than an experienced radiologist in discriminating intraspinal schwannomas from meningiomas. The RF model seems to be better in discriminating the two tumors than the CART model.

A rare case report: multiple intrahepatic masses in a pediatric patient with citrin deficiency.

Deficiency of citrin, the liver-type aspartate-glutamate carrier, arises from biallelic mutations of the gene SLC25A13. Although citrin deficiency (CD) is associated with higher risk of hepatocellular carcinoma (HCC) in adult patients, this association remains inconclusive in pediatric cases. The patient in this paper had been diagnosed to have CD by SLC25A13 analysis at the age 10 months, and then in response to dietary therapy, her prolonged jaundice and marked hepatosplenomegaly resolved gradually. However, she was referred to the hospital once again due to recurrent abdominal distention for 2 weeks at her age 4 years and 9 months, when prominently enlarged liver and spleen were palpated, along with a strikingly elevated serum alpha-fetoprotein (AFP) level of 27605 ng/mL as well as a large mass in the right liver lobe and a suspected tumor thrombus within the portal vein on enhanced computed tomography. After 4 rounds of adjuvant chemotherapy, right hepatic lobectomy and portal venous embolectomy were performed at her age 5 years and 3 months, and metastatic hepatoblastoma was confirmed by histopathological analysis. Afterwards, the patient underwent 5 additional cycles of chemotherapy and her condition remained stable for 7 months after surgery. Unfortunately, hepatoblastoma recurred in the left lobe at the age 5 years and 10 months, which progressed rapidly into liver failure, and led to death at the age 6 years and 1 month. As far as we know, this is the the first case of hepatoblastoma in a patient with CD, raising the possibility of an association between these two conditions.

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.

A diagnostic model based on 18F-FDG PET/CT parameters in improving the differential diagnosis of invasive thymic epithelial tumors and anterior mediastinal lymphomas.

BACKGROUND: Accurately distinguishing between invasive thymic epithelial tumors (TETs) and anterior mediastinal lymphoma before surgery is crucial for subsequent treatment choices. But currently, the diagnosis of invasive TET is sometimes difficult to distinguish from anterior mediastinal lymphoma. OBJECTIVE: To assess the application of fluorine-18-fluorodeoxyglucose (18F-FDG) positron emission tomography/computer tomography (PET/CT) in the differential diagnosis of TETs and anterior mediastinal lymphomas. METHODS: 18F-FDG PET/CT images of 133 invasive TETs and anterior mediastinal lymphomas patients were retrospectively analyzed. In particular, the tumor's longest diameter and maximum standardized uptake value (SUVmax) were evaluated. The SUVmax and longest diameter values of the two groups were analyzed by using the receiver operating characteristic (ROC) curve to determine the optimal threshold and diagnostic efficiency. RESULTS: Age, myasthenia gravis, SUVmax and tumor longest diameter differed significantly between invasive TETs and anterior mediastinal lymphomas patients. The tumor location, calcification, relationship with adjacent vessels and distant metastasis differed significantly between the groups. The ROC analysis showed an AUC for SUVmax and tumor longest diameter of 0.841 and 0.737. Respectively, the cutoff values with the best diagnostic performance were 9.65 (sensitivity: 77.78%, specificity: 81.97%) and 6.65 (sensitivity: 80.56%, specificity: 62.30%) for SUVmax and tumor longest diameter. The diagnostic model of SUVmax, calcification, relationship with surrounding blood vessels, lymph node metastasis and lung metastasis in the highest AUC of 0.935 (sensitivity: 90.16%, specificity: 88.89%). In addition, we incorporated splenic involvement and metastatic sub-diaphragmatic lymph node into Model 2 as a new predictive model 3 for differential diagnosis and found a significant improvement in the diagnostic performance of Model 3. CONCLUSION: The diagnostic model composed of 18F-FDG PET parameters is improving the differential diagnosis of invasive TETs and anterior mediastinal lymphomas.

Using intravoxel incoherent motion imaging to evaluate uric acid-induced renal injury and efficacy after treatment.

OBJECTIVES: To validate the feasibility of intravoxel incoherent motion imaging (IVIM) for monitoring renal injury and uric acid-lowering efficacy in a rat model of hyperuricaemia. METHODS: A total of 92 rats were analysed and categorized into 4 groups: control (CON), hyperuricaemia (HUA), allopurinol intervention (ALL), and combined intervention (COM). Eight rats were randomly selected from each group and underwent IVIM scanning on days 0, 1, 3, 5, 7, and 9. Quantitative magnetic resonance values (D, D*, and f values) measured from the different renal anatomical regions. Quantitative histopathological analysis was performed to assess renal tubular injury using neutrophil gelatinase-associated lipocalin (NGAL), and renal fibrosis using alpha-smooth-muscle-actin (α-SMA). Pearson's correlation analysis was used to determine the correlation between IVIM-derived parameters and the expression of NGAL and α-SMA. RESULTS: The D values of the HUA, ALL, and COM groups generally showed a downward trend over time, and this fluctuation was most significant in the HUA group. The D values showed significant intergroup differences at each point, whereas only a few discrepancies were found in the D* and f values. In addition, the renal D value was negatively correlated with the positive staining rates for NGAL and α-SMA (P < .05), except for the lack of correlation between Dos and α-SMA (P > .05). CONCLUSION: IVIM could be a noninvasive and potential assessment modality for the evaluation of renal injury induced by hyperuricaemia and its prognostic efficacy. ADVANCES IN KNOWLEDGE: IVIM could be a surrogate manner in monitoring renal damage induced by hyperuricaemia and its treatment evaluation.

Association of Muscle Fat Content and Muscle Mass With Impaired Lung Function in Young Adults With Obesity: Evaluation With MRI.

RATIONALE AND OBJECTIVES: Although low muscle mass is associated with decreased lung function, studies exploring the relationship between muscle fat content and lung function impairment are scarce. This study aimed to evaluate the association of muscle mass and fatty infiltration with lung function in young adults with obesity. MATERIALS AND METHODS: We performed a retrospective cross-sectional study of patients aged 18-45 years with obesity who had impaired pulmonary function (case group, n = 66) and those with normal pulmonary function (control group, n = 198) by matching age, sex, body mass index (BMI), and height to assess whether muscle characteristics differed. Muscle mass and muscle fat content were assessed by MRI using a chemical shift-encoded sequence (IDEAL-IQ). RESULTS: A total of 264 patients were enrolled (124 females; mean age 32.0 years). The case group had lower muscle mass than the control group (p = 0.012), and there was an association between low muscle mass and lung function impairment (odds ratio (OR), 3.74; 95% confidence interval (CI), 1.57-8.93). Furthermore, muscle fat content was significantly higher in cases compared to controls (7.4 (2.7) % vs. 6.2 (2.5) %, p = 0.001). Multiple logistic regression analysis showed that muscle fat content was associated with a higher risk of impaired lung function (OR, 2.10; 95% CI, 1.65-2.66), regardless of adiposity and muscle mass. CONCLUSION: Both muscle fat content and muscle mass are associated with impaired lung function in young adults with obesity.

Assessing early tubular protective effects of SGLT2 inhibitor empagliflozin against type 2 diabetes mellitus using functional magnetic resonance imaging.

AIMS: To observe the alterations in functional magnetic resonance imaging parameters in normoalbuminuric type 2 diabetic patients undergoing SGLT2 inhibitor empagliflozin treatment and investigate the early tubular protective effects of the inhibitor. METHODS: This study was performed in normoalbuminuric type 2 diabetes mellitus patients (UACR < 30 mg/g, eGFR ≥ 60 ml/min/1.73 m2). The patients were divided into the intervention group (empagliflozin) and the control group (27 cases each). The intervention group was treated with 10 mg/day empagliflozin tablets orally, while the control group had adjustments to their basic treatment stage. The patients were treated for 6 weeks. RESULTS: The baseline clinical data of the two groups were comparable (P˃0.05). The intervention group exhibited better improvements in blood lipid profiles and more significant reductions in blood uric acid levels compared to the control group (P < 0.05). The two groups had No significant difference in blood pressure changes (P˃0.05). Notably, the intervention group demonstrated a greater reduction in UACR and a more substantial decline in eGFR than the control group (P < 0.05). Regarding functional magnetic resonance imaging parameters, the MD value of the renal medulla region in the intervention group increased after treatment, while the MR2* value of the renal medulla region decreased (P < 0.05). CONCLUSIONS: SGLT2 inhibitor empagliflozin can reduce UACR and eGFR levels in early type 2 diabetic patients with normal proteinuria. Moreover, empagliflozin therapy led to an increase in the MD value and a decrease in the MR2* value of the renal medulla, evidencing the early tubular protective effects of this therapy.

Correlation Between Functional Magnetic Resonance Imaging and Renal Tubular Injury Markers in Early Assessment Of Renal Tubular Injury in Type 2 Diabetes Mellitus.

Objective: Both functional magnetic resonance imaging and renal tubular injury markers have been proved to be able to detect early renal damage in normoalbuminuric diabetic patients. This study mainly explored the functional magnetic resonance imaging parameters and renal tubular injury markers in the early evaluation of type 2 diabetes. Methods: A case observation study was established, and 62 patients with early-stage low-risk type 2 diabetes mellitus with normoalbuminuric (UACR<30 mg/g, eGFR≥60 ml/min/1.73 m2) were included for analysis. Urine kidney damage was determined by ELISA. Kidney injury molecule 1 (KIM-1) and neutrophil gelatinase-associated lipocalin (NGAL) assessment of renal tubular injury, and use of intravoxel incoherent motion magnetic resonance Imaging (intravoxel incoherent motion, IVIM) and blood oxygen level dependent magnetic resonance imaging (blood oxygen level dependent, BOLD) to evaluate renal cortex, medulla blood perfusion, water molecule diffusion, oxygenation level and other functional information, using linear correlation to analyze the correlation between functional magnetic resonance imaging parameters and markers of renal tubular injury. Results: The correlation analysis between IVIM parameters and renal tubular injury markers showed that KIM-1 was inversely correlated with the MD value of the renal medulla region parameter (r = -0.24, P = .03), and was closely related to the other IVIM cortex and medulla. There was no correlation between qualitative parameters (P > .05), and no correlation between NGAL and all parameters of IVIM (P > .05). The correlation analysis between BOLD parameters and renal tubular injury markers showed that KIM-1 was positively correlated with renal medulla region parameter MR2* value (r = 0.26, P = .04) and MCR value (r = 0.28, P = .03), respectively. There was also a positive correlation between NGAL and renal medulla region parameter MR2* value (r = 0.24, P = .04). Conclusion: In the early low-risk type 2 diabetic patients with normoalbuminuria, the more obvious the renal medullary water molecule diffusion disorder, the higher the renal tubular injury marker KIM-1, and the more severe renal medullary hypoxia, the renal tubular injury. The higher the markers KIM-1 and NGAL are, it is proved that the hypoxia and water diffusion disorder in the early renal medulla are related to renal tubular damage.

Well-controlled versus poorly controlled diabetes in patients with obesity: differences in MRI-evaluated pancreatic fat content.

Background: Patients with obesity and poorly controlled type 2 diabetes (T2D) are at high risk of diabetic complications. This study aimed to determine the associations of visceral adipose tissue (VAT), hepatic proton-density fat fraction (PDFF), and pancreatic PDFF with poor glycemic control in patients with obesity and T2D and to evaluate the metabolic effect of bariatric surgery in patients with obesity and poorly controlled diabetes. Methods: In this retrospective cross-sectional study, from July 2019 to March 2021, 151 consecutive obese patients with new-onset T2D (n=28), well-controlled T2D (n=17), poorly controlled T2D (n=32), prediabetes (n=20), or normal glucose tolerance (NGT; n=54) were included. A total of 18 patients with poorly controlled T2D were evaluated before and 12 months after bariatric surgery, and 18 non-obese healthy individuals served as controls. VAT, hepatic PDFF, and pancreatic PDFF were quantified by magnetic resonance imaging (MRI) using a chemical shift-encoded sequence [iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ)]. Univariate analysis and multivariate regression analysis were performed. Results: There were significant differences in VAT, hepatic PDFF, and all pancreatic PDFF between the new-onset T2D, prediabetes, and NGT groups (all P<0.05). Pancreatic tail PDFF was significantly higher in the poorly controlled T2D group than in the well-controlled T2D group (P=0.001). In the multivariate analysis, only pancreatic tail PDFF was significantly associated with increased odds of poor glycemic control [odds ratio (OR) =2.09; 95% confidence interval (CI): 1.11-3.94; P=0.022]. The glycated hemoglobin (HbA1c), hepatic PDFF, and pancreatic PDFF significantly decreased (all P<0.01) after bariatric surgery, and the values were statistically similar to those observed in the non-obese healthy controls. Conclusions: Increased fat in the pancreatic tail is strongly associated with poor glycemic control in patients with obesity and T2D. Bariatric surgery is an effective therapy for poorly controlled diabetes and obesity, which improves glycemic control and decreases ectopic fat deposits.

Stroke recurrence is associated with unfavorable intracranial venous outflow in patients with symptomatic intracranial atherosclerotic large vessel severe stenosis or occlusion.

Objective: The purpose of this study was to investigate the predictive value of intracranial venous outflow for recurrent cerebral ischemic events (RCIE) in patients with symptomatic intracranial atherosclerotic large-vessel severe stenosis or occlusion (sICAS-S/O). Methods: This retrospective study included sICAS-S/O patients with anterior circulation who underwent dynamic computed tomography angiography (dCTA) and computed tomography perfusion (CTP). Arterial collaterals were evaluated using the pial arterial filling score for dCTA data, tissue-level collaterals (TLC) were assessed using the high-perfusion intensity ratio (HIR, Tmax >10 s/Tmax >6 s), and cortical veins were evaluated using the multi-phase venous score (MVS) for the vein of Labbé (VOL), sphenoparietal sinus (SPS), and superficial cerebral middle vein (SCMV). The relationships between multi-phase venous outflow (mVO), TLC, and 1-year RCIE were analyzed. Results: Ninety-nine patients were included, 37 of whom had unfavorable mVO (mVO-) and 62 of whom had favorable mVO (mVO+). Compared with the mVO+ patients, mVO- patients had a higher admission National Institutes of Health Stroke Scale (NIHSS) score (median, 4 [interquartile range (IQR), 0-9] vs. 1 [IQR, 0-4]; p = 0.048), larger ischemic volume (median, 74.3 [IQR, 10.1-177.9] vs. 20.9 [IQR, 5-86.4] mL; p = 0.042), and worse tissue perfusion (median, 0.04 [IQR, 0-0.17] vs. 0 [IQR, 0-0.03]; p = 0.007). Multivariate regression analysis showed that mVO- was an independent predictor of 1-year RCIE. Conclusion: For patients with sICAS-S/O of the anterior circulation, unfavorable intracranial venous outflow is a potential imaging indicator for predicting higher 1-year RCIE risk.

Association of body composition with postoperative complications after laparoscopic sleeve gastrectomy and Roux-en-Y gastric bypass.

OBJECTIVE: To evaluate predictive values of body composition parameters measured from preoperative CT/MRIs for postoperative complications after laparoscopic sleeve gastrectomy (LSG) and Roux-en-Y gastric bypass (LRYGB) in patients with obesity. METHODS: In this retrospective case-control study, patients performing abdominal CT/MRIs within one month before and developing 30-day complications after bariatric procedures were matched for age, sex, and type of surgery with patients without complications (1/3 ratio, respectively). Complications were determined by documentation in the medical record. Two readers blindly segmented the total abdominal muscle area (TAMA) and visceral fat area (VFA) using predetermined thresholds for the Hounsfield unit (HU) on unenhanced CT and the signal intensity (SI) on T1-weighted MRI at the L3 vertebral level. Visceral obesity (VO) was defined as VFA > 136 cm2 in males and > 95 cm2 in females. These measures, along with perioperative variables, were compared. Multivariate logistic regression analyses were performed. RESULTS: Of 145 included patients, 36 had postoperative complications. No significant differences between LSG and LRYGB were present regarding complications and VO. Hypertension (p = 0.022), impaired lung function (p = 0.018), American Society of Anesthesiologists (ASA) grade (p = 0.046), VO (p = 0.021), and VFA/TAMA ratio (p < 0.0001) were associated with postoperative complications in the univariate logistic analysis; the VFA/TAMA ratio was the only independent predictor in multivariate analyses (OR 2.01, 95% CI 1.37-2.93, p < 0.001). CONCLUSION: The VFA/TAMA ratio provides important perioperative information in predicting patients who are likely to develop postoperative complications undergoing bariatric surgery.

Preliminary Feasibility Study on Diffusion Kurtosis Imaging to Monitor the Early Functional Alterations of Kidneys in Streptozocin-Induced Diabetic Rats.

RATIONALE AND OBJECTIVES: The aim of this study was to investigate the potential of diffusion kurtosis imaging (DKI) to assess the early renal functional undulation of diabetic mellitus (DM). MATERIALS AND METHODS: Fifty-seven Sprague-Dawley (SD) rats were randomly divided into two groups and eventually 48 rats were included in this study: the normal control (CON) group and diabetic mellitus (DM) group. Weeks 0, 4, 8, and 12 after the diabetes model was successfully established, all the rats were scanned on the 3.0T MRI. The DKI derived parameters of renal parenchyma, including fractional anisotropy (FAco, FAme), mean diffusivity (MDco, MDme), and mean kurtosis (MKco, MKme) were measured. Their alteration over time was analyzed and then correlated with urine volume (UV), blood urea nitrogen (BUN), and serum creatinine (Scr) using Pearson correlation analysis. Finally, hematoxylin and eosin (H&E) staining was performed on the kidneys of the two groups. RESULT: There was a decreasing trend in FA, MK, and MD values over time in diabetic rats. Also, the gradually worsening histological damage of kidneys was noted over time in diabetic rats. The cortical FA and MK values and medullary FA, MK and MD values of diabetic rats were significantly lower than those of controls at most time points after DM induction. In addition, negative correlations were revealed between the BUN and FAco (r = -0.43, p = 0.03) or FAme value (r = -0.49, p = 0.01). The cortical MK value was moderately correlated with UV (r = -0.46, p = 0.03) and BUN (r = -0.55, p = 0.01). CONCLUSION: The preliminary findings suggest that DKI might be an effective and sensitive tool to assess the early changes of renal function impairment in diabetic rats. The FA values of the cortex and medulla and the MK value of the cortex are sensitive markers in detecting renal injury in diabetic rats.

CuS NP-based nanocomposite with photothermal and augmented-photodynamic activity for magnetic resonance imaging-guided tumor synergistic therapy.

Although many treatments have been developed for oncotherapy, the lack of effective imaging guidance in the therapeutic process is still an urgent problem to be solved. In this study, magnetic resonance contrast agent (Gd) chelated on CuS nanoparticles and glucose oxidase (GOx) were coloaded into mesoporous silica nanoparticles (MSNs) to form GOx-Gd-CuS@MSNs, in which the Gd provided magnetic resonance imaging (MRI) for therapeutic process monitor while GOx could catalyze the generation of H2O2 to enhance the photodynamic therapy (PDT). The in vitro results show that under near-infrared (NIR) laser irradiation (2 W·cm-2, 5 min), temperature rapidly increased by approximately 30 °C for the accumulation of heat. At the same time, GOx on GOx-Gd-CuS@MSNs effectively consumed glucose to produce a large amount of H2O2, which was used to augment PDT through producing highly toxic hydroxyl radicals (·OH) and singlet oxygen (1O2). The photothermal and augmented-photodynamic could induce apoptosis and death of tumor cells. More importantly, the study found that GOx-Gd-CuS@MSNs had MRI performance, which provided imaging guidance during the treatment process, and it can monitor the diffusion of water molecules in the tumor tissue during the treatment and microcirculation perfusion of capillary network. These results indicate that the nanomaterial produced significant synergistic therapeutic effects through photothermal and photodynamic forces, meanwhile showed excellent spatial resolution and deep tissue penetration in imaging.

Intravoxel Incoherent Motion Diffusion-Weighted MR Imaging for Monitoring the Immune Response of Immunogenic Chemotherapy.

Objective: To evaluate the predictive value of intravoxel incoherent motion (IVIM) diffusion-weighted imaging (DWI) in the quantitative assessment of conventional chemotherapy-activated immune responses in mouse tumor models and clinics. Methods: A total of 19 subcutaneous tumor-bearing mice were randomly divided into treated and control groups. Both groups had orderly IVIM DWI examinations before and on days 6 and 12 after the administration of cyclophosphamide (CPA) or saline. Pathologic examinations were performed, including HE staining and immunohistochemistry (IHC). The expressions of immune-related genes in the tumor were measured by qPCR. In addition, six patients with breast cancer requiring neoadjuvant chemotherapy (NACT) also underwent functional MRI examinations and IHC to determine potential antitumor immune response. Results: At the end of the study, the CPA treatment group showed the lowest tumor volume compared to the control group. For pathological examinations, the CPA treatment group showed a lower percentage of CD31 staining (P < 0.01) and Ki-67 staining (P<0.01), and a higher percentage of TUNEL staining (P < 0.01). The tumoral pseudodiffusion coefficient (D*) value showed a positive correlation with the CD31-positive staining rate (r = 0.729, P < 0.0001). The diffusion related parameters (D) value was positively correlated with TUNEL (r = 0.858, P < 0.0001) and negatively correlated with Ki-67 (r = -0.904, P < 0.0001). Moreover, a strong induction of the expression of the immune responses in the CPA treatment group was observed on day 12. D values showed a positive correlation with the Ifnb1-, CD8a-, Mx1-, Cxcl10- (r = 0.868, 0.864, 0.874, and 0.885, respectively, P < 0.0001 for all). Additionally, the functional MRI parameters and IHC results in patients with breast cancer after NACT also showed a close correlation between D value and CD8a (r = 0.631, P = 0.028). Conclusions: The treatment response induced by immunogenic chemotherapy could be effectively evaluated using IVIM-DWI. The D values could be potential, sensitive imaging marker for identifying the antitumor immune response initiated by immunogenic chemotherapy.

Application of Multiparametric Magnetic Resonance Imaging to Monitor the Early Antitumor Effect of CuS@GOD Nanoparticles in a 4 T1 Breast Cancer Xenograft Model.

BACKGROUND: We have developed hybrid nanoparticles (NPs) by co-loading copper sulfide (CuS) NPs and glucose oxidase (GOD) (CuS@GOD NPs) to explore their antitumor properties. PURPOSE: To investigate the feasibility of using multiparametric magnetic resonance imaging (MRI) including intravoxel incoherent motion diffusion-weighted imaging (IVIM-DWI) and R2 * mapping to quantitatively assess the early antitumor effect of CuS@GOD NPs. STUDY TYPE: Prospective. ANIMAL MODEL: The orthotopic BALB/c mice 4 T1 breast cancer model. The 4 T1 xenografts in group 1 mice received normal saline, group 2 received CuS@GOD NPs, group 3 received CuS NPs plus laser, and group 4 received CuS@GOD NPs plus laser (n = 28 for each group). FIELD STRENGTH/SEQUENCE: A 3.0 T/IVIM-DWI MRI single-shot echo-planar imaging, R2 * mapping spoiled gradient recalled echo (SPGR) sequence, T2-weighted images (T2WI) and T1-weighted images (T1WI) fast spin echo (FSE) sequence. ASSESSMENT: The IVIM-DWI and R2 * mapping were performed before and after treatment at 0 hour, 0.5 hour, 1 hour, 2 hours, 4 hours, and 24 hours in four groups and the MRI parameters were obtained. Correlation analysis between the MRI parameters and histological analyses was conducted. STATISTICAL TESTS: One-way ANOVA, Pearson's correlation analysis, two independent samples t test, intraclass correlation coefficient. P < 0.05 was considered to be statistically significant. RESULTS: In group 4, the tumoral D value was significantly higher than that of group 2 at 24 hours (0.541 ± 0.065 vs. 0.492 ± 0.051). The f value of group 4 was significantly lower than that of groups 1 and 2 at 2 hours (10.83 ± 2.16 vs. 14.28 ± 1.86, 16.67 ± 3.53, respectively). The R2 * value was significantly increased at 0 hour in group 4 compared to that of groups 1 and 2 (64.552 ± 4.663 vs. 42.441 ± 1.516, 43.165 ± 1.709, respectively). D, f, and R2 * were correlated with the histological staining results (r = 0.695-0.970). DATA CONCLUSION: The IVIM-DWI-derived D and f and R2 * mapping-derived R2 * could monitor early response to CuS@GOD NPs treatment in vivo. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Multiparametric MRI analysis for the evaluation of renal function in patients with hyperuricemia: a preliminary study.

BACKGROUND: To investigate the renal dysfunction in patients with hyperuricemia by employing a multiparametric MRI protocol, consisting of quantitative water molecule diffusion, microstructure, microscopic perfusion, and oxygenation measurements in kidneys. MATERIALS AND METHODS: A total of 48 patients with hyperuricemia (HU) and 22 age-matched healthy control subjects (HC) were enrolled in the study. For each participant, three different functional magnetic resonance imaging (fMRI) sequences were acquired and analyzed, including intravoxel incoherent motion imaging (IVIM), diffusion tensor imaging (DTI), and blood-oxygen-level-dependent MRI (BOLD). Thereafter, an independent two-sample t-test was applied to discover the significant differences of MRI indices between the hyperuricemia (HU) and HC groups, and the specific potential biomarkers between two subgroups of HU group (asymptomatic hyperuricemia group (AH) and gouty arthritis group (GA)). Further, multivariate logistic regression analyses were performed to classify the AH from the GA group using the MRI indices with significant between-group differences. The receiver operating characteristic (ROC) curve was plotted, and the area under the ROC curve (AUC) was calculated to assess the performance of each MR index for differentiation between the AH and GA groups. RESULTS: Ten parametric values of the HU group were significantly lower than those of the HC group among the 14 fMRI parameters (P < 0.05). The cortical D, D*, and f values and medullary D and R2*values had significant differences between the AH and GA groups (P < 0.05). Combining the cortical D and f values and medullary R2* value gave the best diagnostic efficacy, yielding an AUC, sensitivity, and specificity of 0.967 ± 0.022, 91.67%, and 95.83%, respectively. CONCLUSIONS: A multiparametric MR analysis plays an important role in the evaluation of renal dysfunction in hyperuricemia from multiple perspectives. It could be a promising method for noninvasive detection and identification of the early-stage renal damage induced by hyperuricemia.

Non-invasive investigation of early kidney damage in streptozotocin-induced diabetic rats by intravoxel incoherent motion diffusion-weighted (IVIM) MRI.

BACKGROUND: The current study investigated the performance of intravoxel incoherent motion diffusion (IVIM) technology in monitoring early renal injury in streptozotocin rats. METHODS: Forty-eight Sprague-Dawley (SD) rats were divided into a control group and a diabetic mellitus (DM) group. Six rats in each group were randomly selected for MR scans at four different time points (0, 4, 8, and 12 weeks). The IVIM-derived parameters (D, D*, f and ADC values) of the renal cortex (CO), outer and inner stripe of the outer medulla (OS, IS), and internal medulla (IM) were acquired. Changes in each IVIM-derived parameter over time were analyzed, and differences between the two groups at each point were assessed. The associations between the IVIM parameters and IV collagen expression, urine volume (UV), blood urea nitrogen (BUN), and serum creatinine (Scr) were investigated. RESULTS: The D and D* values of CO and the ADC values of CO, OS, IS and IM displayed significantly different trends between the two groups over time (P<0.05). In addition, significant correlations were discovered between the D* value of CO and UV and BUN (r=0.527, P=0.033; r=0.617, P=0.005), between the ADC value of IM and BUN (r=0.557, P=0.019) and between the f value of IM and BUN (r=0.527, P=0.033). No correlation was found between IVIM parameters and IV collagen expression and Scr. CONCLUSIONS: IVIM is a potential sensitive and noninvasive technology for the simultaneous assessment of early renal cortical and medullary injuries induced by diabetes.

A prospective study of dual-energy computed tomography for differentiating metastatic and non-metastatic lymph nodes of colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is the third most common malignancy worldwide, and lymph node metastasis is considered to be a risk factor for local recurrence and a poor prognosis in colorectal cancer. However, there remains a lack of reliable and non-invasive biomarkers to identify the lymph node status of CRC patients preoperatively. The purpose of this study was to explore the ability of dual-energy computed tomography (DECT) to differentiate metastatic from non-metastatic lymph nodes in colorectal cancer. METHODS: Seventy-one patients with primary colorectal cancer underwent contrast-enhanced dual-energy computed tomography imaging preoperatively. The colorectal specimen was scanned postoperatively, and lymph nodes were matched to the pathology report. The following dual-energy computed tomography quantitative parameters were analyzed: dual-energy curve slope value (λHU), standardized iodine concentration (n△HU), iodine water ratio (nIWR), electron density value (nρeff), and effective atom-number (nZ), based on metastatic and non-metastatic lymph node differentiation. Also, sensitivity and specificity analyses were performed using receiver operating characteristic curves. RESULTS: In all patients, one hundred and fifty lymph nodes, including 66 non-metastatic and 84 metastatic lymph nodes, were matched using the radiological-pathological correlation. Metastatic nodes had significantly greater λHU, n△HU, and nIWR values than non-metastatic nodes in both the arterial and venous phases (P<0.01). The area under curve (AUC), sensitivity, and specificity were 0.80, 80%, and 66% for λHU; 0.86, 70%, and 95% for n△HU; and 0.88, 71%, and 95% for nIWR in the arterial phase. There was no significant difference in electron density and effective Z values between metastatic and non-metastatic lymph nodes. CONCLUSIONS: DECT quantitative parameters may help differentiate between metastatic and normal lymph nodes in patients with CRC.

Evaluating the Velocity and Extent of Cortical Venous Filling in Patients With Severe Middle Cerebral Artery Stenosis or Occlusion.

Objective: To investigate the velocity and extent of cortical venous filling (CVF) and its association with clinical manifestations in patients with severe stenosis or occlusion of the middle cerebral artery (MCA) using dynamic computed tomography angiography (CTA). Methods: Fifty-eight patients (36 symptomatic and 22 asymptomatic) with severe unilateral stenosis (≥70%) or occlusion of the MCA M1 segment who underwent dynamic CTA were included. Collateral status, antegrade flow, and CVF of each patient were observed using dynamic CTA. Three types of cortical veins were selected to observe the extent of CVF, and the absence of CVF (CVF-) was recorded. Based on the appearance of CVF in the superior sagittal sinus, instances of CVF, including early (CVF1), peak (CVF2), and late (CVF3) venous phases, were recorded. The differences in CVF times between the affected and contralateral hemispheres were represented as rCVFs, and CVF velocity was defined compared to the median time of each rCVF. Results: All CVF times in the affected hemisphere were longer than those in the contralateral hemisphere (p < 0.05). Patients with symptomatic MCA stenosis had more ipsilateral CVF- (p = 0.02) and more delayed CVF at rCVF2 and rCVF21 (rCVF2-rCVF1) (p = 0.03 and 0.001, respectively) compared to those with asymptomatic MCA stenosis. For symptomatic patients, fast CVF at rCVF21 was associated with poor collateral status (odds ratio [OR] 6.42, 95% confidence interval [CI] 1.37-30.05, p = 0.02), and ipsilateral CVF- in two cortical veins was associated with poor 3-month outcomes (adjusted OR 0.025, 95% CI 0.002-0.33, p = 0.005). Conclusions: Complete and fast CVF is essential for patients with symptomatic MCA stenosis or occlusion. The clinical value of additional CVF assessment should be explored in future studies to identify patients with severe MCA stenosis or occlusion at a higher risk of stroke occurrence and poor recovery.

Development and Validation of a Machine Learning Approach for Automated Severity Assessment of COVID-19 Based on Clinical and Imaging Data: Retrospective Study.

BACKGROUND: COVID-19 has overwhelmed health systems worldwide. It is important to identify severe cases as early as possible, such that resources can be mobilized and treatment can be escalated. OBJECTIVE: This study aims to develop a machine learning approach for automated severity assessment of COVID-19 based on clinical and imaging data. METHODS: Clinical data-including demographics, signs, symptoms, comorbidities, and blood test results-and chest computed tomography scans of 346 patients from 2 hospitals in the Hubei Province, China, were used to develop machine learning models for automated severity assessment in diagnosed COVID-19 cases. We compared the predictive power of the clinical and imaging data from multiple machine learning models and further explored the use of four oversampling methods to address the imbalanced classification issue. Features with the highest predictive power were identified using the Shapley Additive Explanations framework. RESULTS: Imaging features had the strongest impact on the model output, while a combination of clinical and imaging features yielded the best performance overall. The identified predictive features were consistent with those reported previously. Although oversampling yielded mixed results, it achieved the best model performance in our study. Logistic regression models differentiating between mild and severe cases achieved the best performance for clinical features (area under the curve [AUC] 0.848; sensitivity 0.455; specificity 0.906), imaging features (AUC 0.926; sensitivity 0.818; specificity 0.901), and a combination of clinical and imaging features (AUC 0.950; sensitivity 0.764; specificity 0.919). The synthetic minority oversampling method further improved the performance of the model using combined features (AUC 0.960; sensitivity 0.845; specificity 0.929). CONCLUSIONS: Clinical and imaging features can be used for automated severity assessment of COVID-19 and can potentially help triage patients with COVID-19 and prioritize care delivery to those at a higher risk of severe disease.