Dual-Modality Imaging-Guided Manganese-Based Nanotransformer for Enhanced Gas-Photothermal Therapy Combined Immunotherapeutic Strategy Against Triple-Negative Breast Cancer.

Activating the stimulator of the interferon gene (STING) is a promising immunotherapeutic strategy for converting "cold" tumor microenvironment into "hot" one to achieve better immunotherapy for malignant tumors. Herein, a manganese-based nanotransformer is presented, consisting of manganese carbonyl and cyanine dye, for MRI/NIR-II dual-modality imaging-guided multifunctional carbon monoxide (CO) gas treatment and photothermal therapy, along with triggering cGAS-STING immune pathway against triple-negative breast cancer. This nanosystem is able to transfer its amorphous morphology into a crystallographic-like formation in response to the tumor microenvironment, achieved by breaking metal-carbon bonds and forming coordination bonds, which enhances the sensitivity of magnetic resonance imaging. Moreover, the generated CO and photothermal effect under irradiation of this nanotransformer induce immunogenic death of tumor cells and release damage-associated molecular patterns. Simultaneously, the Mn acts as an immunoactivator, potentially stimulating the cGAS-STING pathway to augment adaptive immunity, resulting in promoting the secretion of type I interferon, the proliferation of cytotoxic T lymphocytes and M2-macrophages repolarization. This nanosystem-based gas-photothermal treatment and immunoactivating therapy synergistic effect exhibit excellent antitumor efficacy both in vitro and in vivo, reducing the risk of triple-negative breast cancer recurrence and metastasis; thus, this strategy presents great potential as multifunctional immunotherapeutic agents for cancer treatment.

Pathogenic variations in MAML2 and MAMLD1 contribute to congenital hypothyroidism due to dyshormonogenesis by regulating the Notch signalling pathway.

BACKGROUND: In several countries, thyroid dyshormonogenesis is more common than thyroid dysgenesis in patients with congenital hypothyroidism (CH). However, known pathogenic genes are limited to those directly involved in hormone biosynthesis. The aetiology and pathogenesis of thyroid dyshormonogenesis remain unknown in many patients. METHODS: To identify additional candidate pathogenetic genes, we performed next-generation sequencing in 538 patients with CH and then confirmed the functions of the identified genes in vitro using HEK293T and Nthy-ori 3.1 cells, and in vivo using zebrafish and mouse model organisms. RESULTS: We identified one pathogenic MAML2 variant and two pathogenic MAMLD1 variants that downregulated canonical Notch signalling in three patients with CH. Zebrafish and mice treated with N-[N-(3,5-difluorophenacetyl)-l-alanyl]-S-phenylglycine t-butylester, a γ-secretase inhibitor exhibited clinical manifestations of hypothyroidism and thyroid dyshormonogenesis. Through organoid culture of primary mouse thyroid cells and transcriptome sequencing, we demonstrated that Notch signalling within thyroid cells directly affects thyroid hormone biosynthesis rather than follicular formation. Additionally, these three variants blocked the expression of genes associated with thyroid hormone biosynthesis, which was restored by HES1 expression. The MAML2 variant exerted a dominant-negative effect on both the canonical pathway and thyroid hormone biosynthesis. MAMLD1 also regulated hormone biosynthesis through the expression of HES3, the target gene of the non-canonical pathway. CONCLUSIONS: This study identified three mastermind-like family gene variants in CH and revealed that both canonical and non-canonical Notch signalling affected thyroid hormone biosynthesis.

Diffusion basis spectrum imaging detects pathological alterations in substantia nigra and white matter tracts with early-stage Parkinson's disease.

OBJECTIVES: Using diffusion basis spectrum imaging (DBSI) to examine the microstructural changes in the substantia nigra (SN) and global white matter (WM) tracts of patients with early-stage PD. METHODS: Thirty-seven age- and sex-matched patients with early-stage PD and 22 healthy controls (HCs) were enrolled in this study. All participants underwent clinical assessments and diffusion-weighted MRI scans, analyzed by diffusion tensor imaging (DTI) and DBSI to assess the pathologies of PD in SN and global WM tracts. RESULTS: The lower DTI fraction anisotropy (FA) was seen in SN of PD patients (PD: 0.316 ± 0.034 vs HCs: 0.331 ± 0.019, p = 0.015). The putative cells marker-DBSI-restricted fraction (PD: 0.132 ± 0.051 vs HCs: 0.105 ± 0.039, p = 0.031) and the edema/extracellular space marker-DBSI non-restricted-fraction (PD: 0.150 ± 0.052 vs HCs: 0.122 ± 0.052, p = 0.020) were both significantly higher and the density of axons/dendrites marker-DBSI fiber-fraction (PD: 0.718 ± 0.073 vs HCs: 0.773 ± 0.071, p = 0.003) was significantly lower in SN of PD patients. DBSI-restricted fraction in SN was negatively correlated with HAMA scores (r = - 0.501, p = 0.005), whereas DTI-FA was not correlated with any clinical scales. In WM tracts, only higher DTI axial diffusivity (AD) among DTI metrics was found in multiple WM regions in PD, while lower DBSI fiber-fraction and higher DBSI non-restricted-fraction were detected in multiple WM regions. DBSI non-restricted-fraction in both left fornix (cres)/stria terminalis (r = -0.472, p = 0.004) and right posterior thalamic radiation (r = - 0.467, p = 0.005) was negatively correlated with MMSE scores. CONCLUSION: DBSI could potentially detect and quantify the extent of inflammatory cell infiltration, fiber/dendrite loss, and edema in both SN and WM tracts in patients with early-stage PD, a finding remains to be further investigated through more extensive longitudinal DBSI analysis. CLINICAL RELEVANCE STATEMENT: Our study shows that DBSI indexes can potentially detect early-stage PD's pathological changes, with a notable ability to distinguish between inflammation and edema. This implies that DBSI has the potential to be an imaging biomarker for early PD diagnosis. KEY POINTS: • Diffusion basis spectrum imaging detected higher restricted-fraction in Parkinson's disease, potentially reflecting inflammatory cell infiltration. • Diffusion basis spectrum imaging detected higher non-restricted-fraction and lower fiber-fraction in Parkinson's disease, indicating the presence of edema and/or dopaminergic neuronal/dendritic loss. • Diffusion basis spectrum imaging metrics correlated with non-motor symptoms, suggesting its potential diagnostic role to detect early-stage PD dysfunctions.

Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma.

BACKGROUND: Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options. PURPOSE: To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC). MATERIAL AND METHODS: A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve. RESULTS: Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; P = 0.008) and MRI (0.946 vs. 0.876; P = 0.003), whereas rim APHE on CT and MRI did not differ significantly (P = 0.809). CONCLUSION: The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

Fuhrman nuclear grade prediction of clear cell renal cell carcinoma: influence of volume of interest delineation strategies on machine learning-based dynamic enhanced CT radiomics analysis.

OBJECTIVE: To investigate the influence of different volume of interest (VOI) delineation strategies on machine learning-based predictive models for discrimination between low and high nuclear grade clear cell renal cell carcinoma (ccRCC) on dynamic contrast-enhanced CT. METHODS: This study retrospectively collected 177 patients with pathologically proven ccRCC (124 low-grade; 53 high-grade). Tumor VOI was manually segmented, followed by artificially introducing uncertainties as: (i) contour-focused VOI, (ii) margin erosion of 2 or 4 mm, and (iii) margin dilation (2, 4, or 6 mm) inclusive of perirenal fat, peritumoral renal parenchyma, or both. Radiomics features were extracted from four-phase CT images (unenhanced phase (UP), corticomedullary phase (CMP), nephrographic phase (NP), excretory phase (EP)). Different combinations of four-phasic features for each VOI delineation strategy were used to build 176 classification models. The best VOI delineation strategy and superior CT phase were identified and the top-ranked features were analyzed. RESULTS: Features extracted from UP and EP outperformed features from other single/combined phase(s). Shape features and first-order statistics features exhibited superior discrimination. The best performance (ACC 81%, SEN 67%, SPE 87%, AUC 0.87) was achieved with radiomics features extracted from UP and EP based on contour-focused VOI. CONCLUSION: Shape and first-order features extracted from UP + EP images are better feature representations. Contour-focused VOI erosion by 2 mm or dilation by 4 mm within peritumor renal parenchyma exerts limited impact on discriminative performance. It provides a reference for segmentation tolerance in radiomics-based modeling for ccRCC nuclear grading. KEY POINTS: • Lesion delineation uncertainties are tolerated within a VOI erosion range of 2 mm or dilation range of 4 mm within peritumor renal parenchyma for radiomics-based ccRCC nuclear grading. • Radiomics features extracted from unenhanced phase and excretory phase are superior to other single/combined phase(s) at differentiating high vs low nuclear grade ccRCC. • Shape features and first-order statistics features showed superior discriminative capability compared to texture features.

Radiomics can differentiate high-grade glioma from brain metastasis: a systematic review and meta-analysis.

OBJECTIVE: (1) To evaluate the diagnostic performance of radiomics in differentiating high-grade glioma from brain metastasis and how to improve the model. (2) To assess the methodological quality of radiomics studies and explore ways of embracing the clinical application of radiomics. METHODS: Studies using radiomics to differentiate high-grade glioma from brain metastasis published by 26 July 2021 were systematically reviewed. Methodological quality and risk of bias were assessed using the Radiomics Quality Score (RQS) system and Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2) tool, respectively. Pooled sensitivity and specificity of the radiomics model were also calculated. RESULTS: Seventeen studies combining 1,717 patients were included in the systematic review, of which 10 studies without data leakage suspicion were employed for the quantitative statistical analysis. The average RQS was 5.13 (14.25% of total), with substantial or almost perfect inter-rater agreements. The inclusion of clinical features in the radiomics model was only reported in one study, as was the case for publicly available algorithm code. The pooled sensitivity and specificity were 84% (95% CI, 80-88%) and 84% (95% CI, 81-87%), respectively. The performances of feature extraction from the volume of interest (VOI) or (semi) automatic segmentation in the radiomics models were superior to those of protocols employing region of interest (ROI) or manual segmentation. CONCLUSION: Radiomics can accurately differentiate high-grade glioma from brain metastasis. The adoption of standardized workflow to avoid potential data leakage as well as the integration of clinical features and radiomics are advised to consider in future studies. KEY POINTS: • The pooled sensitivity and specificity of radiomics for differentiating high-grade gliomas from brain metastasis were 84% and 84%, respectively. • Avoiding potential data leakage by adopting an intensive and standardized workflow is essential to improve the quality and generalizability of the radiomics model. • The application of radiomics in combination with clinical features in differentiating high-grade gliomas from brain metastasis needs further validation.

Dual-Drug Backboned Polyprodrug with a Predefined Drug Combination for Synergistic Chemotherapy.

The codelivery of drugs at specific optimal ratios to cancer cells is vital for combination chemotherapy. However, most of the current strategies are unable to coordinate the loading and release of drug combinations to acquire precise and controllable synergistic ratios. In this work, we designed an innovative dual-drug backboned and reduction-sensitive polyprodrug PEG-P(MTO-ss-CUR) containing the anticancer drugs mitoxantrone (MTO) and curcumin (CUR) at an optimal synergistic ratio to reverse drug resistance. Due to synchronous drug activation and polymer backbone degradation, drug release at the predefined ratio with a synergistic anticancer effect was demonstrated by in vitro and in vivo experiments. Therefore, the dual-drug delivery system developed in this work provides a novel and efficient strategy for combination chemotherapy.

Upregulation of GBP1 in thyroid primordium is required for developmental thyroid morphogenesis.

PURPOSE: Congenital hypothyroidism (CH) is a common congenital endocrine disorder in humans. CH-related diseases such as athyreosis, thyroid ectopy, and hypoplasia are primarily caused by dysgenic thyroid development. However, the underlying molecular mechanisms remain unknown. METHODS: To identify novel CH candidate genes, 192 CH patients were enrolled, and target sequencing of 21 known CH-related genes was performed. The remaining 98 CH patients carrying no known genes were subjected to exome sequencing (ES). The functions of the identified variants were confirmed using thyroid epithelial cells in vitro and in zebrafish model organisms in vivo. RESULTS: Four pathogenic GBP1 variations from three patients were identified. In zebrafish embryos, gbp1 knockdown caused defective thyroid primordium morphogenesis and hypothyroidism. The thyroid cells were stuck together and failed to dissociate from each other to form individual follicles in gbp1-deficient embryos. Furthermore, defects were restored with wild-type human GBP1 (hGBP1) messenger RNA (mRNA) except for mutated hGBP1 (p.H150Y, p.L187P) overexpression. GBP1 promoted ß-catenin translocation into the cytosol and suppressed the formation of cellular adhesion complexes. Suppression of cell-cell adhesion restored the thyroid primordium growth defect observed in gbp1-deficient zebrafish embryos. CONCLUSION: This study provides further understanding regarding thyroid development and shows that defective cellular remodeling could cause congenital hypothyroidism.

Correlation of DUOX2 residual enzymatic activity with phenotype in congenital hypothyroidism caused by biallelic DUOX2 defects.

DUOX2 is the most frequently mutated gene in patients with congenital hypothyroidism (CH) in China. However, no reliable genotype-phenotype relationship has been found in patients with DUOX2 mutations. In this study, DUOX2 mutations were screened in 266 CH patients, and the enzymatic activity of 89 DUOX2 variants was determined in vitro. Furthermore, the DUOX2 residual activity in 76 CH patients caused by DUOX2 biallelic mutations was calculated. The thyroid-stimulating hormone (TSH) and free thyroxine (FT4) levels were found to be higher and lower in patients with DUOX2 residual activity ≤22%, respectively, compared to patients with residual enzymatic activity >22%. Moreover, we interpreted the pathogenicity of DUOX2 variants by applying the ACMG classification criteria with or without PS3/BS3 evidence. The results indicated that residual DUOX2 enzymatic activity was closely related to the clinical phenotypes of CH patients caused by DUOX2 biallelic mutations. These findings suggest that the residual enzymatic activity of 22% may be a cutoff value for estimating the severity of hypothyroidism in CH patients with biallelic DUOX2 mutations. Well-established functional studies are useful and necessary to evaluate the pathogenicity of DUOX2 variants, improving the accuracy and scope of genetic consultations.

The impact of edema and fiber crossing on diffusion MRI metrics assessed in an ex vivo nerve phantom: Multi-tensor model vs. diffusion orientation distribution function.

Diffusion tensor imaging (DTI) has been employed for over 2 decades to noninvasively quantify central nervous system diseases/injuries. However, DTI is an inadequate simplification of diffusion modeling in the presence of coexisting inflammation, edema and crossing nerve fibers. We employed a tissue phantom using fixed mouse trigeminal nerves coated with various amounts of agarose gel to mimic crossing fibers in the presence of vasogenic edema. Diffusivity measures derived by DTI and diffusion basis spectrum imaging (DBSI) were compared at increasing levels of simulated edema and degrees of fiber crossing. Furthermore, we assessed the ability of DBSI, diffusion kurtosis imaging (DKI), generalized q-sampling imaging (GQI), q-ball imaging (QBI) and neurite orientation dispersion and density imaging to resolve fiber crossing, in reference to the gold standard angles measured from structural images. DTI-computed diffusivities and fractional anisotropy were significantly confounded by gel-mimicked edema and crossing fibers. Conversely, DBSI calculated accurate diffusivities of individual fibers regardless of the extent of simulated edema and degrees of fiber crossing angles. Additionally, DBSI accurately and consistently estimated crossing angles in various conditions of gel-mimicked edema when compared with the gold standard (r2 = 0.92, P = 1.9 × 10-9 , bias = 3.9°). Small crossing angles and edema significantly impact the diffusion orientation distribution function, making DKI, GQI and QBI less accurate in detecting and estimating fiber crossing angles. Lastly, we used diffusion tensor ellipsoids to demonstrate that DBSI resolves the confounds of edema and crossing fibers in the peritumoral edema region from a patient with lung cancer metastasis, while DTI failed. In summary, DBSI is able to separate two crossing fibers and accurately recover their diffusivities in a complex environment characterized by increasing crossing angles and amounts of gel-mimicked edema. DBSI also indicated better angular resolution compared with DKI, QBI and GQI.

Radiomics of small renal masses on multiphasic CT: accuracy of machine learning-based classification models for the differentiation of renal cell carcinoma and angiomyolipoma without visible fat.

OBJECTIVE: To investigate the discriminative capabilities of different machine learning-based classification models on the differentiation of small (< 4 cm) renal angiomyolipoma without visible fat (AMLwvf) and renal cell carcinoma (RCC). METHODS: This study retrospectively collected 163 patients with pathologically proven small renal mass, including 118 RCC and 45 AMLwvf patients. Target region of interest (ROI) delineation, followed by texture feature extraction, was performed on a representative slice with the largest lesion area on each phase of the four-phase CT images. Fifteen concatenations of the four-phasic features were fed into 224 classification models (built with 8 classifiers and 28 feature selection methods), classification performances of the 3360 resultant discriminative models were compared, and the top-ranked features were analyzed. RESULTS: Image features extracted from the unenhanced phase (UP) CT image demonstrated dominant classification performances over features from other three phases. The two discriminative models "SVM + t_score" and "SVM + relief" achieved the highest classification AUC of 0.90. The 10 top-ranked features from UP included 1 shape feature, 5 first-order statistics features, and 4 texture features, where the shape feature and the first-order statistics features showed superior discriminative capabilities in differentiating RCC vs. AMLwvf through the t-SNE visualization. CONCLUSION: Image features extracted from UP are sufficient to generate accurate differentiation between AMLwvf and RCC using machine learning-based classification model. KEY POINTS: • Radiomics extracted from unenhanced CT are sufficient to accurately differentiate angiomyolipoma without visible fat and renal cell carcinoma using machine learning-based classification model. • The highest discriminative models achieved an AUC of 0.90 and were based on the analysis of unenhanced CT, alone or in association with images obtained at the nephrographic phase. • Features related to shape and to histogram analysis (first-order statistics) showed superior discrimination compared with gray-level distribution of the image (second-order statistics, commonly called texture features).

Clear cell renal cell carcinoma: the value of sex-specific abdominal visceral fat measured on CT for prediction of Fuhrman nuclear grade.

OBJECTIVE: To explore whether sex-specific abdominal visceral fat composition on CT can predict the Fuhrman nuclear grade of clear cell renal cell carcinoma (ccRCC). METHODS: One hundred seventy-one patients (123 males and 48 females) from four hospitals (multicentre group) and 159 patients (109 males and 50 females) from the cancer imaging archive (TCIA-KIRC group) with pathologically proven ccRCC (multicentre: 124 low grade and 47 high grade; TCIA-KIRC: 79 low grade and 80 high grade) were retrospectively included. Abdominal fat was segmented into subcutaneous fat area (SFA) and visceral fat area (VFA) on CT using ImageJ. The total fat area (TFA) and relative VFA (rVFA) were then calculated. Clinical characteristics (age, sex, waist circumference and maximum tumour diameter) were also assessed. Univariate and multivariate logistic regression analyses were performed to identify the association between general or sex-specific visceral fat composition and Fuhrman grade. RESULTS: Females with high-grade ccRCC from the multicentre group had a higher rVFA (42.4 vs 31.3, p = 0.001) than those with low-grade ccRCC after adjusting for age. There was no significant difference in males. The rVFA remained a stable and independent predictor for females high-grade ccRCC in both the univariate (multicentre: OR 1.205, 95% CI 1.074-1.352, p = 0.001; TCIA-KIRC: OR 1.171, 95% CI 1.016-1.349, p = 0.029) and multivariate (multicentre: OR 1.095, 95% CI 1.024-1.170, p = 0.003; TCIA-KIRC: OR 1.103, 95% CI 1.024-1.187, p = 0.010) models. CONCLUSIONS: Sex-specific visceral fat composition has different values for predicting high-grade ccRCC and could be used as an independent predictor for females with high-grade ccRCC. KEY POINTS: • Visceral fat measurement (rVFA) as an independent predictor for high-grade ccRCC had good predictive power in females, but not in males. • Sex-specific visceral fat composition was significantly associated with high-grade ccRCC in females only. • The rVFA could be considered one of the risk factors for high-grade ccRCC for females.

Aberrant Advanced Cognitive and Attention-Related Brain Networks in Parkinson's Disease with Freezing of Gait.

Background: Freezing of gait (FOG) is a disabling gait disorder influencing patients with Parkinson's disease (PD). Accumulating evidence suggests that FOG is related to the functional alterations within brain networks. We investigated the changes in brain resting-state functional connectivity (FC) in patients with PD with FOG (FOG+) and without FOG (FOG-). Methods: Resting-state functional magnetic resonance imaging (RS-fMRI) data were collected from 55 PD patients (25 FOG+ and 30 FOG-) and 26 matched healthy controls (HC). Differences in intranetwork connectivity between FOG+, FOG-, and HC individuals were explored using independent component analysis (ICA). Results: Seven resting-state networks (RSNs) with abnormalities, including motor, executive, and cognitive-related networks, were found in PD patients compared to HC. Compared to FOG- patients, FOG+ patients had increased FC in advanced cognitive and attention-related networks. In addition, the FC values of the auditory network and default mode network were positively correlated with the Gait and Falls Questionnaire (GFQ) and Freezing of Gait Questionnaire (FOGQ) scores in FOG+ patients. Conclusions: Our findings suggest that the neural basis of PD is associated with impairments of multiple functional networks. Notably, alterations of advanced cognitive and attention-related networks rather than motor networks may be related to the mechanism of FOG.

Whole-lesion histogram analysis of the apparent diffusion coefficient: Evaluation of the correlation with subtypes of mucinous breast carcinoma.

PURPOSE: To evaluate the utility of the whole-lesion histogram apparent diffusion coefficient (ADC) for characterizing the heterogeneity of mucinous breast carcinoma (MBC) and to determine which ADC metrics may help to best differentiate subtypes of MBC. MATERIALS AND METHODS: This retrospective study involved 52 MBC patients, including 37 pure MBC (PMBC) and 15 mixed MBC (MMBC). The PMBC patients were subtyped into PMBC-A (20 cases) and PMBC-B (17 cases) groups. All patients underwent preoperative diffusion-weighted imaging (DWI) at 1.5T and the whole-lesion ADC assessments were generated. Histogram-derived ADC parameters were compared between PMBC vs. MMBC and PMBC-A vs. PMBC-B, and receiver operating characteristic (ROC) curve analysis was used to determine optimal histogram parameters for differentiating these groups. RESULTS: The PMBC group exhibited significantly higher ADC values for the mean (P = 0.004), 25th (P = 0.004), 50th (P = 0.004), 75th (P = 0.006), and 90th percentiles (P = 0.013) and skewness (P = 0.021) than did the MMBC group. The 25th percentile of ADC values achieved the highest area under the curve (AUC) (0.792), with a cutoff value of 1.345 × 10-3 mm2 /s, in distinguishing PMBC and MMBC. The PMBC-A group showed significantly higher ADC values for the mean (P = 0.049), 25th (P = 0.015), and 50th (P = 0.026) percentiles and skewness (P = 0.004) than did the PMBC-B group. The 25th percentile of the ADC cutoff value (1.476 × 10-3 mm2 /s) demonstrated the best AUC (0.837) among the ADC values for distinguishing PMBC-A and PMBC-B. CONCLUSION: Whole-lesion ADC histogram analysis enables comprehensive evaluation of an MBC in its entirety and differentiating subtypes of MBC. Thus, it may be a helpful and supportive tool for conventional MRI. LEVEL OF EVIDENCE: 4 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;47:391-400.

miR-92b-3p acts as a tumor suppressor by targeting Gabra3 in pancreatic cancer.

BACKGROUND: MicroRNAs (miRNAs) can act as oncogenes or tumor suppressors by controlling cell proliferation, differentiation, metastasis and apoptosis, and miRNA dysregulation is involved in the development of pancreatic cancer (PC). Our previous study demonstrated that Gabra3 plays critical roles in cancer progression. However, whether Gabra3 is regulated by miRNAs in PC remains unknown. METHODS: The expression levels of miR-92b-3p and Gabra3 were measured by quantitative PCR (qPCR), immunoblotting, in situ hybridization (ISH) and immunohistochemistry (IHC). The proliferation rate of PC cells was detected by MTS assay. Wound-healing and transwell assays were used to examine the invasive abilities of PC cells. Dual-luciferase reporter assays were used to determine how miR-92b-3p regulates Gabra3. Xenograft mouse models were used to assess the role of miR-92b-3p in PC tumor formation in vivo. RESULTS: Here, we provide evidence that miR-92b-3p acted as a tumor suppressor in PC by regulating Gabra3 expression. MiR-92b-3p expression levels were lower in PC tissues than corresponding noncancerous pancreatic (CNP) tissues and were associated with a poor prognosis in PC patients. MiR-92b-3p overexpression suppressed the proliferation and invasion of PC cells in both in vivo and in vitro models. Conversely, miR-92b-3p knockdown induced an aggressive phenotype in PC cells. Mechanistically, miR-92b-3p overexpression suppressed Gabra3 expression, which then led to the inactivation of important oncogenic pathways, including the AKT/mTOR and JNK pathways. CONCLUSION: Our results suggest that miR-92b-3p acted as a tumor suppressor by targeting Gabra3-associated oncogenic pathways; these results provide novel insight into future treatments for PC patients.

Fibroblast activation protein-sensitive polymeric nanobeacon for early diagnosis of renal fibrosis.

Early diagnosis and treatment of renal fibrosis (RF) significantly affect the clinical outcomes of chronic kidney diseases (CKDs). As the typical fibrotic ailment, RF is characterized by remodeling of the extracellular matrix, and the activation of fibroblast activation protein (FAP) plays a crucial role in the mediation of extracellular matrix protein degradation. Therefore, FAP can serve as a biomarker for RF. However, up to now, no effective tools have been reported to diagnose early-stage RF via detecting FAP. In this work, a polymeric nanobeacon integrating an FAP-sensitive amphiphilic polymer and fluorophores was proposed, which was used to diagnose early RF by sensing FAP. The FAP can be detected in the range of 0 to 200 ng/mL with a detection limit of 0.132 ng/mL. Furthermore, the fluorescence imaging results demonstrate that the polymeric nanobeacon can sensitively image fibrotic kidneys in mice with unilateral ureteral occlusion (UUO), suggesting its potential for early RF diagnosis and guidance of FAP-targeted treatments. Importantly, when employed alongside with non-invasive diagnostic techniques like magnetic resonance imaging (MRI) and serological tests, this nanobeacon exhibits excellent biocompatibility, low biological toxicity, and sustained imaging capabilities, making it a suitable fluorescent tool for diagnosing various FAP-related fibrotic conditions. To our knowledge, this study represents the first attempt to image RF in early stage by detecting FAP, offering a promising fluorescent molecular tool for diagnosing various FAP-associated diseases in the future.

A subregion-based RadioFusionOmics model discriminates between grade 4 astrocytoma and glioblastoma on multisequence MRI.

PURPOSE: To explore a subregion-based RadioFusionOmics (RFO) model for discrimination between adult-type grade 4 astrocytoma and glioblastoma according to the 2021 WHO CNS5 classification. METHODS: 329 patients (40 grade 4 astrocytomas and 289 glioblastomas) with histologic diagnosis was retrospectively collected from our local institution and The Cancer Imaging Archive (TCIA). The volumes of interests (VOIs) were obtained from four multiparametric MRI sequences (T1WI, T1WI + C, T2WI, T2-FLAIR) using (1) manual segmentation of the non-enhanced tumor (nET), enhanced tumor (ET), and peritumoral edema (pTE), and (2) K-means clustering of four habitats (H1: high T1WI + C, high T2-FLAIR; (2) H2: high T1WI + C, low T2-FLAIR; (3) H3: low T1WI + C, high T2-FLAIR; and (4) H4: low T1WI + C, low T2-FLAIR). The optimal VOI and best MRI sequence combination were determined. The performance of the RFO model was evaluated using the area under the precision-recall curve (AUPRC) and the best signatures were identified. RESULTS: The two best VOIs were manual VOI3 (putative peritumoral edema) and clustering H34 (low T1WI + C, high T2-FLAIR (H3) combined with low T1WI + C and low T2-FLAIR (H4)). Features fused from four MRI sequences ([Formula: see text]) outperformed those from either a single sequence or other sequence combinations. The RFO model that was trained using fused features [Formula: see text] achieved the AUPRC of 0.972 (VOI3) and 0.976 (H34) in the primary cohort (p = 0.905), and 0.971 (VOI3) and 0.974 (H34) in the testing cohort (p = 0.402). CONCLUSION: The performance of subregions defined by clustering was comparable to that of subregions that were manually defined. Fusion of features from the edematous subregions of multiple MRI sequences by the RFO model resulted in differentiation between grade 4 astrocytoma and glioblastoma.

Quantitative Measurement on Contrast-Enhanced CT Distinguishes Small Clear Cell Renal Cell Carcinoma From Benign Renal Tumors: A Multicenter Study.

RATIONALE AND OBJECTIVES: To evaluate the potential of quantitative measurements on contrast-enhanced CT (CECT) in differentiating small (≤4 cm) clear cell renal cell carcinoma (ccRCC) from benign renal tumors, including fat-poor angiomyolipoma (fpAML) and renal oncocytoma (RO). MATERIALS AND METHODS: 244 patients with pathologically confirmed ccRCC (n = 184) and benign renal tumors (fpAML, n = 50; RO, n = 10) were randomly assigned into training cohort (n = 193) and test cohort 1 (n = 51), while external test cohort 2 (n = 50) was from another hospital. Quantitative parameters were obtained from CECT (unenhanced phase, UP; corticomedullary phase, CMP; nephrographic phase, NP; excretory phase, EP) by measuring attenuation of renal mass and cortex and subsequently calculated. Univariable and multivariable logistic regression analyses were performed to evaluate the association between these parameters and ccRCC. Finally, the constructed models were compared with radiologists' diagnoses. RESULTS: In univariable analysis, UP-related parameters, particularly UPC-T (cortex minus tumor attenuation on UP), demonstrated AUC of 0.766 in training cohort, 0.901 in test cohort 1, 0.805 in test cohort 2. The heterogeneity-related parameter SD (standard deviation) showed AUC of 0.781, 0.834, and 0.875 respectively. In multivariable analysis, model 1 incorporating UPC-T, NPC-T (cortex minus tumor attenuation on NP), CMPT-UPT (tumor attenuation on CMP minus UP), and SD yielded AUC of 0.866, 0.923, and 0.949 respectively. When compared with radiologists, multivariate models demonstrated higher accuracy (0.800-0.860) and sensitivity (0.794-0.971) than radiologists' assessments (accuracy: 0.700-0.720, sensitivity: 0.588-0.706). CONCLUSION: Quantitative measurements on CECT, particularly UP- and heterogeneity-related parameters, have potential to discriminate ccRCC and benign renal tumors (fpAML, RO).

Nanoparticle-mediated blockade of CXCL12/CXCR4 signaling enhances glioblastoma immunotherapy: Monitoring early responses with MRI radiomics.

The limited therapeutic efficacy of checkpoint blockade immunotherapy against glioblastoma is closely related to the blood-brain barrier (BBB) and tumor immunosuppressive microenvironment, where the latter is driven primarily by tumor-associated myeloid cells (TAMCs). Targeting the C-X-C motif chemokine ligand-12/C-X-C motif chemokine receptor-4 (CXCL12/CXCR4) signaling orchestrates the recruitment of TAMCs and has emerged as a promising approach for alleviating immunosuppression. Herein, we developed an iRGD ligand-modified polymeric nanoplatform for the co-delivery of CXCR4 antagonist AMD3100 and the small-molecule immune checkpoint inhibitor BMS-1. The iRGD peptide facilitated superior BBB crossing and tumor-targeting abilities both in vitro and in vivo. In mice bearing orthotopic GL261-Luc tumor, co-administration of AMD3100 and BMS-1 significantly inhibited tumor proliferation without adverse effects. A reprogramming of immunosuppression upon CXCL12/CXCR4 signaling blockade was observed, characterized by the reduction of TAMCs and regulatory T cells, and an increased proportion of CD8+T lymphocytes. The elevation of interferon-γ secreted from activated immune cells upregulated PD-L1 expression in tumor cells, highlighting the synergistic effect of BMS-1 in counteracting the PD-1/PD-L1 pathway. Finally, our research unveiled the ability of MRI radiomics to reveal early changes in the tumor immune microenvironment following immunotherapy, offering a powerful tool for monitoring treatment responses. STATEMENT OF SIGNIFICANCE: The insufficient BBB penetration and immunosuppressive tumor microenvironment greatly diminish the efficacy of immunotherapy for glioblastoma (GBM). In this study, we prepared iRGD-modified polymeric nanoparticles, loaded with a CXCR4 antagonist (AMD3100) and a small-molecule checkpoint inhibitor of PD-L1 (BMS-1) to overcome physical barriers and reprogram the immunosuppressive microenvironment in orthotopic GBM models. In this nanoplatform, AMD3100 converted the "cold" immune microenvironment into a "hot" one, while BMS-1 synergistically counteracted PD-L1 inhibition, enhancing GBM immunotherapy. Our findings underscore the potential of dual-blockade of CXCL12/CXCR4 and PD-1/PD-L1 pathways as a complementary approach to maximize therapeutic efficacy for GBM. Moreover, our study revealed that MRI radiomics provided a clinically translatable means to assess immunotherapeutic efficacy.

Integrated Diffusion Tensor Imaging and Renal Parenchymal Volume for Early Detection and Grading of Split Renal Functional Impairment in Lupus Nephritis.

RATIONALE AND OBJECTIVES: To investigate the effectiveness of combining split diffusion tensor imaging (DTI) measurements with split renal parenchymal volume (RPV) for assessing split renal functional impairment in patients with lupus nephritis (LN). MATERIALS AND METHODS: Seventy-four participants [48 LN patients and 26 healthy volunteers (HV)] were included in the study. All participant underwent conventional MR and DTI (b = 0, 400, and 600 s/mm2) examinations using a 3.0 T MRI scanner to determine the split renal DTI measurements and split RPV. In LN patients, renography glomerular filtration rate (rGFR) was measured using 99mTc-DTPA scintigraphy based on Gates' method, serving as the reference standard to categorize all split kidneys of LN patients into LN with mild impairment (LNm, n = 65 kidneys) and LN with moderate to severe (LNms, n = 31 kidneys) groups according to the threshold of 30 ml/min in spilt rGFR. All statistical analyses were performed using SPSS 25.0 and MedCalc 20.0 software packages. RESULTS: Only split medullary fractional anisotropy (FA) and the product of split medullary FA and RPV could distinguish pairwise subgroups among the HV and each LN subgroup (all p < 0.05). ROC curve analysis demonstrated that split medullary FA (AUC = 0.866) significantly outperformed other parameters in differentiating HV from LNm groups, while the product of split medullary FA and split RPV was superior in distinguishing LNm and LNms groups (AUC = 0.793) than other parameters. The combination of split medullary FA and split RPV showed best correlation with split rGFR (r = 0.534, p < 0.001). CONCLUSION: Split medullary FA, and its combination with split RPV, are valuable biomarkers for detecting early functional changes in renal alterations and predicting disease progression in patients with LN.