3D genomic mapping reveals multifocality of human pancreatic precancers.

Pancreatic intraepithelial neoplasias (PanINs) are the most common precursors of pancreatic cancer, but their small size and inaccessibility in humans make them challenging to study1. Critically, the number, dimensions and connectivity of human PanINs remain largely unknown, precluding important insights into early cancer development. Here, we provide a microanatomical survey of human PanINs by analysing 46 large samples of grossly normal human pancreas with a machine-learning pipeline for quantitative 3D histological reconstruction at single-cell resolution. To elucidate genetic relationships between and within PanINs, we developed a workflow in which 3D modelling guides multi-region microdissection and targeted and whole-exome sequencing. From these samples, we calculated a mean burden of 13 PanINs per cm3 and extrapolated that the normal intact adult pancreas harbours hundreds of PanINs, almost all with oncogenic KRAS hotspot mutations. We found that most PanINs originate as independent clones with distinct somatic mutation profiles. Some spatially continuous PanINs were found to contain multiple KRAS mutations; computational and in situ analyses demonstrated that different KRAS mutations localize to distinct cell subpopulations within these neoplasms, indicating their polyclonal origins. The extensive multifocality and genetic heterogeneity of PanINs raises important questions about mechanisms that drive precancer initiation and confer differential progression risk in the human pancreas. This detailed 3D genomic mapping of molecular alterations in human PanINs provides an empirical foundation for early detection and rational interception of pancreatic cancer.

Analysis of the differential expression of serum miR-21-5p, miR-135-5p, and miR-155-5p by Bifidobacterium triplex viable capsules during the perioperative stage of colorectal cancer.

OBJECTIVE: In this study, we investigated the impact of perioperative administration of Bifidobacterium triplex viable capsules on the serum levels of circulating miR-21-5p, miR-135-5p, and miR-155-5p in patients with colorectal cancer (CRC). The purpose of this study is to provide a foundation for future research on the use of Bifidobacterium triplex viable capsules to enhance postoperative recovery in patients with CRC. METHODS: A total of 60 patients with primary CRC admitted to the Department of General Surgery at Shanxi Bethune Hospital between June 2020 and December 2020 were selected and randomly divided into two groups: 20 cases in the control group and 40 cases in the experimental group. The experimental group was administered oral Bifidobacterium triplex viable capsules during the perioperative period, while the control group was administered oral placebo. Before and after the perioperative period, the expression levels of miR-21-5p, miR-135-5p, and miR-155-5p were compared in the serum of both groups of patients. Furthermore, we established the prognostic value of these three miRNAs in CRC patients. RESULTS: After surgery, the expression levels of miR-21-5p, miR-135-5p, and miR-155-5p decreased in both groups of patients (P < 0.05). Significantly greater differences were observed between miR-21-5p and miR-135-5p (P < 0.001). Expression levels of serum miR-21-5p (P = 0.020) and miR-135-5p (P = 0.023) decreased significantly more in the experimental group than in the control group. The levels of the above three miRNAs after surgery did not correlate with 3-year OS (HR = 4.21; 95% CI 0.37-47.48; log-rank P = 0.20) or 3-year DFS (HR = 1.57; 95% CI 0.32-7.66; log-rank P = 0.55) in two groups. CONCLUSION: Radical surgery reduces the levels of serum miR-21-5p, miR-135-5p, and miR-155-5p expression in patients with CRC. The use of Bifidobacterium triplex viable capsules assists in achieving quicker perioperative recovery from radical surgery in CRC patients, and this underlying mechanism may be associated with the regulation of serum miR-21-5p, miR-135-5p, and miR-155-5p expression levels.

Virtual formalin-fixed and paraffin-embedded staining of fresh brain tissue via stimulated Raman CycleGAN model.

Intraoperative histology is essential for surgical guidance and decision-making. However, frozen-sectioned hematoxylin and eosin (H&E) staining suffers from degraded accuracy, whereas the gold-standard formalin-fixed and paraffin-embedded (FFPE) H&E is too lengthy for intraoperative use. Stimulated Raman scattering (SRS) microscopy has shown rapid histology of brain tissue with lipid/protein contrast but is challenging to yield images identical to nucleic acid-/protein-based FFPE stains interpretable to pathologists. Here, we report the development of a semi-supervised stimulated Raman CycleGAN model to convert fresh-tissue SRS images to H&E stains using unpaired training data. Within 3 minutes, stimulated Raman virtual histology (SRVH) results that matched perfectly with true H&E could be generated. A blind validation indicated that board-certified neuropathologists are able to differentiate histologic subtypes of human glioma on SRVH but hardly on conventional SRS images. SRVH may provide intraoperative diagnosis superior to frozen H&E in both speed and accuracy, extendable to other types of solid tumors.

Tailoring the Electronic Metal-Support Interactions in Supported Silver Catalysts through Al modification for Efficient Ethylene Epoxidation.

Metal-modified catalysts have attracted extraordinary research attention in heterogeneous catalysis due to their enhanced geometric and electronic structures and outstanding catalytic performances. Silver (Ag) possesses necessary active sites for ethylene epoxidation, but the catalyst activity is usually sacrificed to obtain high selectivity towards ethylene oxide (EO). Herein, we report that using Al can help in tailoring the unoccupied 3d state of Ag on the MnO2 support through strong electronic metal-support interactions (EMSIs), overcoming the activity-selectivity trade-off for ethylene epoxidation and resulting in a very high ethylene conversion rate (~100 %) with 90 % selectivity for EO under mild conditions (170 °C and atmospheric pressure). Structural characterization and theoretical calculations revealed that the EMSIs obtained by the Al modification tailor the unoccupied 3d state of Ag, modulating the adsorption of ethylene (C2H4) and oxygen (O2) and facilitating EO desorption, resulting in high C2H4 conversion. Meanwhile, the increased number of positively charge Ag+ lowers the energy barrier for C2H4(ads) oxidation to produce oxametallacycle (OMC), inducing the unexpectedly high EO selectivity. Such an extraordinary electronic promotion provides new promising pathways for designing advanced metal catalysts with high activity and selectivity in selective oxidation reactions.

Presurgical Medical Treatment in Prolactinomas: Surgical Implications and Pathological Characteristics From 290 Cases.

OBJECTIVE: To review experience regarding the treatment of prolactinomas by endoscopic endonasal surgery focusing on the association between presurgical dopamine agonist (DA) treatment and perioperative outcomes, surgical morbidities, endocrine outcomes, and pathological characteristics. METHODS: A single-center series of 290 cases was analyzed retrospectively and clinical data were collected. Intratumoral collagen content was assessed by Masson trichrome staining. RESULTS: Tenacious tumor consistency (27.8% vs 9.8%, P < .001) was more common in DA-pretreated patients compared with patients who underwent initial surgery. Moreover, DA-pretreated macroadenomas presented more intraoperative blood loss (200 [100-400] mL vs 175 [100-300] mL; P = .014), longer surgical duration (177 ± 95 minutes vs 154 ± 57 minutes; P = .043), and more surgical morbidities (19.4% vs 8.9%; P = .034). Additionally, DA-pretreated macroadenomas presented a higher collagen volume fraction than that of the initial surgery group (23.6 ± 2.2% vs 13.2 ± 2.1%; P = .001). Correlation analysis revealed a close correlation between collagen volume fraction and the cumulative dose of bromocriptine (BRC) in macroadenomas (r = 0.438, P < .001). Regarding endocrine outcomes, DA-pretreated microadenomas showed a lower proportion of initial remission compared with patients who underwent initial surgery (86.7% vs 100%, P = .047). CONCLUSION: This study described increased surgical difficulty and inferior endocrine outcomes associated with tumor fibrosis secondary to presurgical BRC treatment in prolactinomas. Neurosurgeons should note that presurgical BRC treatment may render subsequent surgery more challenging.

A Convolutional Neural Network Model for Distinguishing Hemangioblastomas From Other Cerebellar-and-Brainstem Tumors Using Contrast-Enhanced MRI.

BACKGROUND: Hemangioblastoma (HB) is a highly vascularized tumor most commonly occurring in the posterior cranial fossa, requiring accurate preoperative diagnosis to avoid accidental intraoperative hemorrhage and even death. PURPOSE: To accurately distinguish HBs from other cerebellar-and-brainstem tumors using a convolutional neural network model based on a contrast-enhanced brain MRI dataset. STUDY TYPE: Retrospective. POPULATION: Four hundred five patients (182 = HBs; 223 = other cerebellar-and brainstem tumors): 305 cases for model training, and 100 for evaluation. FIELD STRENGTH/SEQUENCE: 3 T/contrast-enhanced T1-weighted imaging (T1WI + C). ASSESSMENT: A CNN-based 2D classification network was trained by using sliced data along the z-axis. To improve the performance of the network, we introduced demographic information, various data-augmentation methods and an auxiliary task to segment tumor region. Then, this method was compared with the evaluations performed by experienced and intermediate-level neuroradiologists, and the heatmap of deep feature, which indicates the contribution of each pixel to model prediction, was visualized by Grad-CAM for analyzing the misclassified cases. STATISTICAL TESTS: The Pearson chi-square test and an independent t-test were used to test for distribution difference in age and sex. And the independent t-test was exploited to evaluate the performance between experts and our proposed method. P value <0.05 was considered significant. RESULTS: The trained network showed a higher accuracy for identifying HBs (accuracy = 0.902 ± 0.031, F1 = 0.891 ± 0.035, AUC = 0.926 ± 0.040) than experienced (accuracy = 0.887 ± 0.013, F1 = 0.868 ± 0.011, AUC = 0.881 ± 0.008) and intermediate-level (accuracy = 0.827 ± 0.037, F1 = 0.768 ± 0.068, AUC = 0.810 ± 0.047) neuroradiologists. The recall values were 0.910 ± 0.050, 0.659 ± 0.084, and 0.828 ± 0.019 for the trained network, intermediate and experienced neuroradiologists, respectively. Additional ablation experiments verified the utility of the introduced demographic information, data augmentation, and the auxiliary-segmentation task. DATA CONCLUSION: Our proposed method can successfully distinguish HBs from other cerebellar-and-brainstem tumors and showed diagnostic efficiency comparable to that of experienced neuroradiologists. EVIDENCE LEVEL: 3 TECHNICAL EFFICACY: Stage 2.

MRI-derived radiomics assessing tumor-infiltrating macrophages enable prediction of immune-phenotype, immunotherapy response and survival in glioma.

BACKGROUND: The tumor immune microenvironment can influence the prognosis and treatment response to immunotherapy. We aimed to develop a non-invasive radiomic signature in high-grade glioma (HGG) to predict the absolute density of tumor-associated macrophages (TAMs), the preponderant immune cells in the microenvironment of HGG. We also aimed to evaluate the association between the signature, and tumor immune phenotype as well as response to immunotherapy. METHODS: In this retrospective setting, total of 379 patients with HGG from three independent cohorts were included to construct a radiomic model named Radiomics Immunological Biomarker (RIB) for predicting the absolute density of M2-like TAM using the mRMR feature ranking method and LASSO classifier. Among them, 145 patients from the TCGA microarray cohort were randomly allocated into a training set (N=101) and an internal validation set (N=44), while the immune-phenotype cohort (N=203) and the immunotherapy-treated cohort (N=31, patients from a prospective clinical trial treated with DC vaccine) recruited from Huashan Hospital were used as two external validation sets. The immunotherapy-treated cohort was also used to evaluate the relationship between RIB and immunotherapy response. Radiogenomic analysis was performed to find functional annotations using RNA sequencing data from TAM cells. RESULTS: An 11-feature radiomic model for M2-like TAM was developed and validated in four datasets of HGG patients (area under the curve = 0.849, 0.719, 0.674, and 0.671) using MRI images of post contrast enhanced T1-weighted (T1CE). Patients with high RIB scores had a strong inflammatory response. Four hub-genes (SLC7A7, RNASE6, HLA-DRB1 and CD300A) expressed by TAM were identified to be closely related to the RIB, providing important evidence for biological interpretation. Only individuals with a high RIB score were shown to have survival benefits from DC vaccine [DC vaccine vs. Placebo: median progression-free survival (mPFS), 10.0 mos vs. 4.5 mos, HR=0.17, P=0.0056, 95%CI=0.041-0.68; median overall survival (mOS), 15.0 mos vs. 7.0 mos, HR=0.17, P =0.0076, 95%CI=0.04-0.68]. Multivariate analyses also confirmed that treatment by DC vaccine was an independent factor for improved survival in the high RIB score group. However, in the low RIB score group, DC vaccine was not associated with improved survival. Furthermore, a radiomic nomogram based on the RIB score and clinical factors could efficiently predict the 1-, 2-, and 3-year survival rates, as confirmed by ROC curve analysis (AUC for 1-, 2- and 3-year survival: 0.705, 0.729 and 0.684, respectively). CONCLUSIONS: The radiomic model could allow for non-invasive assessment of the absolute density of TAM from MRI images in HGG patients. Of note, our RIB model is the first immunological radiomic model confirmed to have the ability to predict survival benefits from DC vaccine in gliomas, thereby providing a novel tool to inform treatment decisions and monitor patient treatment course by radiomics.

The development of a combined clinico-radiomics model for predicting post-operative recurrence in atypical meningiomas: a multicenter study.

PURPOSE: Atypical meningiomas could manifest early recurrence after surgery and even adjuvant radiotherapy. We aimed to construct a clinico-radiomics model to predict post-operative recurrence of atypical meningiomas based on clinicopathological and radiomics features. MATERIALS AND METHODS: The study cohort was comprised of 224 patients from two neurosurgical centers. 164 patients from center I were divided to the training cohort for model development and the testing cohort for internal validation. 60 patients from center II were used for external validation. Clinicopathological characteristics, radiological semantic, and radiomics features were collected. A radiomic signature was comprised of four radiomics features. A clinico-radiomics model combining the radiomics signature and clinical characteristics was constructed to predict the recurrence of atypical meningiomas. RESULTS: 1920 radiomics features were extracted from the T1 Contrast and T2-FLAIR sequences of patients in center I. The radiomics signature was able to differentiate post-operative patients into low-risk and high-risk groups based on tumor recurrence (P < 0.001). A clinic-radiomics model was established by combining age, extent of resection, Ki-67 index, surgical history and the radiomics signature for recurrence prediction in atypical meningiomas. The model achieved a good prediction performance with the integrated AUC of 0.858 (0.802-0.915), 0.781 (0.649-0.912) and 0.840 (0.747-0.933) in the training, internal validation and external validation cohort, respectively. CONCLUSIONS: The present study established a radiomics signature and a clinico-radiomics model with a favorable performance in predicting tumor recurrence for atypical meningiomas.

Initial screening for occult congenital ectopia lentis based on ocular biological parameters in preschool children.

BACKGROUND: This study aimed to identify an initial screening tool for congenital ectopia lentis (CEL) by comparing ocular biological parameters in children with myopia. METHODS: A retrospective case-control study was conducted at one tertiary referral centre, from October 2020 to June 2022. Axial length (AL), corneal curvature (CC), refractive astigmatism (RA), corneal astigmatism (CA), internal astigmatism (IA), the difference between the axis of RA and CA [AXIS(RA-CA)], white-to-white corneal diameter (WTW), and axial length-corneal radius ratio (AL/CR) were compared in 28 eyes of CEL patients, and 60 eyes of myopic patients matched for age and refraction. The spherical equivalent of each eye was < -3.00 D. Area under the curve (AUC) of the receiver operating characteristic curves were calculated. RESULTS: The differences in RA, AL, mean keratometry (Kmed), maximum keratometry (Kmax), minimum keratometry (Kmin), CA, IA, AXIS(RA-CA), WTW, and AL/CR between the CEL and myopic groups were statistically significant (p < 0.05; p < 0.001; p < 0.001; p < 0.001; p < 0.001; p < 0.05; p < 0.001; p < 0.001; p < 0.001; p < 0.001, respectively). In logistic regression analysis RA, IA, AXIS(RA-CA), and AL/CR were significantly associated with CEL (p < 0.05). AUCs for RA, IA, AXIS(RA-CA), and AL/CR were 0.694, 0.853, 0.814, and 0.960, respectively. AUCs for AL/CR in SE< -6.00 D subgroup was 0.970, and 0.990 in -6.00 D ≤ SE < -3.00 D group. An AL/CR < 3.024 was the optimal cut-off point differentiating the CEL and control groups (sensitivity, 92.9%; specificity, 88.30%). CONCLUSIONS: A smaller AL/CR could identify CEL in children with myopia. An AL/CR cut-off value of 3.024 may be the most sensitive and specific parameter for the differential diagnosis of CEL in patients with mild to high myopia.

CBX7 reprograms metabolic flux to protect against meningioma progression by modulating the USP44/c-MYC/LDHA axis.

Meningioma is one of the most common primary neoplasms in the central nervous system, whereas there is still no specific molecularly targeted therapy that has been approved for the clinical treatment of aggressive meningiomas. There is therefore an urgent demand to decrypt the biological and molecular landscape of malignant meningioma. Here, through the in-silica prescreening and 10-year follow-up of 445 meningioma patients, we uncovered that CBX7 is progressively decreased with malignancy grade and neoplasia stage in meningioma and a high CBX7 expression level predicts a favorable prognosis in meningioma patients. CBX7 restoration significantly induces cell cycle arrest and inhibits meningioma cell proliferation. iTRAQ-based proteomics analysis indicated that CBX7 restoration triggers the metabolic shift from glycolysis to oxidative phosphorylation. The mechanistic study demonstrated that CBX7 promotes the proteasome-dependent degradation of c-MYC proteins by transcriptionally inhibiting the expression of a c-MYC deubiquitinase, USP44, which attenuates c-MYC-mediated transactivation of LDHA transcripts and further inhibits glycolysis and subsequent cellular proliferation. More importantly, the functional role of CBX7 was further confirmed in both subcutaneous and orthotopic meningioma xenografts mouse models and human meningioma patients. Together, our results shed light on the critical role of CBX7 during meningioma malignancy progression and identified the CBX7/USP44/c-MYC/LDHA axis as a promising therapeutic target against meningioma progression.

Predicting meningioma grades and pathologic marker expression via deep learning.

OBJECTIVES: To establish a deep learning (DL) model for predicting tumor grades and expression of pathologic markers of meningioma. METHODS: A total of 1192 meningioma patients from two centers who underwent surgical resection between September 2018 and December 2021 were retrospectively included. The pathological data and post-contrast T1-weight images for each patient were collected. The patients from institute I were subdivided into training, validation, and testing sets, while the patients from institute II served as the external testing cohort. The fine-tuned ResNet50 model based on transfer learning was adopted to classify WHO grade in the whole cohort and predict Ki-67 index, H3K27me3, and progesterone receptor (PR) status of grade 1 meningiomas. The predictive performance was evaluated by the accuracy and loss curve, confusion matrix, receiver operating characteristic curve (ROC), and area under curve (AUC). RESULTS: The DL prediction model for each label achieved high predictive performance in two cohorts. For WHO grade prediction, the area under the curve (AUC) was 0.966 (95%CI 0.957-0.975) in the internal testing set and 0.669 (95%CI 0.643-0.695) in the external validation cohort. The AUC in predicting Ki-67 index, H3K27me3, and PR status were 0.905 (95%CI 0.895-0.915), 0.773 (95%CI 0.760-0.786), and 0.771 (95%CI 0.750-0.792) in the internal testing set and 0.591 (95%CI 0.562-0.620), 0.658 (95%CI 0.648-0.668), and 0.703 (95%CI 0.674-0.732) in the external validation cohort, respectively. CONCLUSION: DL models can preoperatively predict meningioma grades and pathologic marker expression with favorable predictive performance. CLINICAL RELEVANCE STATEMENT: Our DL model could predict meningioma grades and expression of pathologic markers and identify high-risk patients with WHO grade 1 meningioma, which would suggest a more aggressive operative intervention preoperatively and a more frequent follow-up schedule postoperatively. KEY POINTS: WHO grades and some pathologic markers of meningioma were associated with therapeutic strategies and clinical outcomes. A deep learning-based approach was employed to develop a model for predicting meningioma grades and the expression of pathologic markers. Preoperative prediction of meningioma grades and the expression of pathologic markers was beneficial for clinical decision-making.

Digital image analysis allows objective stratification of patients with silent PIT1-lineage pituitary neuroendocrine tumors.

Studies describing the clinical presentation and prognosis of patients with silent PIT1 (pituitary specific transcription factor)-lineage pituitary neuroendocrine tumors (PitNETs) are rare. We identified patients with positive PIT1 tumor staining but without evidence of hormone hypersecretion at a tertiary center. Clusters were obtained according to cell morphology and immunostaining from each patient's digitally segmented whole slide image. We compared the clinical presentations, radiological features, and prognoses of the different clusters. We identified 146 patients (68 male, 42.9 ± 14.1 years old) with silent PIT1-lineage PitNETs. Morphology clustering suggested that tumors with large nuclei and apparent eccentricity were associated with a higher proportion of aggressiveness and a higher hazard of recurrence [hazard ratio (HR): 2.64, (95% CI, 1.06-6.55), p = 0.037]. Immunohistochemical clustering suggested that tumors with thyroid stimulating hormone (TSH) staining or all negative PIT1-lineage hormones were associated with a higher proportion of aggressiveness and a higher risk of recurrence [HR: 12.4, (95% CI, 1.60-93.5), p = 0.015]. We obtained three-tier risk profiles by combining morphological and immunohistochemical clustering. Patients with the high-risk profile presented the highest recurrence rate compared with those in the medium-risk and low-risk profiles [HR: 3.54, (95% CI, 1.40-8.93), p = 0.002]. In conclusion, digital image analysis based on cell morphology and immunohistochemical staining allows objective stratification of patients with silent PIT1-lineage tumors. Typical morphological characteristics of high-risk tumors are large tumor nuclei and high eccentricity, and typical immunostaining characteristics are TSH staining or negative staining for all PIT1-lineage hormones.

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2.

Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co3Sn2S2, we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co3Sn2S2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co3Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co3Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

Deep Learning-Assisted Quantitative Susceptibility Mapping as a Tool for Grading and Molecular Subtyping of Gliomas.

This study aimed to explore the value of deep learning (DL)-assisted quantitative susceptibility mapping (QSM) in glioma grading and molecular subtyping. Forty-two patients with gliomas, who underwent preoperative T2 fluid-attenuated inversion recovery (T2 FLAIR), contrast-enhanced T1-weighted imaging (T1WI + C), and QSM scanning at 3.0T magnetic resonance imaging (MRI) were included in this study. Histopathology and immunohistochemistry staining were used to determine glioma grades, and isocitrate dehydrogenase (IDH) 1 and alpha thalassemia/mental retardation syndrome X-linked gene (ATRX) subtypes. Tumor segmentation was performed manually using Insight Toolkit-SNAP program (www.itksnap.org). An inception convolutional neural network (CNN) with a subsequent linear layer was employed as the training encoder to capture multi-scale features from MRI slices. Fivefold cross-validation was utilized as the training strategy (seven samples for each fold), and the ratio of sample size of the training, validation, and test dataset was 4:1:1. The performance was evaluated by the accuracy and area under the curve (AUC). With the inception CNN, single modal of QSM showed better performance in differentiating glioblastomas (GBM) and other grade gliomas (OGG, grade II-III), and predicting IDH1 mutation and ATRX loss (accuracy: 0.80, 0.77, 0.60) than either T2 FLAIR (0.69, 0.57, 0.54) or T1WI + C (0.74, 0.57, 0.46). When combining three modalities, compared with any single modality, the best AUC/accuracy/F1-scores were reached in grading gliomas (OGG and GBM: 0.91/0.89/0.87, low-grade and high-grade gliomas: 0.83/0.86/0.81), predicting IDH1 mutation (0.88/0.89/0.85), and predicting ATRX loss (0.78/0.71/0.67). As a supplement to conventional MRI, DL-assisted QSM is a promising molecular imaging method to evaluate glioma grades, IDH1 mutation, and ATRX loss. Supplementary Information: The online version contains supplementary material available at 10.1007/s43657-022-00087-6.

Multi-b-value diffusion stretched-exponential model parameters correlate with MIB-1 and CD34 expression in Glioma patients, an intraoperative MR-navigated, biopsy-based histopathologic study.

Background: To understand the pathological correlations of multi-b-value diffusion-weighted imaging (MDWI) stretched-exponential model (SEM) parameters of α and diffusion distribution index (DDC) in patients with glioma. SEM parameters, as promising biomarkers, played an important role in histologically grading gliomas. Methods: Biopsy specimens were grouped as high-grade glioma (HGG) or low-grade glioma (LGG). MDWI-SEM parametric mapping of DDC1500, α1500 fitted by 15 b-values (0-1,500 sec/mm2)and DDC5000 and α5000 fitted by 22 b-values (0-5,000 sec/mm2) were matched with pathological samples (stained by MIB-1 and CD34) by coregistered localized biopsies, and all SEM parameters were correlated with these pathological indices pMIB-1(percentage of MIB-1 expression positive rate) and CD34-MVD (CD34 expression positive microvascular density for each specimen). The two-tailed Spearman's correlation was calculated for pathological indexes and SEM parameters, as well as WHO grades and SEM parameters. Results: MDWI-derived α1500 negatively correlated with CD34-MVD in both LGG (6 specimens) and HGG (26 specimens) (r=-0.437, P =0.012). MDWI-derived DDC1500 and DDC5000 negatively correlated with MIB-1 expression in all glioma patients (P<0.05). WHO grades negatively correlated with α1500(r=-0.485; P=0.005) and α5000(r=-0.395; P=0.025). Conclusions: SEM-derived DDC and α are significant in histologically grading gliomas, DDC may indicate the proliferative ability, and CD34 stained microvascular perfusion may be an important determinant of water diffusion inhomogeneity α in glioma.

Histopathological auxiliary system for brain tumour (HAS-Bt) based on weakly supervised learning using a WHO CNS5-style pipeline.

PURPOSE: Classification and grading of central nervous system (CNS) tumours play a critical role in the clinic. When WHO CNS5 simplifies the histopathology diagnosis and places greater emphasis on molecular pathology, artificial intelligence (AI) has been widely used to meet the increased need for an automatic histopathology scheme that could liberate pathologists from laborious work. This study was to explore the diagnosis scope and practicality of AI. METHODS: A one-stop Histopathology Auxiliary System for Brain tumours (HAS-Bt) is introduced based on a pipeline-structured multiple instance learning (pMIL) framework developed with 1,385,163 patches from 1038 hematoxylin and eosin (H&E) slides. The system provides a streamlined service including slide scanning, whole-slide image (WSI) analysis and information management. A logical algorithm is used when molecular profiles are available. RESULTS: The pMIL achieved an accuracy of 0.94 in a 9-type classification task on an independent dataset composed of 268 H&E slides. Three auxiliary functions are developed and a built-in decision tree with multiple molecular markers is used to automatically formed integrated diagnosis. The processing efficiency was 443.0 s per slide. CONCLUSION: HAS-Bt shows outstanding performance and provides a novel aid for the integrated neuropathological diagnostic workflow of brain tumours using CNS 5 pipeline.

Ectopic recurrence craniopharyngioma: series report and literature review.

BACKGROUND: Craniopharyngioma is a common intracranial tumor located in the sellar-suprasellar region. Due to the involvement of adjacent structures, it can lead to increased intracranial pressure, visual impairment, and endocrine deficiencies. Surgical resection is the primary treatment, but it is a tough challenge to achieve total resection, which will led to the frequency of recurrences and progressions. Among them, distant spread is extremely rare, but important complication, identifying and providing proper therapy, is crucial. METHODS: We report two cases of ectopic recurrence craniopharyngioma and make a literature review for the published similar case reports. RESULTS: Our literature review revealed 63 cases (including our patient). The onset age in children group and adult group ranges from 2-14 years old (6.70 ± 3.33) to 17-73 years old (40.63 ± 15.58), while the interval year between tumor initiation and ectopic recurrence ranges from 0.17-20 (7.28 ± 6.76) years to 0.3-34 (6.85 ± 7.29). Achieving gross total resection seems not to prevent the ectopic recurrence. The major pathology of ectopic recurrence craniopharyngioma is adamantinomatous type. The most common site of ectopic recurrence is frontal lobe. According to the pathogenesis, 35 cases were seeding along the surgical approach, and 28 cases were seeding via the CSF pathway. CONCLUSION: Ectopic recurrence craniopharyngioma is rare, but it can lead to serious symptoms. Delicate surgical procedure can help to reduce the risk of ectopic recurrence, and standardized follow-up can provide valuable information for treatment.

Refractive status and retinal morphology in children with a history of intravitreal ranibizumab for retinopathy of prematurity.

This study investigated the characteristics of refractive status, visual acuity, and retinal morphology in children with a history of receiving intravitreal ranibizumab for retinopathy of prematurity (ROP). Children 4-6 years of age were enrolled and divided into the following four groups: group 1, children with a history of ROP who had been treated with intravitreal ranibizumab; group 2, children with a history of ROP who had not received any treatment; group 3, premature children without ROP; and group 4, full-term children. Refractive status, peripapillary retinal nerve fiber layer (RNFL), and macular thickness were measured. A total of 204 children were enrolled. In group 1, myopic shift was not noted, but poorer best corrected visual acuity (BCVA) and shorter axial length were observed. Significantly lower peripapillary RNFL thickness in the average total and superior quadrant, higher central subfield thickness, lower parafoveal retinal thickness in average total, superior, and nasal and temporal quadrants were observed in group 1 than in the other groups. The poor BCVA in patients with ROP was correlated with the lower RNFL thickness in the superior quadrant.   Conclusion: Children with a history of type 1 ROP treated with ranibizumab did not show a myopic shift but did show abnormal retinal morphology and the poorest BCVA among all groups. We suggest that pediatric ophthalmologists should always pay attention to visual development in patients with ROP with a history of intravitreal ranibizumab. What is Known: • Anti-VEGF is efficiently and widely used in the treatment of type 1 retinopathy of prematurity (ROP), and different anti-VEGF agents are associated with different prevalence of myopia. • Patients with ROP who receive treatment such as laser therapy or cryotherapy have abnormal macular development and retinal nerve fiber layer (RNFL) thickness. What is New: • Children with a history of ROP treated with intravitreal ranibizumab did not show a myopic shift but did show poor BCVA at 4-6 years of age. • Abnormal macular morphology and lower peripapillary RNFL thickness were found in these children.

Correlations between intravoxel incoherent motion-derived fast diffusion and perfusion fraction parameters and VEGF- and MIB-1-positive rates in brain gliomas: an intraoperative MR-navigated, biopsy-based histopathologic study.

OBJECTIVES: To explore the correlations between histopathologic findings and intravoxel incoherent motion (IVIM)-derived perfusion and diffusion parameters in brain gliomas. METHODS: Thirty-two biopsy samples from twenty-one patients with newly diagnosed gliomas from a previous prospective cohort study were retrospectively analyzed. All patients underwent diffusion-weighted MRI with 22 b values (0-5000 s/mm2), followed by intraoperative MR-guided biopsy surgery and surgical resection. All 32 biopsy samples underwent immunohistochemical staining followed by quantitative analysis of cell density (cellularity), percent of MIB-1 (Ki67)-positive expression (pMIB-1), number of CD34-stained vessels (CD34-MVD), and percent of VEGF-positive expressing cells (pVEGF) using a multispectral phenotyping microscope. Based on the co-registered localized biopsy, correlation analysis was performed between the IVIM-derived biexponential model-based parameters (Dfast1500 and Dfast5000, Dslow1500 and Dslow5000, PF1500 and PF5000) and the above four pathological biomarkers and glioma grades. RESULTS: Significant positive correlations were revealed between Dfast5000 and pVEGF (rho (r) = 0.466, p = 0.007), and Dfast1500 and pVEGF (r = 0.371, p = 0.037). A significant negative correlation was revealed between PF5000 with pMIB-1 (r = - 0.456, p = 0.01). Moderate to good positive correlations were shown between Dfast5000 and glioma grades (r = 0.509, p = 0.003) and Dfast1500 and glioma grades (r = 0.476, p = 0.006). CONCLUSIONS: IVIM-DWI-derived Dfast and PF correlate, respectively, with intratumor pVEGF and pMIB-1. When using the wide-high b value scheme, IVIM-derived Dfast and PF tend to demonstrate better efficacy in evaluating malignancy-related characteristics such as angiogenesis and cellular proliferation in gliomas. KEY POINTS: • Intravoxel incoherent motion-diffusion-weighted imaging (IVIM-DWI)-derived fast diffusion (Dfast) and perfusion fraction (PF) can quantitatively reflect intratumor pVEGF and pMIB-1. • IVIM-DWI-derived Dfast and PF tend to demonstrate better efficacy in evaluating glioma malignancy when an optimized scheme is used. • IVIM-DWI-derived Dfast5000 and PF5000 are promising non-invasive parameters correlating with pVEGF and pMIB-1 in gliomas.

Three-dimensional genomic mapping of human pancreatic tissue reveals striking multifocality and genetic heterogeneity in precancerous lesions.

Pancreatic intraepithelial neoplasia (PanIN) is a precursor to pancreatic cancer and represents a critical opportunity for cancer interception. However, the number, size, shape, and connectivity of PanINs in human pancreatic tissue samples are largely unknown. In this study, we quantitatively assessed human PanINs using CODA, a novel machine-learning pipeline for 3D image analysis that generates quantifiable models of large pieces of human pancreas with single-cell resolution. Using a cohort of 38 large slabs of grossly normal human pancreas from surgical resection specimens, we identified striking multifocality of PanINs, with a mean burden of 13 spatially separate PanINs per cm3 of sampled tissue. Extrapolating this burden to the entire pancreas suggested a median of approximately 1000 PanINs in an entire pancreas. In order to better understand the clonal relationships within and between PanINs, we developed a pipeline for CODA-guided multi-region genomic analysis of PanINs, including targeted and whole exome sequencing. Multi-region assessment of 37 PanINs from eight additional human pancreatic tissue slabs revealed that almost all PanINs contained hotspot mutations in the oncogene KRAS, but no gene other than KRAS was altered in more than 20% of the analyzed PanINs. PanINs contained a mean of 13 somatic mutations per region when analyzed by whole exome sequencing. The majority of analyzed PanINs originated from independent clonal events, with distinct somatic mutation profiles between PanINs in the same tissue slab. A subset of the analyzed PanINs contained multiple KRAS mutations, suggesting a polyclonal origin even in PanINs that are contiguous by rigorous 3D assessment. This study leverages a novel 3D genomic mapping approach to describe, for the first time, the spatial and genetic multifocality of human PanINs, providing important insights into the initiation and progression of pancreatic neoplasia.