The prognostic role of 18F-FDG PET/CT-based response evaluation in children with stage 4 neuroblastoma.

OBJECTIVES: To evaluate the association between metabolic response on 18F-FDG PET/CT and long-term survival in children with neuroblastoma (NB). METHODS: A total of 39 consecutive children with newly diagnosed stage 4 NB undergoing both 18F-FDG PET/CT imaging at baseline and after chemotherapy were retrospectively analyzed. The associations between metabolic parameters, including SUVmax of the lesion with the most intense 18F-FDG uptake at baseline (SUVb), after chemotherapy (SUVe), and the percentage change between SUVb and SUVe, and long-term survival were evaluated. RESULTS: With a median follow-up of 56 months, 22 patients who had achieved complete resolution on PET (no residual 18F-FDG uptake higher than the surrounding backgrounds) after chemotherapy had superior 5-year overall survival (OS) (73.6% vs. 39.0%, p = 0.044). SUVb > 6.9 indicated significantly poorer 5-year event-free survival (EFS) (12.5% vs. 59.3%, p = 0.005), as did SUVe > 1.2 (18.8% vs. 41.7%, p = 0.041). Children with SUVe > 1.2 had shorter 5-year OS (33.9% vs. 75.0%, p = 0.018). Multivariate analysis identified SUVe > 1.2 as an independent predictor for both EFS [hazard ratio (HR), 3.479, 95% CI, 1.381-8.761, p = 0.008] and OS (HR, 6.948, 95% CI, 1.663-29.025, p = 0.008), while SUVb > 6.9 was a predictor for EFS (HR, 2.889, 95% CI, 1.064-7.842, p = 0.037). Among 11 children with both SUVb > 6.9 and SUVe > 1.2, all experienced disease progression or relapse within 2 years since diagnosis. CONCLUSION: 18F-FDG PET/CT could be of useful to evaluate treatment response in children with stage 4 NB. CLINICAL RELEVANCE STATEMENT: 18F-FDG PET/CT after chemotherapy exhibits prognostic significance in neuroblastoma and holds potential as an alternative imaging modality for response evaluation, especially in cases with metaiodobenzylguanidine-nonavid or persistent avid disease. KEY POINTS: The prognostic value of chemotherapy response on 18F-FDG PET/CT in advanced neuroblastoma is unknown. Higher 18F-FDG uptake after chemotherapy was associated with worse long-term event-free survival and overall survival. 18F-FDG PET/CT after chemotherapy holds prognostic significance in children with stage 4 neuroblastoma.

Kinematic target surface sensing based on improved deep optical flow tracking.

Reconstruction of moving target surfaces based on active image sensing techniques, such as phase-shifting profilometry, has attracted intensive research in recent years. The measurement error caused by object motion can be addressed successfully by tracking the object movement. However, it either requires high-cost color imaging equipment or is limited by the assumption of 2D translation movement. Therefore, this paper proposes what we believe to be a new method to reconstruct the kinematic object surfaces with any 2D movement sensed by affordable monochrome camera. An improved RAFT optical flow algorithm is proposed to track the object based on the object fringe pattern image directly. The feature points on the object are retrieved immune to the fringe pattern illumination. Then, the RANSAC algorithm and an iteration selection process are employed to select feature points with high quality optical flow. At last, the motion is described mathematically, and the dynamic object is reconstructed successfully. Experiments are presented to verify the effectiveness of the proposed method.

Three-dimensional genome landscape comprehensively reveals patterns of spatial gene regulation in papillary and anaplastic thyroid cancers: a study using representative cell lines for each cancer type.

BACKGROUND: Spatial chromatin structure is intricately linked with somatic aberrations, and somatic mutations of various cancer-related genes, termed co-mutations (CoMuts), occur in certain patterns during cancer initiation and progression. The functional mechanisms underlying these genetic events remain largely unclear in thyroid cancer (TC). With discrepant differentiation, papillary thyroid cancer (PTC) and anaplastic thyroid cancer (ATC) differ greatly in characteristics and prognosis. We aimed to reveal the spatial gene alterations and regulations between the two TC subtypes. METHODS: We systematically investigated and compared the spatial co-mutations between ATC (8305C), PTC (BCPAP and TPC-1), and normal thyroid cells (Nthy-ori-3-1). We constructed a framework integrating whole-genome sequencing (WGS), high-throughput chromosome conformation capture (Hi-C), and transcriptome sequencing, to systematically detect the associations between the somatic co-mutations of cancer-related genes, structural variations (SVs), copy number variations (CNVs), and high-order chromatin conformation. RESULTS: Spatial co-mutation hotspots were enriched around topologically associating domains (TADs) in TC. A common set of 227 boundaries were identified in both ATC and PTC, with significant overlaps between them. The spatial proximities of the co-mutated gene pairs in the two TC types were significantly greater than in the gene-level and overall backgrounds, and ATC cells had higher TAD contact frequency with CoMuts > 10 compared with PTC cells. Compared with normal thyroid cells, in ATC the number of the created novel three-dimensional chromatin structural domains increased by 10%, and the number of shifted TADs decreased by 7%. We found five TAD blocks with CoMut genes/events specific to ATC with certain mutations in genes including MAST-NSUN4, AM129B/TRUB2, COL5A1/PPP1R26, PPP1R26/GPSM1/CCDC183, and PRAC2/DLX4. For the majority of ATC and PTC cells, the HOXA10 and HIF2α signals close to the transcription start sites of CoMut genes within TADs were significantly stronger than those at the background. CNV breakpoints significantly overlapped with TAD boundaries in both TC subtypes. ATCs had more CNV losses overlapping with TAD boundaries, and noncoding SVs involved in intrachromosomal SVs, amplified inversions, and tandem duplication differed between ATC and PTC. TADs with short range were more abundant in ATC than PTC. More switches of A/B compartment types existed in ATC cells compared with PTC. Gene expression was significantly synchronized, and orchestrated by complex epigenetics and regulatory elements. CONCLUSION: Chromatin interactions and gene alterations and regulations are largely heterogeneous in TC. CNVs and complex SVs may function in the TC genome by interplaying with TADs, and are largely different between ATC and PTC. Complexity of TC genomes, which are highly organized by 3D genome-wide interactions mediating mutational and structural variations and gene activation, may have been largely underappreciated. Our comprehensive analysis may provide key evidence and targets for more customized diagnosis and treatment of TC.

An Augmented Sample Selection Framework for Prediction of Anticancer Peptides.

Anticancer peptides (ACPs) have promising prospects for cancer treatment. Traditional ACP identification experiments have the limitations of low efficiency and high cost. In recent years, data-driven deep learning techniques have shown significant potential for ACP prediction. However, data-driven prediction models rely heavily on extensive training data. Furthermore, the current publicly accessible ACP dataset is limited in size, leading to inadequate model generalization. While data augmentation effectively expands dataset size, existing techniques for augmenting ACP data often generate noisy samples, adversely affecting prediction performance. Therefore, this paper proposes a novel augmented sample selection framework for the prediction of anticancer peptides (ACPs-ASSF). First, the prediction model is trained using raw data. Then, the augmented samples generated using the data augmentation technique are fed into the trained model to compute pseudo-labels and estimate the uncertainty of the model prediction. Finally, samples with low uncertainty, high confidence, and pseudo-labels consistent with the original labels are selected and incorporated into the training set to retrain the model. The evaluation results for the ACP240 and ACP740 datasets show that ACPs-ASSF achieved accuracy improvements of up to 5.41% and 5.68%, respectively, compared to the traditional data augmentation method.

Cross-Corpus Speech Emotion Recognition Based on Multi-Task Learning and Subdomain Adaptation.

To solve the problem of feature distribution discrepancy in cross-corpus speech emotion recognition tasks, this paper proposed an emotion recognition model based on multi-task learning and subdomain adaptation, which alleviates the impact on emotion recognition. Existing methods have shortcomings in speech feature representation and cross-corpus feature distribution alignment. The proposed model uses a deep denoising auto-encoder as a shared feature extraction network for multi-task learning, and the fully connected layer and softmax layer are added before each recognition task as task-specific layers. Subsequently, the subdomain adaptation algorithm of emotion and gender features is added to the shared network to obtain the shared emotion features and gender features of the source domain and target domain, respectively. Multi-task learning effectively enhances the representation ability of features, a subdomain adaptive algorithm promotes the migrating ability of features and effectively alleviates the impact of feature distribution differences in emotional features. The average results of six cross-corpus speech emotion recognition experiments show that, compared with other models, the weighted average recall rate is increased by 1.89~10.07%, the experimental results verify the validity of the proposed model.

Preclinical and clinical study on [18F]DRKXH1: a novel ß-amyloid PET tracer for Alzheimer's disease.

BACKGROUND: The deposition of ß-amyloid (Aß) in the brain is a biomarker of Alzheimer's disease (AD). Highly sensitive Aß positron emission tomography (PET) imaging plays an essential role in diagnosing and evaluating the therapeutic effects of AD. AIM: To synthesize a new Aß tracer [18F]DRKXH1 (5-(4-(6-(2-[18]fluoroethoxy)ethoxy)imidazo[1,2-alpha]pyridin-2-yl)phenyl) and evaluate the tracer performance by biodistribution analysis, in vivo small-animal PET-CT dynamic scan, ex vivo and in vitro autoradiography, and PET in human subjects. METHODS: [18F]DRKXH1 was synthesized automatically by the GE FN module. Log D (pH 7.4) and biodistribution of [18F]DRKXH1 were investigated. Small-animal-PET was used for [18F]DRKXH1 and [18F]AV45 imaging study in AD transgenic mice (APPswe/PSEN1dE9) and age-matched normal mice. The distribution volume ratios (DVR) and standardized uptake value ratios (SUVRs) were calculated with the cerebellum as the reference region. The deposition of Aß plaques in the brain of AD transgenic mice was determined by ex vivo autoradiography and immunohistochemistry. In vitro autoradiography was performed in the postmortem brain sections of AD patients and healthy controls. Two healthy control subjects and one AD patient was subjected to in vivo PET study using [18F]DRKXH1. RESULTS: The yield of [18F]DRKXH1 was 40%, and the specific activity was 156.64 ± 11.55 GBq/µmol. [18F]DRKXH1 was mainly excreted through the liver and kidney. The small-animal PET study showed high initial brain uptake and rapid washout of [18F]DRKXH1. The concentration of [18F]DRKXH1 was detected in the cortex and hippocampus of AD transgenic mice brain. The cortex DVR of AD transgenic mice was higher than that of WT mice (P < 0.0001). Moreover, the SUVRs of AD transgenic mice were higher than those of WT mice based on the 0-60-min dynamic scanning. In vitro autoradiography showed a significant concentration of tracer in the Aß plaque-rich areas in the brain of AD transgenic mice. The DVR value of [18F]-DRKXH1 is higher than that of [18F]-AV45 (1.29 ± 0.05 vs. 1.05 ± 0.08; t = 5.33, P = 0.0003). Autoradiography of postmortem human brain sections showed [18F]DRKXH1-labeled Aß plaques in the AD brain. The AD patients had high retention in cortical regions, while healthy control subjects had uniformly low radioactivity uptake. CONCLUSIONS: [18F]DRKXH1 is an Aß tracer with high sensitivity in preclinical study and has the potential for in vivo detection of the human brain.

Multi-Stream Convolution-Recurrent Neural Networks Based on Attention Mechanism Fusion for Speech Emotion Recognition.

The quality of feature extraction plays a significant role in the performance of speech emotion recognition. In order to extract discriminative, affect-salient features from speech signals and then improve the performance of speech emotion recognition, in this paper, a multi-stream convolution-recurrent neural network based on attention mechanism (MSCRNN-A) is proposed. Firstly, a multi-stream sub-branches full convolution network (MSFCN) based on AlexNet is presented to limit the loss of emotional information. In MSFCN, sub-branches are added behind each pooling layer to retain the features of different resolutions, different features from which are fused by adding. Secondly, the MSFCN and Bi-LSTM network are combined to form a hybrid network to extract speech emotion features for the purpose of supplying the temporal structure information of emotional features. Finally, a feature fusion model based on a multi-head attention mechanism is developed to achieve the best fusion features. The proposed method uses an attention mechanism to calculate the contribution degree of different network features, and thereafter realizes the adaptive fusion of different network features by weighting different network features. Aiming to restrain the gradient divergence of the network, different network features and fusion features are connected through shortcut connection to obtain fusion features for recognition. The experimental results on three conventional SER corpora, CASIA, EMODB, and SAVEE, show that our proposed method significantly improves the network recognition performance, with a recognition rate superior to most of the existing state-of-the-art methods.

Metabolic tumor burden on baseline 18F-FDG PET/CT improves risk stratification in pediatric patients with mature B-cell lymphoma.

PURPOSE: In order to better identify patients most at risk of treatment failure and disease progression in pediatric mature B-cell non-Hodgkin lymphoma (B-NHL), the prognostic role of metabolic tumor burden measured on baseline 18F-FDG PET/CT scan, including total metabolic tumor volume (TMTV) and total lesion glycolysis (TLG), was investigated. METHODS: Pretreatment 18F-FDG PET/CT scans from 46 consecutive pediatric patients (median age 7 years; range 2-18 years) with newly diagnosed B-NHL were retrospectively analyzed. Clinicopathological parameters and imaging characteristics, including TMTV, TLG, and bone marrow (BM) involvement detected by PET/CT were compared to predict progression-free survival (PFS) and overall survival (OS). RESULTS: The median follow-up time was 31 months. Areas under the curve of TMTV and TLG to predict events were 0.820 and 0.816, respectively. The 2-year PFS and OS were 29% and 43% in 7 patients with high TLG (> 5797 g) vs. 93% and 96% in those with low TLG (P < 0.001). High TMTV (> 524 cm3) was present in ten patients and predicted a significantly inferior outcome (PFS: 50% vs. 92%, P = 0.001; OS: 60% vs. 96%, P = 0.002). In multivariate analysis, TMTV and TLG outperformed other clinicopathological factors, including serum lactate dehydrogenase and BM involvement on biopsy, and remained the most robust predictors of survival. Furthermore, TLG sub-stratified patients with distinct outcomes efficiently within high- or intermediate-risk groups, with the negative predictive value of 100% and 92% and the positive predictive value of 100% and 50% for high-risk and intermediate-risk patients, respectively. On the other hand, BM involvement identified only by PET demonstrated an inferior prognostic value in comparison with BM biopsy. CONCLUSIONS: Baseline TMTV and TLG are both strong independent prognostic factors for pediatric B-NHL and provide a potential approach to aid in risk sub-stratification, especially in patients with high-risk disease.

FDG PET/CT Evaluation of Pediatric Patients With Yolk Sac Tumor.

OBJECTIVE. The objective of our study was to evaluate the clinical utility of FDG PET/CT in staging and restaging pediatric patients with yolk sac tumor (YST). MATERIALS AND METHODS. We retrospectively reviewed the data from 31 pediatric patients with pathologically confirmed YST who underwent 34 PET/CT studies for the purpose of staging or restaging. The PET/CT studies were read by two nuclear medicine doctors in consensus. Histopathology combined with clinical and imaging follow-up was taken as the reference standard. The results of PET/CT were also compared with conventional imaging and α-fetoprotein (AFP) levels when available. RESULTS. Of the total 34 studies, six were performed for initial staging and the other 28 for posttherapy evaluation. FDG PET/CT was true-positive in all six staging studies, detected only a few more metastatic foci than conventional imaging, and changed the therapeutic regimen in none of the six patients. Nevertheless, PET/CT showed high accuracy in the restaging group, with a sensitivity of 100% and specificity of 85.7%. The treatment regimen was changed in 46.4% of the patients in the restaging group according to the PET/CT study. In addition, PET/CT had higher accuracy than AFP levels in YST restaging. Overall, the per-study performance of PET/CT was a sensitivity of 100%, specificity of 85.7%, positive predictive value of 90.9%, and negative predictive value of 100%. CONCLUSION. FDG PET/CT was only slightly superior to conventional imaging in staging YST in pediatric patients. However, PET/CT of posttherapy patients with YST showed high diagnostic accuracy and had a great impact on therapeutic management.

PET/CT predicts bone marrow involvement in paediatric non-Hodgkin lymphoma and may preclude the need for bone marrow biopsy in selected patients.

OBJECTIVES: To investigate the role of 18F-FDG PET/CT to detect bone marrow (BM) involvement in paediatric non-Hodgkin lymphoma (NHL). METHODS: Pretreatment PET/CT scans from 93 consecutive paediatric patients with NHL were retrospectively reviewed. Patterns of BM FDG uptake and standardized uptake value of the fifth lumbar vertebra (SUVBM) were compared with bone marrow biopsy (BMB) for diagnosis of BM involvement. RESULTS: Of 93 patients, 41 were judged to have BM involvement. Thirty-nine were identified by PET/CT, versus 23 by BMB. Sensitivity and specificity were 95 % and 98 % for PET/CT and 56 % and 100 % for BMB, respectively. None of the patients with BM FDG uptake lower than liver had positive BMB. In 45 patients presenting homogeneously increased BM uptake, positive BMB was achieved in 93 % (14/15) of patients with FDG uptake expanding to the distal portion of extremities, compared to 7 % (2/30) of those without. A multifocal pattern was observed in 25 patients and 18 had negative BMB. SUVBM differentiated BM involvement from benign BM activation with an area under the curve of 0.885 (p < 0.001). CONCLUSIONS: PET/CT had a high level of accuracy for detecting BM involvement in paediatric NHL. BMB might be omitted in selected patients. KEY POINTS: • PET/CT allows for accurate detection of bone marrow involvement. • Patterns of bone marrow FDG uptake are highly correlated with marrow disease. • Bone marrow biopsy could be omitted in selected paediatric patients.