Altered brain function in classical trigeminal neuralgia patients: ALFF, ReHo, and DC static- and dynamic-frequency study.

The present study aimed to clarify the brain function of classical trigeminal neuralgia (CTN) by analyzing 77 CTN patients and age- and gender-matched 73 healthy controls (HCs) based on three frequency bands of the static and dynamic amplitude of low-frequency fluctuation, regional homogeneity, and degree centrality (sALFF, sReHo, sDC, dALFF, dReHo, and dDC). Compared to HCs, the number of altered brain regions was different in three frequency bands, and the classical frequency band was most followed by slow-4 in CTN patients. Cerrelellum_8_L (sReHo), Cerrelellum_8_R (sDC), Calcarine_R (sDC), and Caudate_R (sDC) were found only in classical frequency band, while Precuneus_L (sALFF) and Frontal_Inf_Tri_L (sReHo) were found only in slow-4 frequency band. Except for the above six brain regions, the others overlapped in the classical and slow-4 frequency bands. CTN seriously affects the mental health of patients, and some different brain regions are correlated with clinical parameters. The static and dynamic indicators of brain function were complementary in CTN patients, and the changing brain regions showed frequency specificity. Compared to slow-5 frequency band, slow-4 is more consistent with the classical frequency band, which could be valuable in exploring the pathophysiology of CTN.

In Situ Spatiotemporal SERS Profiling of Bacterial Quorum Sensing by Hierarchical Hydrophobic Plasmonic Arrays in Agar Medium.

A feedback inhibition effect of high autoinducer levels on metabolite secretion in Chromobacterium subtsugae (C. subtsugae) was evidenced by in situ spatiotemporal surface-enhanced Raman spectroscopy (SERS) profiling. The hierarchical hydrophobic plasmonic array in agar medium is structured by oil/water/oil (OL/W/OH) triphasic interfacial self-assembly. The hydrophobic layer acts as a "door curtain" to selectively permit adsorption of a quorum sensing (QS)-regulated fat-soluble metabolite, i.e., violacein (Vio), and significantly blocks nonspecific adsorption of water-soluble proteins, etc. The SERS profiling clearly evidences that the diffusion of N-hexanoyl-l-homoserine lactone (C6-HSL) in agar medium quickly triggers the initial synthesis of Vio in C. subtsugae CV026 but surprisingly inhibits the intrinsic synthesis of Vio in C. subtsugae ATCC31532. The latter negative response might be related to the VioS repressor of ATCC31532, which negatively controls violacein production without influencing the expression of the CviI/R QS system. Moreover, two sender-receiver systems are constructed by separately coculturing CV026 or ATCC31532 with Hafnia alvei H4 that secretes large amounts of C6-HSL. Expectedly, the cocultivation similarly triggers the initial synthesis of Vio in CV026 but seems to have a quite weak negative effect on the intrinsic synthesis in ATCC31532. In fact, the negative regulation in ATCC31532 might be affected by a diffusion-dependent concentration effect. The H4 growth and its secretion of C6-HSL are a slow and continuous process, thereby avoiding the gathering of local high concentrations. Overall, our study put forward an in situ SERS strategy as an alternative to traditional bioluminescent tools for highly sensitively analyzing the spatiotemporal communication and cooperation in live microbial colonies.

Artificial intelligence model system for bone age assessment of preschool children.

BACKGROUD: Our study aimed to assess the impact of inter- and intra-observer variations when utilizing an artificial intelligence (AI) system for bone age assessment (BAA) of preschool children. METHODS: A retrospective study was conducted involving a total sample of 53 female individuals and 41 male individuals aged 3-6 years in China. Radiographs were assessed by four mid-level radiology reviewers using the TW3 and RUS-CHN methods. Bone age (BA) was analyzed in two separate situations, with/without the assistance of AI. Following a 4-week wash-out period, radiographs were reevaluated in the same manner. Accuracy metrics, the correlation coefficient (ICC)and Bland-Altman plots were employed. RESULTS: The accuracy of BAA by the reviewers was significantly improved with AI. The results of RMSE and MAE decreased in both methods (p < 0.001). When comparing inter-observer agreement in both methods and intra-observer reproducibility in two interpretations, the ICC results were improved with AI. The ICC values increased in both two interpretations for both methods and exceeded 0.99 with AI. CONCLUSION: In the assessment of BA for preschool children, AI was found to be capable of reducing inter-observer variability and enhancing intra-observer reproducibility, which can be considered an important tool for clinical work by radiologists. IMPACT: The RUS-CHN method is a special bone age method devised to be suitable for Chinese children. The preschool stage is a critical phase for children, marked by a high degree of variability that renders BA prediction challenging. The accuracy of BAA by the reviewers can be significantly improved with the aid of an AI model system. This study is the first to assess the impact of inter- and intra-observer variations when utilizing an AI model system for BAA of preschool children using both the TW3 and RUS-CHN methods.

Altered trends of local brain function in classical trigeminal neuralgia patients after a single trigger pain.

OBJECTIVE: To investigate the altered trends of regional homogeneity (ReHo) based on time and frequency, and clarify the time-frequency characteristics of ReHo in 48 classical trigeminal neuralgia (CTN) patients after a single pain stimulate. METHODS: All patients underwent three times resting-state functional MRI (before stimulation (baseline), after stimulation within 5 s (triggering-5 s), and in the 30th min of stimulation (triggering-30 min)). The spontaneous brain activity was investigated by static ReHo (sReHo) in five different frequency bands and dynamic ReHo (dReHo) methods. RESULTS: In the five frequency bands, the number of brain regions which the sReHo value changed in classical frequency band were most, followed by slow 4 frequency band. The left superior occipital gyrus was only found in slow 2 frequency band and the left superior parietal gyrus was only found in slow 3 frequency band. The dReHo values were changed in midbrain, left thalamus, right putamen, and anterior cingulate cortex, which were all different from the brain regions that the sReHo value altered. There were four altered trends of the sReHo and dReHo, which dominated by decreased at triggering-5 s and increased at triggering-30 min. CONCLUSIONS: The duration of brain function changed was more than 30 min after a single pain stimulate, although the pain of CTN was transient. The localized functional homogeneity has time-frequency characteristic in CTN patients after a single pain stimulate, and the changed brain regions of the sReHo in five frequency bands and dReHo complemented to each other. Which provided a certain theoretical basis for exploring the pathophysiology of CTN.

Application of the process-based teaching based on SPARK case database in the practice teaching of radiology in the musculoskeletal system for undergraduate medical students.

BACKGROUND: Process-based teaching is a new education model. SPARK case database is a free medical imaging case database. This manuscript aimed to explore the application of the process-based teaching based on SPARK case database in the practice teaching of radiology in the musculoskeletal system. METHODS: 117 third year medical students were included. They were divided into Group A, B, C and D according to the curriculum arrangement. Group A and B attended the experimental class at the same time, A was the experimental group, B was the control group. Group C and D attended experimental classes at the same time, C was the experimental group, D was the control group. The experimental group used SPARK case database, while the control group used traditional teaching model for learning. The four groups of students were respectively tested after the theoretical class, before the experimental class, after the experimental class, and one week after the experimental class to compare the results. Finally, all students used SPARK case database to study, and were tested one month after the experimental class to compare their differences. RESULTS: The scores after the theoretical class of Group A and B were (100.0 ± 25.4), (101.0 ± 23.8)(t=-0.160, P > 0.05), Group C and D were (94.7 ± 23.7), (92.1 ± 18.6)(t = 0.467, P > 0.05). The scores of Group A and B before and after the experimental class and one week after the experimental class were respectively (84.1 ± 17.4), (72.1 ± 21.3)(t = 2.363, P < 0.05), (107.6 ± 14.3), (102.1 ± 18.0)(t = 1.292, P > 0.05), (89.7 ± 24.3), (66.6 ± 23.2)(t = 3.706, P < 0.05). The scores of Group C and D were (94.0 ± 17.3), (72.8 ± 25.5)(t = 3.755, P < 0.05), (107.3 ± 20.3), (93.1 ± 20.9)(t = 2.652, P < 0.05), (100.3 ± 19.7), (77.2 ± 24.0)(t = 4.039, P < 0.05). The scores of Group A and B for one month after the experimental class were (86.6 ± 28.8), (84.5 ± 24.0)(t = 0.297, P > 0.05), and Group C and D were (95.7 ± 20.3), (91.7 ± 23.0)(t = 0.699, P > 0.05). CONCLUSIONS: The process-based teaching based on SPARK case database could improve the radiology practice ability of the musculoskeletal system of students.

Acoustic Levitation Synthesis of Ultrahigh-Density Spherical Nucleic Acid Architectures for Specific SERS Analysis.

Controllably regulating the electrostatic bilayer of nanogold colloids is a significant premise for synthesizing spherical nucleic acid (SNA) and building ordered plasmonic architectures. We develop a facile acoustic levitation reactor to universally synthesize SNAs with an ultra-high density of DNA strands, which is even higher than those of various state-of-the-art methods. Results reveal a new mechanism of DNA grafting via acoustic wave that can reconfigure the ligands on colloidal surfaces. The acoustic levitation reactor enables substrate-free three-dimentional (3D) spatial assembly of SNAs with controllable interparticle nanogaps through regulating DNA lengths. This kind of architecture may overcome the plasmonic enhancement limits by blocking electron tunneling and breaking electrostatic shielding in dried aggregations. Finite element simulations support the architecture with 3D spatial plasmonic hotspot matrix, and its ultrahigh surface-enhanced Raman scattering (SERS) capability is evidenced by in situ untargeted tracking of biomolecular events during photothermal stimulation (PTS)-induced cell death process. For biomarker diagnosis, the conjugation of adenosine triphosphate (ATP) aptamer onto SNAs enables in situ targeted tracking of ATP during PTS-induced cell death process. Particularly, the CD71 receptor and integrin α3ß1 protein on PL45 cell membrance could be well distinguished by label-free SERS fingerprints when using specific XQ-2d and DML-7 aptamers, respectively, to synthesize SNA architectures. Our current acoustic levitation reactor offers a new method for synthesizing SNAs and enables both targeted and untargeted SERS analysis for tracking molecular events in living systems. It promises great potentials in biochemical synthesis and sensing in future.

Prediction of early hematoma expansion of spontaneous intracerebral hemorrhage based on deep learning radiomics features of noncontrast computed tomography.

OBJECTIVES: Aimed to develop a nomogram model based on deep learning features and radiomics features for the prediction of early hematoma expansion. METHODS: A total of 561 cases of spontaneous intracerebral hemorrhage (sICH) with baseline Noncontrast Computed Tomography (NCCT) were included. The metrics of hematoma detection were evaluated by Intersection over Union (IoU), Dice coefficient (Dice), and accuracy (ACC). The semantic features of sICH were judged by EfficientNet-B0 classification model. Radiomics analysis was performed based on the region of interest which was automatically segmented by deep learning. A combined model was constructed in order to predict the early expansion of hematoma using multivariate binary logistic regression, and a nomogram and calibration curve were drawn to verify its predictive efficacy by ROC analysis. RESULTS: The accuracy of hematoma detection by segmentation model was 98.2% for IoU greater than 0.6 and 76.5% for IoU greater than 0.8 in the training cohort. In the validation cohort, the accuracy was 86.6% for IoU greater than 0.6 and 70.0% for IoU greater than 0.8. The AUCs of the deep learning model to judge semantic features were 0.95 to 0.99 in the training cohort, while in the validation cohort, the values were 0.71 to 0.83. The deep learning radiomics model showed a better performance with higher AUC in training cohort (0.87), internal validation cohort (0.83), and external validation cohort (0.82) than either semantic features or Radscore. CONCLUSION: The combined model based on deep learning features and radiomics features has certain efficiency for judging the risk grade of hematoma. CLINICAL RELEVANCE STATEMENT: Our study revealed that the deep learning model can significantly improve the work efficiency of segmentation and semantic feature classification of spontaneous intracerebral hemorrhage. The combined model has a good prediction efficiency for early hematoma expansion. KEY POINTS: • We employ a deep learning algorithm to perform segmentation and semantic feature classification of spontaneous intracerebral hemorrhage and construct a prediction model for early hematoma expansion. • The deep learning radiomics model shows a favorable performance for the prediction of early hematoma expansion. • The combined model holds the potential to be used as a tool in judging the risk grade of hematoma.

Antifreezing Hydroxyl Monolayer of Small Molecules on a Nanogold Surface.

The rational design of ice recrystallization inhibition (IRI) materials is challenging due to the poor understanding of the IRI mechanism at the molecular level. Here we report several new findings about IRI. (1) A dense hydroxyl monolayer of small molecules, e.g. 6-aza-2-thiothymine (ATT), adsorbed on a nanogold surface was demonstrated, for the first time, to have IRI activity. Five structural analogues adsorbed on groups nanogold with outward hydroxyl or methyl were created to evidence the origin of IRI activity. (2) Their IRI mechanism is closely related to the density of hydroxyls on a nanogold surface. However, the hydrophobic interaction in our model is not essential for macroscopic IRI activity. (3) A molecular dynamics simulation elucidates the hydroxyl density dependent IRI trajectories underlying the experimental observations, and the radial distribution function reveals that the methyl even slightly hinders the formation of hydrogen bonding due to a hydrophobic interaction. This work sheds more light on the IRI mechanism that should help in the customization of novel IRI materials.

Alteration of the cortical morphology in classical trigeminal neuralgia: voxel-, deformation-, and surface-based analysis.

OBJECTIVE: This study aimed to combine voxel-based morphometry, deformation-based morphometry, and surface-based morphometry to analyze gray matter volume and cortex shape in classical trigeminal neuralgia patients. METHODS: This study included 79 classical trigeminal neuralgia patients and age- and sex-matched 81 healthy controls. The aforementioned three methods were used to analyze brain structure in classical trigeminal neuralgia patients. Spearman correlation analysis was used to analyze the correlation of brain structure with the trigeminal nerve and clinical parameters. RESULTS: The bilateral trigeminal nerve was atrophied, and the ipsilateral trigeminal nerve volume was smaller than the contralateral volume in the classical trigeminal neuralgia. The gray matter volume of Temporal_Pole_Sup_R and Precentral_R was found to be decreased using voxel-based morphometry. The gray matter volume of Temporal_Pole_Sup_R had a positive correlation with disease duration and a negative correlation with the cross-section area of the compression point and the quality-of-life score in trigeminal neuralgia. The gray matter volume of Precentral_R was negatively correlated with the ipsilateral volume of the trigeminal nerve cisternal segment, cross-section area of compression point, and visual analogue scale. The gray matter volume of Temporal_Pole_Sup_L was found to be increased using deformation-based morphometry and had a negative correlation with the self-rating anxiety scale. The gyrification of the middle temporal gyrus_L increased and the Postcentral_L thickness decreased, as detected using surface-based morphometry. CONCLUSIONS: The gray matter volume and cortical morphology of pain-related brain regions were correlated with clinical and trigeminal nerve parameters. voxel-based morphometry, deformation-based morphometry, and surface-based morphometry complemented each other in analyzing the brain structures of patients with classical trigeminal neuralgia and provided a basis for studying the pathophysiology of classical trigeminal neuralgia.

Pinpointing Alkane Chain Length, Saturation, and Double Bond Regio- and Stereoisomers by Liquid Interfacial Plasmonic Enhanced Raman Spectroscopy.

The lipids with a rich diversity of isomers face a formidable challenge in comprehensive structural analysis. The commonly used mass spectrometry-based techniques usually require a considerable number of molecules with sophisticated chemical derivatization or ion mobility separation, but the co-existing of structurally similar isomers often makes the distinction impossible. Here, we develop an alternative powerful liquid/liquid interfacial surface-enhanced Raman spectroscopy (SERS) strategy at normal temperature and pressure without any sources of ionization or radiation. This strategy generates high-resolution fingerprints in molecular chain length, C═C position, saturation, and regio- and stereoisomers of both glycerides and fatty acids and requires only trace amounts of molecules down to 1 ppb to achieve discrimination and exhibits great potentials to push the identification capability to trace levels or even the single-molecule level. According to experimental data and theoretical simulations, these targets have the amphiphilic and emulsifying properties, exhibit ordered molecular orientation and adsorption patterns, promote the co-assembly with plasmonic nanoarrays at the immiscible liquid/liquid interface, and consequently amplify the detection sensitivity. As a contrast, the typical SERS based on solid/air interfacial plasmonic nanoarrays faces the intrinsic bottleneck of extremely weak intensity and indistinguishable spectral fingerprints of lipid molecules. The vibrational fingerprints exhibit a rich range of well-resolved absorption features that are clearly diagnostic for fine structural changes and pave a new way for straightforward measurement without laborsome sample purification, enrichment, or complex derivatization. Although challenging, its unprecedented resolving power expands the potentials of SERS, serving as an ultimate analytical method to provide insights into the detailed structural features of other lipids under facile conditions in the future.

Deep learning derived automated ASPECTS on non-contrast CT scans of acute ischemic stroke patients.

Ischemic stroke is the most common type of stroke, ranked as the second leading cause of death worldwide. The Alberta Stroke Program Early CT Score (ASPECTS) is considered as a systematic method of assessing ischemic change on non-contrast CT scans (NCCT) of acute ischemic stroke (AIS) patients, while still suffering from the requirement of experts' experience and also the inconsistent results between readers. In this study, we proposed an automated ASPECTS method to utilize the powerful learning ability of neural networks for objectively scoring CT scans of AIS patients. First, we proposed to use the CT perfusion (CTP) from one-stop stroke imaging to provide the golden standard of ischemic regions for ASPECTS scoring. Second, we designed an asymmetry network to capture features when comparing the left and right sides for each ASPECTS region to estimate its ischemic status. Third, we performed experiments in a large main dataset of 870 patients, as well as an independent testing dataset consisting of 207 patients with radiologists' scorings. Experimental results show that our network achieved remarkable performance, as sensitivity and accuracy of 93.7 and 92.4% in the main dataset, and 95.5 and 91.3% in the independent testing dataset, respectively. In the latter dataset, our analysis revealed a high positive correlation between the ASPECTS score and the prognosis of patients in 90DmRs. Also, we found ASPECTS score is a good indicator of the size of CTP core volume of an infraction. The proposed method shows its potential for automated ASPECTS scoring on NCCT images.

Ultrasound gray scale ratio for differential diagnosis of papillary thyroid microcarcinoma from benign micronodule in patients with Hashimoto's thyroiditis.

BACKGROUND: To investigate the diagnostic value of ultrasound gray scale ratio (UGSR) in differentiating papillary thyroid microcarcinomas (PTMCs) from benign micronodules (BMNs) in patients with Hashimoto's thyroiditis (HT). METHODS: The ultrasound images of 285 PTMCs (from 247 patients) and 173 BMNs (from 140 patients) in the HT group, as well as 461 PTMCs (from 417 patients) and 234 BMNs (from 197 patients) in the non-HT group were retrospectively analyzed. The diagnosis of all cases was confirmed by histopathological examinations. The gray scale values of the nodules and surrounding thyroid tissues were measured and subsequently the UGSRs were calculated. Receiver operating characteristic curve analysis was used to determine the area under the curve (AUC), optimal UGSR threshold, sensitivity and specificity in differentiating PTMCs and BMNs in the two groups. RESULTS: The UGSR of PTMC and BMN was 0.52 ± 0.12 and 0.85 ± 0.24 in the HT group (P < 0.001), and 0.57 ± 0.13 and 0.87 ± 0.20 in the non-HT group (P < 0.001), respectively. The difference in PTMC-UGSR was significant between the two groups (P < 0.001), whereas BMN-UGSR did not differ between the two groups (P = 0.416). The AUC, optimal UGSR threshold, sensitivity and specificity of UGSR for differentiating PTMC and BMN in the HT and non-HT group were 0.890 versus 0.901, 0.68 versus 0.72, 91.23% versus 90.67%, and 77.46% versus 82.05%, respectively. CONCLUSIONS: The USGR of the HT group was lower than that of the non-HT group. Moreover, UGSR exhibited important diagnostic value in differentiating PTMC from BMN in both HT and non-HT groups.

A diagnosis model in nasopharyngeal carcinoma based on PET/MRI radiomics and semiquantitative parameters.

BACKGROUND: The staging of nasopharyngeal carcinoma (NPC) is of great value in treatment and prognosis. We explored whether a positron emission tomography/ magnetic resonance imaging (PET/MRI) based comprehensive model of radiomics features and semiquantitative parameters was useful for clinical evaluation of NPC staging. MATERIALS AND METHODS: A total of 100 NPC patients diagnosed with non-keratinized undifferentiated carcinoma were divided into early-stage group (I-II) and advanced-stage group (III-IV) and divided into the training set (n = 70) and the testing set (n = 30). Radiomics features (n = 396 × 2) of the primary site of NPC were extracted from MRI and PET images, respectively. Three major semiquantitative parameters of primary sites including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) in all NPC patients were measured. After feature selection, three diagnostic models including the radiomics model, the metabolic parameter model, and the combined model were established using logistic regression model. Finally, internal validation was performed, and a nomogram for NPC comprehensive diagnosis has been made. RESULTS: The radiomics model and metabolic parameter model showed an area under the curve (AUC) of 0.83 and 0.80 in the testing set, respectively. The combined model based on radiomics and semiquantitative parameters showed an AUC of 0.90 in the testing set, with the best performance among the three models. CONCLUSION: The combined model based on PET/MRI radiomics and semiquantitative parameters is of great value in the evaluation of clinical stage (early-stage group and advanced-stage group) of NPC.

Application of SPARK teaching in acute abdomen radiography teaching for undergraduate medical students.

BACKGROUND: Acute abdomen is a series of acute and severe abdominal diseases commonly encountered in clinic. It is important to strengthen the image teaching of acute abdomen for undergraduates. AIM: This study aimed to explore the application effect of SPARK[sub-speciality (S), problem-based learning (P), assessment (A), report (R) and reading skill (K)] teaching mode in the experimental teaching of acute abdomen for undergraduate medical students. METHODS: We selected a total of 58 third year medical students for observation. The students were divided into experimental group and control group. Among them, 29 students in the experimental group studied in SPARK teaching mode, 29 students in the control group studied in traditional teaching mode. The two groups of students were tested after the theory class, before and after the experimental class, and one week after the experimental class, to compare the application effects of the two teaching modes. After the test one week after the experimental class, the two groups of students jointly adopted SPARK mode to learn, and were tested again one month after the experimental class to compare whether the two groups of students achieved the same results. The total score of all tests was 150. RESULTS: The average scores of the experimental group and the control group after theory class were (69.0 ± 26.4) and (72.1 ± 24.1) respectively, with no statistical difference (t = 0.468, P = 0.642). The average scores of the experimental group before, after and one week after the experimental class were higher than those of the control group. The experimental group was (84.5 ± 23.1), (109.7 ± 23.8), (105.5 ± 31.0) respectively, and the control group was (52.8 ± 15.1), (93.8 ± 17.0), (80.0 ± 22.8) respectively. The differences were statistically significant (t = -6.195, P = 0.00; t = -2.919, P = 0.05; t = -3.569, P = 0.01). The average scores of the experimental group and the control group after one month were (99.0 ± 31.0) and (95.5 ± 25.6) respectively, and there was no significant difference between the two groups (t = -0.462, P = 0.646). CONCLUSIONS: The SPARK teaching mode was helpful for undergraduate medical students to consolidate image foundation, improve image reading skills.

Amplitude of low-frequency fluctuation after a single-trigger pain in patients with classical trigeminal neuralgia.

OBJECTIVE: This study aimed to explore the central mechanism of classical trigeminal neuralgia (CTN) by analyzing the static amplitude of low-frequency fluctuation (sALFF) and dynamic amplitude of low-frequency fluctuation (dALFF) in patients with CTN before and after a single-trigger pain. METHODS: This study included 48 patients (37 women and 11 men, age 55.65 ± 11.41 years) with CTN. All participants underwent 3D-T1WI and three times resting-state functional magnetic resonance imaging. The images were taken before stimulating the trigger zone (baseline), within 5 s after stimulating the trigger zone (triggering-5 s), and in the 30th minute after stimulating the trigger zone (triggering-30 min). The differences between the three measurements were analyzed using a repeated-measures analysis of variance. RESULTS: The sALFF values of the bilateral middle occipital gyrus and right cuneus gradually increased, and the values of the left posterior cingulum gyrus and bilateral superior frontal gyrus gradually decreased in triggering-5 s and triggering-30 min. The values of the right middle temporal gyrus and right thalamus decreased in triggering-5 s and subsequently increased in triggering-30 min. The sALFF values of the left superior temporal gyrus increased in triggering-5 s and then decreased in triggering-30 min. The dALFF values of the right fusiform gyrus, bilateral lingual gyrus, left middle temporal gyrus, and right cuneus gyrus gradually increased in both triggering-5 s and triggering-30 min. CONCLUSIONS: The sALFF and dALFF values changed differently in multiple brain regions in triggering-5 s and triggering-30 min of CTN patients after a single trigger of pain, and dALFF is complementary to sALFF. The results might help explore the therapeutic targets for relieving pain and improving the quality of life of patients with CTN.

Risk stratification of thymic epithelial tumors by using a nomogram combined with radiomic features and TNM staging.

OBJECTIVES: To construct and validate a nomogram model that integrated the CT radiomic features and the TNM staging for risk stratification of thymic epithelial tumors (TETs). METHODS: A total of 136 patients with pathology-confirmed TETs who underwent CT examination were collected from two institutions. According to the WHO pathological classification criteria, patients were classified into low-risk and high-risk groups. The TNM staging was determined in terms of the 8th edition AJCC/UICC staging criteria. LASSO regression was performed to extract the optimal features correlated to risk stratification among the 704 radiomic features calculated. A nomogram model was constructed by combining the Radscore and the TNM staging. The clinical performance was evaluated by ROC analysis, calibration curve, and decision curve analysis (DCA). The Kaplan-Meier (KM) analysis was employed for survival analysis. RESULTS: Five optimal features identified by LASSO regression were employed to calculate the Radscore correlated to risk stratification. The nomogram model showed a better performance in both training cohort (AUC = 0.84, 95%CI 0.75-0.91) and external validation cohort (AUC = 0.79, 95%CI 0.69-0.88). The calibration curve and DCA analysis indicated a better accuracy of the nomogram model for risk stratification than either Radscore or the TNM staging alone. The KM analysis showed a significant difference between the two groups stratified by the nomogram model (p = 0.02). CONCLUSIONS: A nomogram model that integrated the radiomic signatures and the TNM staging could serve as a reliable model of risk stratification in predicting the prognosis of patients with TETs. KEY POINTS: • The radiomic features could be associated with the TET pathophysiology. • TNM staging and Radscore could independently stratify the risk of TETs. • The nomogram model is more objective and more comprehensive than previous methods.

Radiotherapy-related quality of life in patients with head and neck cancers: a meta-analysis.

OBJECTIVES: To compare effects of intensity-modulated radiotherapy (IMRT) with those of conventional radiotherapy on quality of life (QoL) and severity of xerostomia in patients with head and neck cancer. MATERIAL AND METHODS: PubMed, Cochrane, and Embase databases were searched to July 1, 2019, to identify relevant studies, using the following terms: radiotherapy, head and neck cancer, quality of life, cognition, xerostomia, two-/three-dimensional conformal radiation therapy, IMRT, conformal proton beam radiation therapy, stereotactic radiosurgery, and volumetric modulated arc therapy. The outcomes of interest were QoL measured by global health status; emotional, social, and cognitive function; and severity of xerostomia. RESULTS: Seven studies with a total of 761 patients (n = 369 with IMRT; n = 392 with conventional RT) were included in this study. Median patient age was 18-65 years. IMRT group patients had better global health status (pooled standardized mean difference [SMD] = 0.80, 95% CI 0.26 to 1.35, P = 0.004) and cognitive function (pooled SMD = 0.30, 95% CI 0.06 to 0.54, P = 0.013) than the conventional RT group. Patients receiving IMRT also had significantly lower scores for xerostomia than those receiving conventional RT (pooled SMD = - 0.60, 95% CI - 0.97 to - 0.24, P = 0.001). No differences were found in emotional function (P = 0.531) and social function (P = 0.348) between the two groups. CONCLUSION: IMRT significantly improves QoL and reduces the severity of xerostomia in patients with head and neck cancer. Results of this study provide clinicians with guidelines for decisions on the use of IMRT versus conventional RT.

Benign ependymoma with extensive intracranial and spinal cerebrospinal fluid dissemination: case report and literature review.

Myxopapillary ependymoma (MPE) is a rare variant of ependymoma that is most commonly located in the cauda equina and filum terminale. We present a case of 23-year-old man diagnosed with MPE in the fourth ventricle and sacral canal area with extensive disseminated lesions along the cerebrospinal ventricular system. Additionally, a molecular pathological diagnosis was performed. The patient underwent a craniotomy and a lumbar laminectomy. In the course of 18 months of follow-up, the patient have recovered very well.

Radiation-induced brain structural and functional abnormalities in presymptomatic phase and outcome prediction.

Radiation therapy, a major method of treatment for brain cancer, may cause severe brain injuries after many years. We used a rare and unique cohort of nasopharyngeal carcinoma patients with normal-appearing brains to study possible early irradiation injury in its presymptomatic phase before severe, irreversible necrosis happens. The aim is to detect any structural or functional imaging biomarker that is sensitive to early irradiation injury, and to understand the recovery and progression of irradiation injury that can shed light on outcome prediction for early clinical intervention. We found an acute increase in local brain activity that is followed by extensive reductions in such activity in the temporal lobe and significant loss of functional connectivity in a distributed, large-scale, high-level cognitive function-related brain network. Intriguingly, these radiosensitive functional alterations were found to be fully or partially recoverable. In contrast, progressive late disruptions to the integrity of the related far-end white matter structure began to be significant after one year. Importantly, early increased local brain functional activity was predictive of severe later temporal lobe necrosis. Based on these findings, we proposed a dynamic, multifactorial model for radiation injury and another preventive model for timely clinical intervention. Hum Brain Mapp 39:407-427, 2018. © 2017 Wiley Periodicals, Inc.

Real-time diagnosis of intracerebral hemorrhage by generating dual-energy CT from single-energy CT.

Real-time diagnosis of intracerebral hemorrhage after thrombectomy is crucial for follow-up treatment. However, this is difficult to achieve with standard single-energy CT (SECT) due to similar CT values of blood and contrast agents under a single energy spectrum. In contrast, dual-energy CT (DECT) scanners employ two different energy spectra, which allows for real-time differentiation between hemorrhage and contrast extravasation based on energy-related attenuation characteristics. Unfortunately, DECT scanners are not as widely used as SECT scanners due to their high costs. To address this dilemma, in this paper, we generate pseudo DECT images from a SECT image for real-time diagnosis of hemorrhage. More specifically, we propose a SECT-to-DECT Transformer-based Generative Adversarial Network (SDTGAN), which is a 3D transformer-based multi-task learning framework equipped with a shared attention mechanism. In this way, SDTGAN can be guided to focus more on high-density areas (crucial for hemorrhage diagnosis) during the generation. Meanwhile, the introduced multi-task learning strategy and the shared attention mechanism also enable SDTGAN to model dependencies between interconnected generation tasks, improving generation performance while significantly reducing model parameters and computational complexity. In the experiments, we approximate real SECT images using mixed 120kV images from DECT data to address the issue of not being able to obtain the true paired DECT and SECT data. Extensive experiments demonstrate that SDTGAN can generate DECT images better than state-of-the-art methods. The code of our implementation is available at https://github.com/jiang-cw/SDTGAN.