Sex differences in chest electrical impedance tomography findings.

Objective.Electrical impedance tomography (EIT) has been used to determine regional lung ventilation distribution in humans for decades, however, the effect of biological sex on the findings has hardly ever been examined. The aim of our study was to determine if the spatial distribution of ventilation assessed by EIT during quiet breathing was influenced by biological sex.Approach.219 adults with no known acute or chronic lung disease were examined in sitting position with the EIT electrodes placed around the lower chest (6th intercostal space). EIT data were recorded at 33 images/s during quiet breathing for 60 s. Regional tidal impedance variation was calculated in all EIT image pixels and the spatial distribution of the values was determined using the established EIT measures of centre of ventilation in ventrodorsal (CoVvd) and right-to-left direction (CoVrl), the dorsal and right fraction of ventilation, and ventilation defect score.Main results.After exclusion of one subject due to insufficient electrode contact, 218 data sets were analysed (120 men, 98 women) (age: 53 ± 18 vs 50 ± 16 yr (p= 0.2607), body mass index: 26.4 ± 4.0 vs 26.4 ± 6.6 kg m-2(p= 0.9158), mean ± SD). Highly significant differences in ventilation distribution were identified between men and women between the right and left chest sides (CoVrl: 47.0 ± 2.9 vs 48.8 ± 3.3% of chest diameter (p< 0.0001), right fraction of ventilation: 0.573 ± 0.067 vs 0.539 ± 0.071 (p= 0.0004)) and less significant in the ventrodorsal direction (CoVvd: 55.6 ± 4.2 vs 54.5 ± 3.6% of chest diameter (p= 0.0364), dorsal fraction of ventilation: 0.650 ± 0.121 vs 0.625 ± 0.104 (p= 0.1155)). Ventilation defect score higher than one was found in 42.5% of men but only in 16.6% of women.Significance.Biological sex needs to be considered when EIT findings acquired in upright subjects in a rather caudal examination plane are interpreted. Sex differences in chest anatomy and thoracoabdominal mechanics may explain the results.

Unraveling the functional signals of rods and cones in the human retina: separation and analysis.

In recent years, optoretinography has become an important functional imaging method for the retina, as light-evoked changes in the photoreceptors have been demonstrated for a large number of different OCT systems. Full-field swept-source optical coherence tomography (FF-SS-OCT) is particularly phase-stable, and it is currently the only technique sensitive enough to detect the smaller functional changes in the inner plexiform layer (IPL). However, the resolution of state-of-the art FF-SS-OCT systems is not high enough to distinguish individual photoreceptors. This makes it difficult to separate rods from cones. In this work, we circumvent this problem by separating the functional changes in rods and cones by their different temporal dynamics to the same light stimulus. For this purpose, a mathematical model was developed that represents the measured signals as a superposition of two impulse responses. The developed model describes the measured data under different imaging conditions very well and is able to analyze the sensitivity and temporal dynamics of the two photoreceptor types separately.

COVID-19 is associated with changes in brain function and structure: A multimodal meta-analysis of neuroimaging studies.

The actual role of coronavirus disease 2019 (COVID-19) in brain damage has been increasingly reported, necessitating a meta-analysis to collate and summarize the inconsistent findings from functional imaging and voxel-based morphometry (VBM) studies. A comprehensive voxel-wise meta-analysis of the whole brain was conducted to identify alterations in functional activity and gray matter volume (GMV) between COVID-19 patients and healthy controls (HCs) by using Seed-based d Mapping software. We included 15 functional imaging studies (484 patients with COVID-19, 534 HCs) and 9 VBM studies (449 patients with COVID-19, 388 HCs) in the analysis. Overall, patients with COVID-19 exhibited decreased functional activity in the right superior temporal gyrus (STG) (extending to the right middle and inferior temporal gyrus, insula, and temporal pole [TP]), left insula, right orbitofrontal cortex (OFC) (extending to the right olfactory cortex), and left cerebellum compared to HCs. For VBM, patients with COVID-19, relative to HCs, showed decreased GMV in the bilateral anterior cingulate cortex/medial prefrontal cortex (extending to the bilateral OFC), and left cerebellum, and increased GMV in the bilateral amygdala (extending to the bilateral hippocampus, STG, TP, MTG, and right striatum). Moreover, overlapping analysis revealed that patients with COVID-19 exhibited both decreased functional activity and increased GMV in the right TP (extending to the right STG). The multimodal meta-analysis suggests that brain changes of function and structure in the temporal lobe, OFC and cerebellum, and functional or structural alterations in the insula and the limbic system in COVID-19. These findings contribute to a better understanding of the pathophysiology of brain alterations in COVID-19. SIGNIFICANCE STATEMENT: This first large-scale multimodal meta-analysis collates existing neuroimaging studies and provides voxel-wise functional and structural whole-brain abnormalities in COVID-19. Findings of this meta-analysis provide valuable insights into the dynamic brain changes (from infection to recovery) and offer further explanations for the pathophysiological basis of brain alterations in COVID-19.

Combining morphological and functional imaging parameters to diagnose primary bone neoplasms in the skull base, spine and sacrum.

PURPOSE: Morphological magnetic resonance (MR) and computed tomography (CT) features are used in combination with histology for diagnosis and treatment selection of primary bone neoplasms. Isolated functional MRI parameters have shown potential in diagnosis. Our goal is to facilitate diagnosis of primary bone neoplasms of the skull base, mobile spine and sacrum, by a comprehensive approach, combining morphological and functional imaging parameters. MATERIALS AND METHODS: Pre-treatment MR of 80 patients with histologically proven diagnosis of a primary bone neoplasm of the skull base, mobile spine and sacrum were retrospectively analyzed for morphological and functional MRI parameters. Functional parameters were measured in 4 circular regions of interest per tumor placed on non-adjacent scan slices. Differences in values of functional parameters between different histologies were analyzed with Dunn's test. RESULTS: Chordomas were the predominant histology (60.0%). Most neoplasms (80.0%) originated in the midline and had geographical (78.2%) bone destruction. Amorphous-type calcification (pre-existing bone) was seen only in chordomas. Homogeneous contrast enhancement pattern was seen only in chondrosarcoma and plasmacytoma. Ktrans and Kep were significantly lower in both chordoma, and chondrosarcoma compared to giant cell tumor of the bone (p = 0.006 - 0.011), and plasmacytoma (p = 0.004 - 0.014). Highest diffusion-weighted MRI apparent diffusion coefficient (ADC) values corresponded to chondrosarcoma and were significantly higher to those of chordoma (p = 0.008). CONCLUSION: We identified the most discriminating morphological parameters and added functional MR parameters based on histopathological features that are useful in making a confident diagnosis of primary bone neoplasms in the skull base, mobile spine and sacrum.

Resection of meningiomas located in motor eloquent areas - comparative analysis of navigated transcranial magnetic stimulation and conventional neuronavigation.

BACKGROUND: Navigated transcranial magnetic stimulation (nTMS) has been established as a preoperative diagnostic procedure in glioma surgery, increasing the extent of resection and preserving functional outcome. nTMS motor mapping for the resection of motor eloquent meningiomas has not been evaluated in a comparative analysis, yet. METHODS: We conducted a retrospective matched-pair analysis for tumor location and size in meningioma patients with tumors located over or close to the primary motor cortex. Half of the study population received nTMS motor mapping preoperatively (nTMS-group). The primary endpoint were permanent surgery-related motor deficits. Additional factors associated with new motor deficits were evaluated apart from nTMS. RESULTS: 62 patients (mean age 62 ± 15.8 years) were evaluated. 31 patients received preoperative nTMS motor mapping. In this group, motor thresholds (rMT) corresponded with tumor location and preoperative motor status, but could not predict motor outcome. No patient with preoperative intact motor function had a surgery-related permanent deficit in the nTMS group whereas four patients in the non-TMS group with preoperative intact motor status harbored from permanent deficits. 13 patients (21.3%) had a permanent motor deficit postoperatively with no difference between the nTMS and the non-TMS-group. Worsening in motor function was associated with higher patient age (p = 0.01) and contact to the superior sagittal sinus (p = 0.027). CONCLUSION: nTMSmotor mapping did not lead to postoperative preservation in motorfunction. nTMS data corresponded well with the preoperative motorstatus and were associated with postoperative permanent deficits if tumors were located over the motor hotspot according to nTMS.

Symptomatic Myeloma: PET, Whole-Body MR Imaging with Diffusion-Weighted Imaging or Both.

According to international guidelines, patients with suspected myeloma should primarily undergo low-dose whole-body computed tomography (CT) for diagnostic purposes. To optimize sensitivity and specificity and enable treatment response assessment, whole-body MR (WB-MR) imaging should include diffusion-weighted imaging with apparent diffusion coefficient maps and T1-weighted Dixon sequences with bone marrow Fat Fraction Quantification. At baseline WB-MR imaging shows greater sensitivity for the detecting focal lesions and diffuse bone marrow infiltration pattern than 18F-fluorodeoxyglucose PET-CT, which is considered of choice for evaluating response to treatment and minimal residual disease and imaging of extramedullary disease.

Contrast agent-free functional magnetic resonance imaging with matrix pencil decomposition to quantify abnormalities in lung perfusion and ventilation in patients with cystic fibrosis.

Background: Previous studies showed that contrast-enhanced (CE) morpho-functional magnetic resonance imaging (MRI) detects abnormalities in lung morphology and perfusion in patients with cystic fibrosis (CF). Novel matrix pencil decomposition MRI (MP-MRI) enables quantification of lung perfusion and ventilation without intravenous contrast agent administration. Objectives: To compare MP-MRI with established morpho-functional MRI and spirometry in patients with CF. Methods: Thirty-nine clinically stable patients with CF (mean age 21.6 ± 10.7 years, range 8-45 years) prospectively underwent morpho-functional MRI including CE perfusion MRI, MP-MRI and spirometry. Two blinded chest radiologists assessed morpho-functional MRI and MP-MRI employing the validated chest MRI score. In addition, MP-MRI data were processed by automated software calculating perfusion defect percentage (QDP) and ventilation defect percentage (VDP). Results: MP perfusion score and QDP correlated strongly with the CE perfusion score (both r = 0.81; p < 0.01). MP ventilation score and VDP showed strong inverse correlations with percent predicted FEV1 (r = -0.75 and r = -0.83; p < 0.01). The comparison of visual and automated parameters showed that both MP perfusion score and QDP, and MP ventilation score and VDP were strongly correlated (r = 0.74 and r = 0.78; both p < 0.01). Further, the MP perfusion score and MP ventilation score, as well as QDP and VDP were strongly correlated (r = 0.88 and r = 0.86; both p < 0.01). Conclusion: MP-MRI detects abnormalities in lung perfusion and ventilation in patients with CF without intravenous or inhaled contrast agent application, and correlates strongly with the well-established CE perfusion MRI score and spirometry. Automated analysis of MP-MRI may serve as quantitative noninvasive outcome measure for diagnostic monitoring and clinical trials.

Ring-shaped odor coding in the antennal lobe of migratory locusts.

The representation of odors in the locust antennal lobe with its >2,000 glomeruli has long remained a perplexing puzzle. We employed the CRISPR-Cas9 system to generate transgenic locusts expressing the genetically encoded calcium indicator GCaMP in olfactory sensory neurons. Using two-photon functional imaging, we mapped the spatial activation patterns representing a wide range of ecologically relevant odors across all six developmental stages. Our findings reveal a functionally ring-shaped organization of the antennal lobe composed of specific glomerular clusters. This configuration establishes an odor-specific chemotopic representation by encoding different chemical classes and ecologically distinct odors in the form of glomerular rings. The ring-shaped glomerular arrangement, which we confirm by selective targeting of OR70a-expressing sensory neurons, occurs throughout development, and the odor-coding pattern within the glomerular population is consistent across developmental stages. Mechanistically, this unconventional spatial olfactory code reflects the locust-specific and multiplexed glomerular innervation pattern of the antennal lobe.

[Artificial intelligence (AI) in diagnostic and therapeutic decision-making-a tool or communication partner?] / Künstliche Intelligenz (KI) bei Diagnostik- und Therapieentscheidungen ­ Einsatz als Werkzeug oder als Kommunikationspartner?

Artificial intelligence (AI) is a tool that is only as good as its user. In the case of humanoid robots, an AI system can be seen as a social counterpart. Decision intelligence (DI) is a term that stems from engineering. DI as a science is used to process data with findings from the social sciences and decision theories. The aim is to improve decision-making processes. However, AI should be categorized as a tool and not as a communication partner. AI analyzes information from studies, guidelines, and textbooks from the outset-taking individual patient information into account. Physicians with a high level of clinical expertise can ask more specific questions about the latter. ChatGPT is trained with millions of texts from the internet, social media, online forums, journal articles, and books; it covers almost all areas of life.

Combination of static and dynamic neural imaging features to distinguish sensorineural hearing loss: a machine learning study.

Purpose: Sensorineural hearing loss (SNHL) is the most common form of sensory deprivation and is often unrecognized by patients, inducing not only auditory but also nonauditory symptoms. Data-driven classifier modeling with the combination of neural static and dynamic imaging features could be effectively used to classify SNHL individuals and healthy controls (HCs). Methods: We conducted hearing evaluation, neurological scale tests and resting-state MRI on 110 SNHL patients and 106 HCs. A total of 1,267 static and dynamic imaging characteristics were extracted from MRI data, and three methods of feature selection were computed, including the Spearman rank correlation test, least absolute shrinkage and selection operator (LASSO) and t test as well as LASSO. Linear, polynomial, radial basis functional kernel (RBF) and sigmoid support vector machine (SVM) models were chosen as the classifiers with fivefold cross-validation. The receiver operating characteristic curve, area under the curve (AUC), sensitivity, specificity and accuracy were calculated for each model. Results: SNHL subjects had higher hearing thresholds in each frequency, as well as worse performance in cognitive and emotional evaluations, than HCs. After comparison, the selected brain regions using LASSO based on static and dynamic features were consistent with the between-group analysis, including auditory and nonauditory areas. The subsequent AUCs of the four SVM models (linear, polynomial, RBF and sigmoid) were as follows: 0.8075, 0.7340, 0.8462 and 0.8562. The RBF and sigmoid SVM had relatively higher accuracy, sensitivity and specificity. Conclusion: Our research raised attention to static and dynamic alterations underlying hearing deprivation. Machine learning-based models may provide several useful biomarkers for the classification and diagnosis of SNHL.

Establishing a 4D-CT lung function related volumetric dose model to reduce radiation pneumonia.

In order to study how to use pulmonary functional imaging obtained through 4D-CT fusion for radiotherapy planning, and transform traditional dose volume parameters into functional dose volume parameters, a functional dose volume parameter model that may reduce level 2 and above radiation pneumonia was obtained. 41 pulmonary tumor patients who underwent 4D-CT in our department from 2020 to 2023 were included. MIM Software (MIM 7.0.7; MIM Software Inc., Cleveland, OH, USA) was used to register adjacent phase CT images in the 4D-CT series. The three-dimensional displacement vector of CT pixels was obtained when changing from one respiratory state to another respiratory state, and this three-dimensional vector was quantitatively analyzed. Thus, a color schematic diagram reflecting the degree of changes in lung CT pixels during the breathing process, namely the distribution of ventilation function strength, is obtained. Finally, this diagram is fused with the localization CT image. Select areas with Jacobi > 1.2 as high lung function areas and outline them as fLung. Import the patient's DVH image again, fuse the lung ventilation image with the localization CT image, and obtain the volume of fLung different doses (V60, V55, V50, V45, V40, V35, V30, V25, V20, V15, V10, V5). Analyze the functional dose volume parameters related to the risk of level 2 and above radiation pneumonia using R language and create a predictive model. By using stepwise regression and optimal subset method to screen for independent variables V35, V30, V25, V20, V15, and V10, the prediction formula was obtained as follows: Risk = 0.23656-0.13784 * V35 + 0.37445 * V30-0.38317 * V25 + 0.21341 * V20-0.10209 * V15 + 0.03815 * V10. These six independent variables were analyzed using a column chart, and a calibration curve was drawn using the calibrate function. It was found that the Bias corrected line and the Apparent line were very close to the Ideal line, The consistency between the predicted value and the actual value is very good. By using the ROC function to plot the ROC curve and calculating the area under the curve: 0.8475, 95% CI 0.7237-0.9713, it can also be determined that the accuracy of the model is very high. In addition, we also used Lasso method and random forest method to filter out independent variables with different results, but the calibration curve drawn by the calibration function confirmed poor prediction performance. The function dose volume parameters V35, V30, V25, V20, V15, and V10 obtained through 4D-CT are key factors affecting radiation pneumonia. Establishing a predictive model can provide more accurate lung restriction basis for clinical radiotherapy planning.

Multimodal neuroimaging fusion unravel structural-functional-neurotransmitter change in Parkinson's disease with impulse control disorders.

BACKGROUND: Impulse control disorders (ICD) in Parkinson's disease (PD) is highly multifactorial in etiology and has intricate neural mechanisms. Our multimodal neuroimaging study aimed to investigate the specific patterns of structure-function-neurotransmitter interactions underlying ICD. METHODS: Thirty PD patients with ICD (PD-ICD), 30 without ICD (PD-NICD) and 32 healthy controls (HCs) were recruited. Gyrification and perivascular spaces (PVS) were computed to capture the alternations of cortical surface morphology and glymphatic function. Seed-based functional connectivity (FC) were performed to identify the corresponding functional changes. Further, JuSpace toolbox were employed for cross-modal correlations to evaluate whether the spatial patterns of functional alterations in ICD patients were associated with specific neurotransmitter system. RESULTS: Compared to PD-NICD, PD-ICD patients showed hypogyrification and enlarged PVS volume fraction in the left orbitofrontal gyrus (OFG), as well as decreased FC between interhemispheric OFG. The interhemispheric OFG connectivity reduction was associated with spatial distribution of µ-opioid pathway (r = -0.186, p = 0.029, false discovery rate corrected). ICD severity was positively associated with the PVS volume fraction of left OFG (r = 0.422, p = 0.032). Furthermore, gyrification index (LGI) and percent PVS (pPVS) in OFG and their combined indicator showed good performance in differentiating PD-ICD from PD-NICD. CONCLUSIONS: Our findings indicated that the co-altered structure-function-neurotransmitter interactions of OFG might be involved in the pathogenesis of ICD.

18F-fluoro-ethyl-tyrosine PET co-registered with MRI in patients with persisting acromegaly.

OBJECTIVE: To report our experience with 18F-fluoro-ethyl-tyrosine (FET) positron emission tomography-computed tomography (PET-CT) co-registered with magnetic resonance imaging (MRI) (FET-PET/MRICR) in the care trajectory for persistent acromegaly. DESIGN: Prospective case series. PATIENTS: Ten patients with insufficiently controlled acromegaly referred to our team to evaluate surgical options. MEASUREMENTS: FET-PET/MRICR was used to support decision-making if MRI alone and multidisciplinary team evaluation did not provide sufficient clarity to proceed to surgery. RESULTS: FET-PET/MRICR showed suspicious (para)sellar tracer uptake in all patients. In five patients FET-PET/MRICR was fully concordant with conventional MRI, and in one patient partially concordant. FET-PET/MRICR identified suggestive new foci in four other patients. Surgical re-exploration was performed in nine patients (aimed at total resection (6), debulking (2), diagnosis (1)), and one patient underwent radiation therapy. In 7 of 9 (78%) operated patients FET-PET/MRICR findings were confirmed intraoperatively, and in six (67%) also histologically. IGF-1 decreased significantly in eight patients (89%). All patients showed clinical improvement. Complete biochemical remission was achieved in three patients (50% of procedures in which total resection was anticipated feasible). Biochemistry improved in five and was unchanged in one patient. No permanent complications occurred. At six months, optimal outcome (preoperative intended goal achieved without permanent complications) was achieved in six (67%) patients and an intermediate outcome (goal not achieved, but no complications) in the other three patients. CONCLUSIONS: In patients with persisting acromegaly without a clear surgical target on MRI, FET-PET/MRICR is a new tracer to provide additional information to aid decision-making by the multidisciplinary pituitary team.

Indirect functional connectivity does not predict overall survival in glioblastoma.

BACKGROUND: Lesion network mapping (LNM) is a popular framework to assess clinical syndromes following brain injury. The classical approach involves embedding lesions from patients into a normative functional connectome and using the corresponding functional maps as proxies for disconnections. However, previous studies indicated limited predictive power of this approach in behavioral deficits. We hypothesized similarly low predictiveness for overall survival (OS) in glioblastoma (GBM). METHODS: A retrospective dataset of patients with GBM was included (n = 99). Lesion masks were registered in the normative space to compute disconnectivity maps. The brain functional normative connectome consisted in data from 173 healthy subjects obtained from the Human Connectome Project. A modified version of the LNM was then applied to core regions of GBM masks. Linear regression, classification, and principal component (PCA) analyses were conducted to explore the relationship between disconnectivity and OS. OS was considered both as continuous and categorical (low, intermediate, and high survival) variable. RESULTS: The results revealed no significant associations between OS and network disconnection strength when analyzed at both voxel-wise and classification levels. Moreover, patients stratified into different OS groups did not exhibit significant differences in network connectivity patterns. The spatial similarity among the first PCA of network maps for each OS group suggested a lack of distinctive network patterns associated with survival duration. CONCLUSIONS: Compared with indirect structural measures, functional indirect mapping does not provide significant predictive power for OS in patients with GBM. These findings are consistent with previous research that demonstrated the limitations of indirect functional measures in predicting clinical outcomes, underscoring the need for more comprehensive methodologies and a deeper understanding of the factors influencing clinical outcomes in this challenging disease.

[PET/CT in radiotherapy : indications and potential applications]. / TEP/TDM en radiothérapie : indications et perspectives.

Functional imaging, including positron emission tomography combined with computed tomography (PET/CT), allows the evaluation of numerous biological properties that could be considered at all steps of the therapeutic management of patients treated with radiotherapy. Indeed, it enables better initial staging of the disease, and some parameters may also be used as predictive biomarkers for treatment response, allowing better selection of patients eligible for radiotherapy. It may also improve the definition of target volumes with the aim of dose escalations by dose-painting. Finally, it could be useful during the follow-up to assess response to treatment. In this review, we report how functional imaging is integrated at the present time during the radiotherapy procedure, and what are its potential future contributions.

L'imagerie fonctionnelle, dont la tomographie par émission de positons couplée à la tomodensitométrie (TEP/TDM), permet l'évaluation de nombreuses propriétés biologiques qui pourraient être prises en compte à toutes les étapes de la prise en charge des patients traités par radiothérapie. En effet, elle permet une meilleure stadification initiale de la maladie, et certains paramètres peuvent également être utilisés comme biomarqueurs prédictifs de la réponse au traitement, permettant ainsi une meilleure sélection des patients éligibles à la radiothérapie. Elle peut également améliorer la définition des volumes cibles dans le but d'escalader la dose par dose-painting. Enfin, elle pourrait être utile lors du suivi pour évaluer la réponse au traitement. Dans cette revue, nous rapportons comment l'imagerie fonctionnelle est intégrée, à l'heure actuelle, au cours d'un traitement par radiothérapie, et nous discutons quelles sont ses futures contributions potentielles dans les principales localisations tumorales où la radiothérapie est recommandée.

Label-Free Functional Imaging of Vagus Nerve Stimulation-Evoked Potentials at the Cortical Surface.

Vagus Nerve Stimulation (VNS) was the first FDA-approved stimulation therapy to treat patients with refractory epilepsy and remains widely used. The mechanisms behind the therapeutic effect of VNS remain unknown but are thought to involve afferent-mediated modulation to cortical circuits 1. In this work, we use a coherent holographic imaging system to characterize vagus nerve evoked potentials (VEPs) in the cortex in response to typical VNS stimulation paradigms, which does not require electrode placement nor any genetic, structural, or functional labels. We find that stimulation amplitude strongly modulates VEPs response magnitude (effect size 0.401), while pulse width has a moderate modulatory effect (effect size 0.127) and frequency has almost no modulatory effect (effect size 0.009) on the evoked potential magnitude. We find mild interaction between pulse width and frequency. This non-contact label-free functional imaging technique could serve as a non-invasive rapid feedback tool to quantify VEPs and could increase the efficacy of VNS in patients with refractory epilepsy.

[99mTc]Tc-labeled cyc-DX600-HYNIC as a SPECT probe for ACE2-specific pancreatic cancer imaging.

As a regulator in renin-angiotensin-aldosterone system, angiotensin-converting enzyme 2 (ACE2) closely correlated with tumor progression of pancreatic cancer, meantime, was easily affected by a variety of factors. [99mTc]Tc-cyc-DX600 SPECT was established as an ACE2-specific imaging protocol to figure out the ACE2 status in pancreatic tumor. BALB/C-NU mice were used to prepare the subcutaneous cell derived xenograft (CDX) models with HEK-293T or HEK-293T/hACE2 cells to validate ACE2 specificity of [99mTc]Tc-cyc-DX600 SPECT and establish SPECT imaging protocol. On the basis of [99mTc]Tc-cyc-DX600 SPECT and [18F]F-FDG PET/CT, ACE2-dependence on tumor size and tumor metabolism were further verified on orthotopic pancreatic cancer model with KPC cells. Immunohistochemical analysis was used to demonstrate the findings on ACE2 SPECT. [99mTc]Tc-cyc-DX600 was of superior tumor uptake in HEK-293T/hACE2 CDX than wild type (6.74 ± 0.31 %ID/mL vs 1.83 ± 0.26 %ID/mL at 1.5 h post injection (p.i.); 3.14 ± 0.31 %ID/mL vs 1.16 ± 0.15 %ID/mL at 4.5 h p.i.). For the CDX models with PANC-1 cells, a significant negative correlation between the slope of tumor volume and tumor uptake was observed (r = -0.382 for the 1-4th day; r = -0.146 for the 1-5th day; r = -0.114 for the 1-6th day; r = -0.152 for the 1-7th day; but P > 0.05 for all). For orthotopic pancreatic cancer model, the linear correlation between FDG PET and ACE2 SPECT of the pancreatic lesions was negative (r = -0.878), the quantitative values of ACE2 SPCET was positively correlated with the volume of primary lesions (r = 0.752) and also positively correlated with the quantitative values of ACE2 immunohistochemical analysis (r = 0.991). Conclusively, [99mTc]Tc-cyc-DX600 SPECT is an ACE2-specific imaging protocol with clinical translational potential, adding multidimensional information on the disease progression of pancreatic cancer.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Significance: Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. Aim: We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Approach: Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Results: Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p=0.042). In addition, the change in normalized tumor StO2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p=0.038). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. Conclusions: These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

Systematic review and meta-analysis: multimodal functional and anatomical neural alterations in autism spectrum disorder.

BACKGROUND: This meta-analysis aimed to explore the most robust findings across numerous existing resting-state functional imaging and voxel-based morphometry (VBM) studies on the functional and structural brain alterations in individuals with autism spectrum disorder (ASD). METHODS: A whole-brain voxel-wise meta-analysis was conducted to compare the differences in the intrinsic functional activity and gray matter volume (GMV) between individuals with ASD and typically developing individuals (TDs) using Seed-based d Mapping software. RESULTS: A total of 23 functional imaging studies (786 ASD, 710 TDs) and 52 VBM studies (1728 ASD, 1747 TDs) were included. Compared with TDs, individuals with ASD displayed resting-state functional decreases in the left insula (extending to left superior temporal gyrus [STG]), bilateral anterior cingulate cortex/medial prefrontal cortex (ACC/mPFC), left angular gyrus and right inferior temporal gyrus, as well as increases in the right supplementary motor area and precuneus. For VBM meta-analysis, individuals with ASD displayed decreased GMV in the ACC/mPFC and left cerebellum, and increased GMV in the left middle temporal gyrus (extending to the left insula and STG), bilateral olfactory cortex, and right precentral gyrus. Further, individuals with ASD displayed decreased resting-state functional activity and increased GMV in the left insula after overlapping the functional and structural differences. CONCLUSIONS: The present multimodal meta-analysis demonstrated that ASD exhibited similar alterations in both function and structure of the insula and ACC/mPFC, and functional or structural alterations in the default mode network (DMN), primary motor and sensory regions. These findings contribute to further understanding of the pathophysiology of ASD.

Computational modeling of light processing in the habenula and dorsal raphe based on laser ablation of functionally-defined cells.

BACKGROUND: The habenula is a major regulator of serotonergic neurons in the dorsal raphe, and thus of brain state. The functional connectivity between these regions is incompletely characterized. Here, we use the ability of changes in irradiance to trigger reproducible changes in activity in the habenula and dorsal raphe of zebrafish larvae, combined with two-photon laser ablation of specific neurons, to establish causal relationships. RESULTS: Neurons in the habenula can show an excitatory response to the onset or offset of light, while neurons in the anterior dorsal raphe display an inhibitory response to light, as assessed by calcium imaging. The raphe response changed in a complex way following ablations in the dorsal habenula (dHb) and ventral habenula (vHb). After ablation of the ON cells in the vHb (V-ON), the raphe displayed no response to light. After ablation of the OFF cells in the vHb (V-OFF), the raphe displayed an excitatory response to darkness. After ablation of the ON cells in the dHb (D-ON), the raphe displayed an excitatory response to light. We sought to develop in silico models that could recapitulate the response of raphe neurons as a function of the ON and OFF cells of the habenula. Early attempts at mechanistic modeling using ordinary differential equation (ODE) failed to capture observed raphe responses accurately. However, a simple two-layer fully connected neural network (NN) model was successful at recapitulating the diversity of observed phenotypes with root-mean-squared error values ranging from 0.012 to 0.043. The NN model also estimated the raphe response to ablation of D-off cells, which can be verified via future experiments. CONCLUSION: Lesioning specific cells in different regions of habenula led to qualitatively different responses to light in the dorsal raphe. A simple neural network is capable of mimicking experimental observations. This work illustrates the ability of computational modeling to integrate complex observations into a simple compact formalism for generating testable hypotheses, and for guiding the design of biological experiments.