Accurate and comprehensive preoperative staging is one of the most important prognostic factors for the management of esophageal cancer (EC). We aimed to develop and validate predictive models using radiomics from preoperative contrast-enhanced Computed Tomography (CT) images to assess pathological staging in EC patients. This study retrospectively included 161 patients who underwent esophagectomy at Sichuan Cancer Hospital from July 2018 to February 2023. Pathological staging outcomes encompassed overall TNM staging, T and N staging, and tumor progressions (vascular invasion and perineural invasion). Radiomics features were extracted from segmented regions of tumors. A radiomic signature (Rad-signature) for each outcome was developed using a fivefold cross-validation least absolute shrinkage and selection operator (LASSO) regression model within the training cohort and subsequently validated in the test cohort for predictive accuracy. Out of the 851 radiomics features extracted, two were selected to formulate the Rad-signature for each staging outcome. These signatures showed a significant correlation with their respective outcomes in both the training set and the testing set. Furthermore, the Rad-signature exhibited favorable predictive performance for advanced pTNM staging, advanced pT staging, vascular invasion and perineural invasion, with AUC of 0.721 [95%CI, 0.570–0.872], 0.900 [95%CI 0.805–0.995], 0.824 [0.686–0.961], and 0.737 [0.586–0.887], respectively. However, the predictive performance of the Rad-signature for pN staging is moderate (AUC = 0.693 [0.534–0.852]), indicating needs for additional data modalities. This study established a non-invasive preoperative radiomics model that demonstrated good predictive performance in determining the pTNM staging, pT staging, vascular invasion, and perineural invasion for EC patients. These results could inform personalized treatment strategies and improve outcomes for EC patients.
Abstract Background The cardiac magnetic resonance tissue tracking (CMR-TT) technique was used to obtain left atrial strain and strain rate in patients with myocardial infarction (MI) and to evaluate the utility of this technique in the quantitative assessment of myocardial infarction for distinguishing acute from chronic myocardial infarction. Methods We retrospectively analyzed 36 consecutive patients with acute myocardial infarction (AMI) and 29 patients with chronic myocardial infarction (CMI) who underwent CMR and 30 controls. Left atrial (LA) and ventricular functions were quantified by volumetric, and CMR-TT derived strain analysis from long and short left ventricular view cines. Receiver Operating Characteristics (ROC) analysis was used to determine the diagnostic accuracy of CMR-TT strain parameters for discriminating between acute and chronic myocardial infarction. Results AMI and CMI participants had impaired LA reservoir function, conduit function and LA booster pump dysfunction compared to the controls. LA strain was more sensitive than LV global strain for the assessment of the MI stage. Peak late-negative SR yielded the best areas under the ROC curve (AUC) of 0.879, showing differentiation between acute and chronic myocardial infarction of all the LA strain parameters obtained. The highest significant differences between chronic myocardial infarction and normal myocardium were also found in the LV strain ( p < 0.001) and LA functional parameters ( p < 0.001), but there was no difference between AMI and normals. Conclusions CMR-TT-derived LA strain is a potential and robust tool in demonstrating impaired LA mechanics and quantifying LA dynamics, which have high sensitivity and specificity in the differential diagnosis of acute versus chronic myocardial infarction. Their use is thus worth popularizing in clinical application.
The purpose of this study was to explore the resting-state functional connectivity (FC) changes among the pain matrix and other brain regions in herpes zoster (HZ) and postherpetic neuralgia (PHN) patients. Fifty-four PHN patients, 52 HZ patients, and 54 healthy controls (HCs) underwent resting-state functional magnetic resonance imaging (rs-fMRI) scans. We used a seed-based FC approach to investigate whether HZ and PHN patients exhibited abnormal FC between the pain matrix and other brain regions compared to HCs. A random forest (RF) model was constructed to explore the feasibility of potential neuroimaging indicators to distinguish the two groups of patients. We found that PHN patients exhibited decreased FCs between the pain matrix and the putamen, superior temporal gyrus, middle frontal gyrus, middle cingulate gyrus, amygdala, precuneus, and supplementary motor area compared with HCs. Similar results were observed in HZ patients. The disease durations of PHN patients were negatively correlated with those aforementioned impaired FCs. The results of machine learning experiments showed that the RF model combined with FC features achieved a classification accuracy of 75%. Disrupted FC among the pain matrix and other regions in HZ and PHN patients may affect multiple dimensions of pain processing.
Abstract Postherpetic neuralgia (PHN) is a neuropathic pain syndrome characterized by persistent burning or stinging pain, and its underlying pathogenesis is still unclear. Although conventional resting-state magnetic resonance imaging (rs-fMRI) studies have revealed abnormal resting-state functional connectivity (rsFC) in PHN patients, dynamic functional connectivity (dFC) remains unexplored. In this paper, a sliding time window method was used to generate a dFC matrix, and rs-fMRI data from 55 PHN patients, 55 Herpes Zoster (HZ) patients, and 50 healthy controls (HCs) were analyzed. Machine learning was used to determine whether these abnormal dFC values could be used as neuroimaging markers of the transition from HZ to PHN. All dFC matrices were clustered into two reoccurring states, and the state transition metrics were obtained. We found that patients with PHN were in State 1, which is characterized by weak connections between the networks, more often than patients with HZ (p < 0.05). We also found that in State 1, compared with that in HCs, the dFC between the BGN and SN in HZ patients increased. In State 2, the dFC of PHN patients was lower than that of HZ patients and HCs, and the dFC was mainly observed in the DMN, SN, DAN, VN and LN. The results of the SVM classifier revealed that the change in dFC between the BGN and DMN may be a strong neuroimaging marker of the transition from HZ to PHN. These findings further our understanding of the neuropathological mechanism of PHN.
Resting-state functional magnetic resonance imaging (rs-fMRI) and Granger causality analysis (GCA) were used to observe the characteristics of amygdala and whole-brain effect connections in patients with herpes zoster (HZ) and post-herpetic neuralgia (PHN) and to determine their relationship with clinical features.
To review and analyze the functional connectivity (FC) abnormalities in the brain olfactory network (ON) of patients with chronic rhinosinusitis with olfactory dysfunction (CRSwOD) and explore the relationship between these FC abnormalities and olfactory dysfunction, providing clues to the neurophysiological mechanisms underlying CRSwOD.FC analysis on the ON of patients with CRSwOD and patients with chronic rhinosinusitis without olfactory dysfunction (CRSsOD) identified the regions of the ON with abnormal FC in CRSwOD patients, and the correlation between abnormal FC and clinical scales for chronic rhinosinusitis was analyzed.(1) Compared with the CRSsOD group, CRSwOD patients showed decreased FC between the bilateral orbitofrontal cortex (OFC) and the right middle frontal gyrus, (2) Receiver operating characteristic (ROC) curve analysis revealed that the FC value between the right middle frontal gyrus and the left OFC (area under the curve (AUC) = 0.852, sensitivity: 0.821, specificity: 0.800, p < 0.001) was more capable of distinguishing whether CRS patients may have olfactory dysfunction than the FC value between the right middle frontal gyrus and the right OFC (AUC = 0.827, sensitivity: 0.893, specificity: 0.667, p < 0.001), and (3) Lund-Kennedy scores were positively correlated with the FC values between the right middle frontal gyrus and the left OFC (r = 0.443, p < 0.018). Lund-Mackay scores were also positively correlated with the FC values between the right middle frontal gyrus and the left OFC (r = 0.468, p < 0.012). Questionnaire of Olfactory Disorders-Negative Statements scores were negatively correlated with the FC values between the right middle frontal gyrus and the left OFC (r = -0.481, p < 0.001).Persistent nasal inflammation affects the FC between the middle frontal gyrus and the OFC, which may serve as a potential imaging marker for identifying CRSwOD. The severity of nasal inflammation and olfactory damage is closely related to the FC between the middle frontal gyrus and OFC, and the abnormal changes in this FC can be used to explain the neurophysiological mechanisms behind the occurrence of olfactory dysfunction in patients.
To investigate the presence of modular loss of coupling and abnormal alterations in functional and structural networks in the brain networks of patients with postherpetic neuralgia (PHN). We collected resting-state functional magnetic resonance imaging data and diffusion tensor imaging data from 82 healthy controls (HCs) and 71 PHN patients, generated structural connectivity (SC) and functional connectivity (FC) networks, and assessed the corresponding clinical information assessment. Based on AAL(90) mapping, the brain network was divided into 9 modules, and the structural–functional connectivity (SC–FC) coupling was compared at the whole-brain level and within the modules, as well as alterations in the topological properties of the brain network in the patient group. Finally, correlation analyses were performed using the following clinical scales: Visual Analogue Scale (VAS), Hamilton Anxiety Scale (HAMA), and Hamilton Depression Scale (HAMD). Compared with HCs, patients with PHN had reduced global efficiency (Eg) and local efficiency (Eloc) of structural and functional networks. The FC in the PHN group presented abnormal node clustering coefficients (NCp), local node efficiencies (NLe), and node efficiencies (Ne), and the SC presented abnormal node degrees (Dc), NCp, NLe, characteristic path lengths (NLp), and Ne. In addition, SC–FC coupling was reduced in the patient default network (DMN), salient network (SN), and visual network (VIS). Moreover, the degree of impairment of graph theory indicators was significantly positively correlated with scales such as VAS scores, and the coupling of modules was significantly negatively correlated with the early course of the patient's disease. Large-scale impaired topological properties of the FC and SC networks were observed in patients with PHN, and SC–FC decoupling was detected in these modules of the DMN, SN, and VIS. These aberrant alterations may have led to over-transmission of pain information or central sensitization of pain.
This study aimed to explore the abnormal changes in short- and long-range functional connectivity density (FCD) in patients with herpes zoster (HZ) and postherpetic neuralgia (PHN).
AbstractOBJECTIVE: This study aimed to investigate the changes in resting-state functional connectivity (rsFC) of the sensorimotor network(SMN) in patients with herpes zoster(HZ) and postherpetic neuralgia patients(PHN). Then, We applied machine learning to distinguish PHN/HZ patients from healthy controls(HC). METHODS: HZ (n=53), PHN (n=57), and HC (n=50) were included, and resting-state functional magnetic resonance imaging (rs-fMRI) was performed on them. Seed-based and ROI-to-ROI analyses were applied to evaluate connectivity inside and between the SMN and other voxels throughout the brain. After that, we used machine learning to separate patients with PHN/HZ from those with HC. RESULTS: Compared to HC, there was a substantial reduction in functional connectivity between the lateral SMN (R), lateral SMN (L), and superior SMN in PHN patients. There was a disruption of rsFC between SMN subregions and several brain regions (insula, parietal, occipital, and superior frontal gyrus) in PHN. These damaged FCs were linked positively with clinical data (such as mood scores, disease duration, and VAS scores). Furthermore, We discovered that the rsFC value of SMN could successfully classify PHN patients from other types of pain with an accuracy of 85.7% when applied to a machine-learning approach. CONCLUSION: Significant changes occurred in the rsFC of SMN in HZ and PHN. Suggesting that the role of SMN in HZ/PHN may help understand the pathophysiology and development of these diseases.
'/%3e%3cuse xlink:href='%23a' transform='rotate(23.036 .093 25.536)'/%3e%3cuse xlink:href='%23a' transform='rotate(45.87 1.273 16.18)'/%3e%3cuse xlink:href='%23a' transform='rotate(69.945 .996 12.078)'/%3e%3cuse xlink:href='%23a' transform='rotate(20.66 -19.689 31.932)'/%3e%3c/svg%3e)