Automating Linear and Angular Measurements for the Hip and Knee After Computed Tomography: Validation of a Three-Stage Deep Learning and Computer Vision-Based Pipeline for Pathoanatomic Assessment.

Background: Variability in the bony morphology of pathologic hips/knees is a challenge in automating preoperative computed tomography (CT) scan measurements. With the increasing prevalence of CT for advanced preoperative planning, processing this data represents a critical bottleneck in presurgical planning, research, and development. The purpose of this study was to demonstrate a reproducible and scalable methodology for analyzing CT-based anatomy to process hip and knee anatomy for perioperative planning and execution. Methods: One hundred patients with preoperative CT scans undergoing total knee arthroplasty for osteoarthritis were processed. A two-step deep learning pipeline of classification and segmentation models was developed that identifies landmark images and then generates contour representations. We utilized an open-source computer vision library to compute measurements. Classification models were assessed by accuracy, precision, and recall. Segmentation models were evaluated using dice and mean Intersection over Union (IOU) metrics. Contour measurements were compared against manual measurements to validate posterior condylar axis angle, sulcus angle, trochlear groove-tibial tuberosity distance, acetabular anteversion, and femoral version. Results: Classifiers identified landmark images with accuracy of 0.91 and 0.88 for hip and knee models, respectively. Segmentation models demonstrated mean IOU scores above 0.95 with the highest dice coefficient of 0.957 [0.954-0.961] (UNet3+) and the highest mean IOU of 0.965 [0.961-0.969] (Attention U-Net). There were no statistically significant differences for the measurements taken automatically vs manually (P > 0.05). Average time for the pipeline to preprocess (48.65 +/- 4.41 sec), classify/retrieve landmark images (8.36 +/- 3.40 sec), segment images (<1 sec), and obtain measurements was 2.58 (+/- 1.92) minutes. Conclusions: A fully automated three-stage deep learning and computer vision-based pipeline of classification and segmentation models accurately localized, segmented, and measured landmark hip and knee images for patients undergoing total knee arthroplasty. Incorporation of clinical parameters, like patient-reported outcome measures and instability risk, will be important considerations alongside anatomic parameters.

Interstitial Optical Fiber-Mediated Multimodal Phototheranostics Based on an Aggregation-Induced NIR-II Emission Luminogen for Orthotopic Breast Cancer Treatment.

One-for-all phototheranostics based on a single molecule is recognized as a convenient approach for cancer treatment, whose efficacy relies on precise lesion localization through multimodal imaging, coupled with the efficient exertion of phototherapy. To unleash the full potential of phototheranostics, advancement in both phototheranostic agents and light delivery methods is essential. Herein, an integrated strategy combining a versatile molecule featuring aggregation-induced emission, namely tBuTTBD, with a modified optical fiber to realize comprehensive tumor diagnosis and "inside-out" irradiation in the orthotopic breast tumor, is proposed for the first time. Attributed to the intense donor-acceptor interaction, highly distorted conformation, abundant molecular rotors, and loose intermolecular packing upon aggregation, tBuTTBD can synchronously undergo second near-infrared (NIR-II) fluorescence emission, photothermal and photodynamic generation under laser irradiation, contributing to a trimodal NIR-II fluorescence-photoacoustic (PA)-photothermal imaging-guided phototherapy. The tumor treatment is further carried out following the insertion of a modified optical fiber, which is fabricated by splicing a flat-end fiber with an air-core fiber. This configuration aims to enable effective in situ phototherapy by maximizing energy utilization for therapeutic benefits. This work not only enriches the palette of NIR-II phototheranostic agents but also provides valuable insight for exploring an integrated phototheranostic protocol for practical cancer treatment.

Predictive value of CXCL1+_FAP+ phenotype in CAFs for distant metastasis and its correlation with PD-L1 expression in locoregionally advanced nasopharyngeal carcinoma patients.

OBJECTIVE: There is a lack of effective biomarkers for predicting the distant metastasis in nasopharyngeal carcinoma (NPC). We aimed to explore the expression of FAP+Cancer-associated fibroblasts (CAFs) derived CXCL1 in NPC and its predictive values for distant metastasis and correlation with PD-L1 expression. MATERIALS AND METHODS: A total of 345 patients with locoregionally advanced NPC were retrospectively enrolled (the training cohort: the validation cohort = 160:185). Co-expression of CXCL1 and FAP and the expression of PD-L1 were detected by multi-immunofluorescence staining and immunohistochemistry, respectively. The primary end-point was distant metastasis-free survival (DMFS). The Kaplan-Meier method was used to calculate the survival. The Cox proportional hazards model was used to assess prognostic risk factors. RESULTS: A novel CXCL1+_FAP+ phenotype in CAFs was identified in NPC and then used to divide patients into low and high risk groups. Both in the training cohort and validation cohort, patients in the high risk group had poorer DMFS, overall survival (OS), progression-free survival (PFS) and locoregional relapse-free survival (LRFS) than patients in the low risk group. Multivariate analysis revealed CXCL1+_FAP+ phenotype was an independent prognostic factor for DMFS, OS, PFS and LRFS. Further results showed patients in the high risk group had higher PD-L1 expression than those in the low risk group. CONCLUSION: Our study showed CXCL1+_FAP+ phenotype in CAFs could effectively classified locoregionally advanced NPC patients into different risk groups for distant metastasis and might be a potential biomarker for anti-PD-1/PD-L1 immunotherapy.

Hydrogenation of the benzene rings in PET degraded chemicals over meso-HZSM-5 supported Ru catalyst.

Chemical upcycling of waste polyethylene terephthalate (PET) to value-added products can reduce the emission of CO2, microplastics and toxic chemicals. In this work, mesoporous H-type Zeolite Socony Mobil-5 (HZSM-5) supported Ru catalyst (Ru/m-HZSM-5) was synthesized and tested in the hydrogenation of PET degraded chemicals (bis(2-hydroxyethyl) terephthalate, dimethyl terephthalate, diethyl terephthalate, and terephthalic acid). Characterizations disclosed that Ru/m-HZSM-5 catalyst possesses mesopores (a dominant channel of 5.32 nm), enlarged specific surface area (404 m2·g-1), and Ru NPs dispersed highly (40.6 %) compared to that of Ru/HZSM-5. And also, it was found that Ru/m-HZSM-5 was capable for the hydrogenation of benzene rings in these PET degraded chemicals with large sizes (1.09-1.82 nm). In particular, the conversion of BHET and the selectivity of BHCD over Ru/m-HZSM-5 reached 95.5 % and 95.6 % at 120 °C within 2 h. And Ru/m-HZSM-5 could be recycled at least five times without obvious loss of activity and selectivity.

CRISPR-Based Assays for Point-of-Need Detection and Subtyping of Influenza.

The high disease burden of influenza virus poses a significant threat to human health. Optimized diagnostic technologies that combine speed, sensitivity, and specificity with minimal equipment requirements are urgently needed to detect the many circulating species, subtypes, and variants of influenza at the point of need. Here, we introduce such a method using Streamlined Highlighting of Infections to Navigate Epidemics (SHINE), a clustered regularly interspaced short palindromic repeats (CRISPR)-based RNA detection platform. Four SHINE assays were designed and validated for the detection and differentiation of clinically relevant influenza species (A and B) and subtypes (H1N1 and H3N2). When tested on clinical samples, these optimized assays achieved 100% concordance with quantitative RT-PCR. Duplex Cas12a/Cas13a SHINE assays were also developed to detect two targets simultaneously. This study demonstrates the utility of this duplex assay in discriminating two alleles of an oseltamivir resistance (H275Y) mutation as well as in simultaneously detecting influenza A and human RNAse P in patient samples. These assays have the potential to expand influenza detection outside of clinical laboratories for enhanced influenza diagnosis and surveillance.

A Novel Near-Infrared Fluorescent Probe for the Detection of Endogenous Peroxynitrite (ONOO-) in Living Cells.

In this study, we present a novel near-infrared (NIR) fluorescent probe Nile-ONO designed for the selective and sensitive detection of ONOO-. The probe Nile-ONO employed Nile red as the fluorophore, with diphenylphosphinate serving as the reaction site. In the presence of ONOO-, the probe Nile-ONO exhibits remarkable fluorescence enhancement at 659 nm, with a response time of less than 20 min and a low detection limit of 0.32 µM. Importantly, MTT assays demonstrate low cytotoxicity in living cells. Furthermore, Nile-ONO has excellent imaging capabilities for endogenous ONOO-. Overall, this work introduces a valuable new method for the rapid detection of ONOO- in biological systems.

Label-Free Multiplex Profiling of Exosomal Proteins with a Deep Learning-Driven 3D Surround-Enhancing SERS Platform for Early Cancer Diagnosis.

Identification of protein profiling on plasma exosomes by SERS can be a promising strategy for early cancer diagnosis. However, it is still challenging to detect multiple exosomal proteins simultaneously by SERS since the Raman signals of exosomes detected by conventional colloidal nanocrystals or two-dimensional SERS substrates are incomplete and complex. Herein, we develop a novel three-dimensional (3D) surround-enhancing SERS platform, named 3D se-SERS, for the multiplex detection of exosomal proteins. In this 3D se-SERS, proteins and exosomes are covered with "hotspots" generated by the gold nanoparticles, which surround the analytes densely and three-dimensionally, providing sensitive and comprehensive SERS signals. Combining this 3D se-SERS with a deep learning model, we successfully quantitatively profiled seven proteins including CD63, CD81, CD9, CD151, CD171, TSPAN8, and PD-L1 on the surface of plasma exosomes from patients, which can predict the occurrence and advancement of lung cancer. This 3D se-SERS integrating deep learning technique benefits from high sensitivity and significant multiplexing ability for comprehensive analysis of proteins and exosomes, demonstrating the potential of deep learning-driven 3D se-SERS technology for plasma exosome-based early cancer diagnosis.

A novel lysosome-targeted fluorescent probe for precise formaldehyde detection in water samples, living cells and breast cancer tumors.

This study investigated the potential ability of the fluorescent probe Ly-CHO to detect formaldehyde (FA) in living cells and tumor-bearing mice. Ly-CHO exhibited great selectivity, excellent sensitivity, and rapid response to FA, making it a valuable tool for tracking FA concentration changes. The probe was also found to target lysosomes specifically. Furthermore, Ly-CHO showed an obvious fluorescence increase in endogenous CHO detection after adding tetrahydrogen folic acid (THFA). This study validated Ly-CHO's possibility for FA imaging in vivo, with potential applications in understanding formaldehyde-related diseases.

Who Are the Anatomic Outliers Undergoing Total Knee Arthroplasty? A Computed Tomography-Based Analysis of the Hip-Knee-Ankle Axis Across 1,352 Preoperative Computed Tomographies Using a Deep Learning and Computer Vision-Based Pipeline.

BACKGROUND: Dissatisfaction after total knee arthroplasty (TKA) ranges from 15 to 30%. While patient selection may be partially responsible, morphological and reconstructive challenges may be determinants. Preoperative computed tomography (CT) scans for TKA planning allow us to evaluate the hip-knee-ankle axis and establish a baseline phenotypic distribution across anatomic parameters. The purpose of this cross-sectional analysis was to establish the distributions of 27 parameters in a pre-TKA cohort and perform threshold analysis to identify anatomic outliers. METHODS: There were 1,352 pre-TKA CTs that were processed. A 2-step deep learning pipeline of classification and segmentation models identified landmark images and then generated contour representations. We used an open-source computer vision library to compute measurements for 27 anatomic metrics along the hip-knee axis. Normative distribution plots were established, and thresholds for the 15th percentile at both extremes were calculated. Metrics falling outside the central 70th percentile were considered outlier indices. A threshold analysis of outlier indices against the proportion of the cohort was performed. RESULTS: Significant variation exists in pre-TKA anatomy across 27 normally distributed metrics. Threshold analysis revealed a sigmoid function with a critical point at 9 outlier indices, representing 31.2% of subjects as anatomic outliers. Metrics with the greatest variation related to deformity (tibiofemoral angle, medial proximal tibial angle, lateral distal femoral angle), bony size (tibial width, anteroposterior femoral size, femoral head size, medial femoral condyle size), intraoperative landmarks (posterior tibial slope, transepicondylar and posterior condylar axes), and neglected rotational considerations (acetabular and femoral version, femoral torsion). CONCLUSIONS: In the largest non-industry database of pre-TKA CTs using a fully automated 3-stage deep learning and computer vision-based pipeline, marked anatomic variation exists. In the pursuit of understanding the dissatisfaction rate after TKA, acknowledging that 31% of patients represent anatomic outliers may help us better achieve anatomically personalized TKA, with or without adjunctive technology.

Tomographic FLEET with a wedge array for multi-point three-component velocimetry.

Femtosecond laser electronic excitation tagging (FLEET) velocimetry is an important diagnostic technique for seedless velocimetry measurements particularly in supersonic and hypersonic flows. Typical FLEET measurements feature a single laser line and camera system to achieve one-component velocimetry along a line, although some multiple-spot and multiple-component configurations have been demonstrated. In this work, tomographic imaging is used to track the three-dimensional location of many FLEET spots. A quadscope is used to combine four unique views onto a single high-speed image intensifier and camera. Tomographic reconstructions of the FLEET emission are analyzed for three-component velocimetry from multiple FLEET spots. Glass wedges are used to create many (nine) closely spaced FLEET spots with less than 10% transmission losses. These developments lead to a significant improvement in the dimensionality and spatial coverage of a FLEET instrument with some increases in experimental complexity and data processing. Multiple-point three-component FLEET velocimetry is demonstrated in an underexpanded jet.

Predicting the unpredictable: a robust nomogram for predicting recurrence in patients with ampullary carcinoma.

OBJECTIVE: To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it. METHODS: Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group. RESULTS: The patients were split into two groups, with a 7:3 ratio for training and validation. The variables screened by Lasso regression, such as CA19-9/GGT, AJCC 8th edition TNM staging, Lymph node invasion, Differentiation, Tumor size, CA19-9, Gender, GPR, PLR, Drinking history, and Complications, were used in modeling with the Lasso-Cox regression model (C-index = 0.845) and RSF model (C-index = 0.719) in the training group. According to the Delong test we chose the Lasso-Cox regression model (P = 0.019) and validated its performance with time-dependent receiver operating characteristics curves(tdROC), calibration curves, and decision curve analysis (DCA). The areas under the tdROC curves for 1, 3, and 5 years were 0.855, 0.888, and 0.924 in the training group and 0.841, 0.871, and 0.901 in the validation group, respectively. The calibration curves performed well, as well as the DCA showed higher net returns and a broader range of threshold probabilities using the predictive model. A nomogram visualization is used to display the results of the selected model. CONCLUSION: The study established a nomogram based on the Lasso-Cox regression model for predicting recurrence in AC patients. Compared to a nomogram built via other methods, this one is more robust and accurate.

Effect of e-learning program for improving nurse knowledge and practice towards managing pressure injuries: A systematic review and meta-analysis.

AIM: The aim of this review was to determine the effectiveness of the e-learning programs for improving the knowledge and professional practices of nursing personnel in managing pressure injuries patients. DESIGN: Systematic review and meta-analysis. METHODS: Systematic search was done in EMBASE, SCOPUS, Cochrane library, MEDLINE, Google Scholar, ScienceDirect and Clinicaltrials.gov databases until August 2022. Meta-analysis was carried out using random-effects model, and the results were reported as pooled standardized mean differences (SMD), or odds ratios (OR) with 95% confidence intervals (CIs). RESULTS: Eight studies were included in the analysis. Most of the studies had higher risk of bias. The pooled SMD for knowledge score and for the classification skill were 1.40 (95%CI: 0.45-2.35; I2 = 93.1%) and 1.75 (95%CI: 0.94-3.24; I2 = 78.3%) respectively. The pooled OR for the classification skills was 1.75 (95%CI: 0.94-3.24; I2 = 78.3%). PATIENT OR PUBLIC CONTRIBUTION: No patient or public contribution.

[Spatial and Temporal Evolution and Prediction of Carbon Storage in Kunming City Based on InVEST and CA-Markov Model].

Land use/cover change is an important driving factor for carbon stock changes in terrestrial ecosystems and affects the carbon cycle of the whole ecosystem. Taking Kunming City as a case study, based on the modified carbon density coefficient, this study analyzed the spatio-temporal characteristics of carbon storage changes in the terrestrial ecosystem under different land use scenarios from 2000 to 2020 and "three-line" constraints by coupling the carbon storage module of the InVEST model and CA-Markov model. The results showed that:① cultivated land, forest land, and grassland were the main types of land use in Kunming City, and land use transfer also occurred among the three types. ② From 2000 to 2020, the overall carbon storage in Kunming City was low in the south and high in the north, and the carbon storage decreased yearly with a cumulative loss of 5.27×106 t. The degradation of forest land and grassland was the main reason for the decrease in carbon storage. ③ From 2020 to 2030, the carbon storage of the four scenarios should decrease, and the decline in carbon storage in the inertia development scenario was the most obvious, which was mainly caused by the rapid expansion of construction land. The cultivated land protection scenario effectively slowed down the reduction in carbon storage compared with the inertia development scenario. The ecological protection scenario could enhance the carbon sequestration capacity of the study area, with carbon storage reaching 262.49×106 t, but could not effectively control the reduction in cultivated land area. The scenario of preventing urban expansion effectively inhibited the disorderly expansion of construction land and indirectly prevented further reduction in carbon storage. Therefore, the cultivated land protection scenario, ecological protection scenario, and urban expansion prevention scenario can be considered comprehensively in the study area, which could not only increase the carbon sink space of the study area but also ensure food and ecological security.

Factors Influencing Noise Following Primary Ceramic-on-Ceramic Total Hip Arthroplasty.

BACKGROUND: The noise associated with ceramic-on-ceramic (CoC) total hip arthroplasty (THA) has been a concerning issue, while its underlying causes remain unclear. METHODS: We conducted a retrospective analysis of 119 patients (174 primary CoC THAs) who had a mean follow-up of 28 months (range, 12 to 106). A questionnaire was designed to collect information on nature, frequency, onset, duration, and impact of the noise. Postoperative x-rays were evaluated. Clinical evaluations, including Harris and Oxford hip scores, were documented at follow-up time points (6 weeks, 3 months, 6 months, and 1 year). RESULTS: Of the 174 hips, 31.6% reported noise, including 26 popping (14.9%), 24 clicking (12.1%), and 5 grinding (2.9%). No patients reported squeaking. Noisy hips had lower age (P = .009) and body mass index (P = .019). Among patients with developmental dysplasia of the hip, 17 of 55 hips reported noise associated with smaller cup anteversion angle (P = .004), greater body height (P = .022), and larger acetabular cup size (P = .049). Noise typically began at a mean of 193 days (range, 1 to 2,598) after surgery and disappeared spontaneously in 50.9% of hips before final follow-up, with an average disappearance time of 211 days (range, 60 to 730). Noise did not affect daily life in 74.5% of patients, while 26.9% of patients who had popping reported painful sensations. One patient experienced joint dislocation, and another experienced a ceramic liner fracture during follow-up. No statistical difference was observed in outcome scores between noise and silent groups at 4 follow-up time points. CONCLUSIONS: Incidence of noise after primary CoC THA is relatively high. Smaller cup anteversion and larger acetabular cup size were associated with noise production in patients who had developmental dysplasia of the hip.

Evaluation of a biomarker (NO) dynamics in inflammatory zebrafish and periodontitis saliva samples via a fast-response and sensitive fluorescent probe.

Many pathological processes include nitric oxide (NO), a signaling transduction molecule. Tumors, cardiovascular, cerebrovascular, neurodegenerative, and other illnesses are linked to abnormal NO levels. Thus, evaluating NO levels in vitro and in vivo is crucial for studying chemical biology process of associated disorders. This work devised and manufactured a coumarin-based fluorescent probe ZPS-NO to detect nitric oxide (NO). The reaction between ZPS-NO and NO produced a highly selective and sensitive optical response that caused a powerful fluorescence "turn-on" effect with a ultra-low NO detection limit of 14.5 nM. Furthermore, the probe was applied to sense and image NO in living cells and inflammatory model of zebrafish, as well as to detect NO in periodontitis patients' saliva samples. We anticipate that probe ZPS-NO will serve as a practical and effective tool for assessing the interactions and evaluation of periodontitis development.

Lack of causal association between epilepsy and dementia: A Mendelian randomization analysis.

OBJECTIVE: Epidemiological studies have reported an association between epilepsy and dementia. However, the causal relationship between epilepsy and the risk of dementia is not clear. We aimed to inspect the causal effect of epilepsy on memory loss and dementia. METHODS: We analyzed summary data of epilepsy, memory loss, and dementia from the genome-wide association study (GWAS) using the two-sample Mendelian randomization (MR) method. We used the estimated odds ratio of memory loss and dementia associated with each of the genetically defined traits to infer evidence for a causal relationship with the following exposures: all epilepsy, focal epilepsy (including focal epilepsy with hippocampal sclerosis, lesion-negative focal epilepsy, and focal epilepsy with other lesions), and genetic generalized epilepsy (including childhood absence epilepsy, generalized tonic-clonic seizures alone, Juvenile absence epilepsy, and Juvenile myoclonic epilepsy). RESULTS: According to the result of MR using the inverse variance weighted method (IVW), we found that genetically predicted epilepsy did not causally increase the risk of memory loss and dementia (p > 0.05). Results of the MR-Egger and weighted median method were consistent with the IVW method. CONCLUSIONS: No evidence has been found to support the notion that epilepsy can result in memory loss and dementia. The associations observed in epidemiological studies could be attributed, in part, to confounding or nongenetic determinants.

Evaluation of complexity and deliverability of IMRT treatment plans for breast cancer.

This study aimed to predict the outcome of patient specific quality assurance (PSQA) in IMRT for breast cancer using complexity metrics, such as MU factor, MAD, CAS, MCS. Several breast cancer plans were considered, including LBCS, RBCS, LBCM, RBCM, left breast, right breast and the whole breast for both Edge and TrueBeam LINACS. Dose verification was completed by Portal Dosimetry (PD). The receiver operating characteristic (ROC) curve was employed to determine whether the treatment plans pass or failed. The area under the curve (AUC) was used to assess the classification performance. The correlation of PSQA and complexity metrics was examined using Spearman's rank correlation coefficient (Rs). For LINACS, the most suitable complexity metric was found to be the MU factor (Edge Rs = - 0.608, p < 0.01; TrueBeam Rs = - 0.739, p < 0.01). Regarding the specific breast cancer categories, the optimal complexity metrics were as follows: MAD (AUC = 0.917) for LBCS, MCS (AUC = 0.681) for RBCS, MU factor (AUC = 0.854) for LBCM and MAD (AUC = 0.731) for RBCM. On the Edge LINAC, the preferable method for breast cancers was MCS (left breast, AUC = 0.938; right breast, AUC = 0.813), while on the TrueBeam LINAC, it became MU factor (left breast, AUC = 0.950) and MCS (right breast, AUC = 0.806), respectively. Overall, there was no universally suitable complexity metric for all types of breast cancers. The choice of complexity metric depended on different cancer types, locations and treatment LINACs. Therefore, when utilizing complexity metrics to predict PSQA outcomes in IMRT for breast cancer, it was essential to select the appropriate metric based on the specific circumstances and characteristics of the treatment.

Visualization of photothermal therapy by semiconducting polymer dots mediated photoacoustic detection in NIR II.

Visualization of photothermal therapy mediated by photothermal transduction agents (PTAs) is important to promote individual treatment of patients with low side effects. Photoacoustic detection has emerged as a promising noninvasive method for the visualization of PTAs distribution but still has limitations in temperature measurement, including poor measurement accuracy and low tissue penetration depth. In this study, we developed biocompatible semiconducting polymer dots (SPD) for in situ coupling of photothermal and photoacoustic detection in the near-infrared II window. SPD has dual photostability under pulsed laser and continuous-wave laser irradiation with a photothermal conversion efficiency of 42.77%. Meanwhile, a strong correlation between the photoacoustic signal and the actual temperature of SPD can be observed. The standard deviation of SPD-mediated photoacoustic thermometry can reach 0.13 °C when the penetration depth of gelatin phantom is 9.49 mm. Preliminary experimental results in vivo show that SPD-mediated photoacoustic signal has a high signal-to-noise ratio, as well as good performance in temperature response and tumor enrichment. Such a study not only offers a new nanomaterial for the visualization of photothermal therapy but will also promote the theranostic platform for clinical applications.

Treatment with a flow diverter-assisted coil embolization for ruptured blood blister-like aneurysms of the internal carotid artery: a technical note and analysis of single-center experience with pooled data.

Treatment of blood blister-like aneurysms (BBAs) of the supraclinoid internal carotid artery (ICA) with flow diverters (FDs) has become widespread in recent years. However, ruptured blood blister-like aneurysm (BBA) of ICA treatment with flow diverter-assisted coil embolization (FDAC) remains controversial. Moreover, limited direct comparative studies have been conducted between the two treatment modalities, FDs and FDAC, for BBAs. The purpose of this study was to document our experience and evaluate the effectiveness and safety of FDAC. We conducted a retrospective analysis of clinical and radiological information from ten patients who experienced ruptured BBAs of the supraclinoid ICA at our center from January 2021 to February 2023. The technical details of FDAC for ruptured BBAs were described, and the technical steps were named "pipeline embolization device (PED)-Individualized shaping(microcatheter)-Semi deploying-Rivet(coils)-Massage(microwire)" as the PEISSERM technique. Clinical outcomes were assessed using the modified Rankin Scale (mRS), whereas radiological results were determined through angiography. A pooled analysis was implemented, incorporating data from literature sources that reported perioperative and long-term clinical and angiographic outcomes of ruptured BBAs treated with FD and FDAC strategies, along with our data. Data in our analysis pool were categorized into FD and FDAC strategy groups to explore the preferred treatment modalities for BBAs. The PEISSERM technique was utilized to treat ten patients, seven males, and three females, with an average age of 41.7 years. A single PED was deployed in conjunction with coils in all ten patients. All PEDs were documented to have good wall apposition. The immediate postoperative angiograms demonstrated Raymond grade I in ten aneurysms. Angiographic follow-up of nine patients at 4-25 months showed total occlusion of the aneurysms. At the most recent follow-up, the mRS scores of nine patients hinted at a good prognosis. Pooled analysis of 233 ICA-BBA cases of FD revealed a technical success rate of 91% [95% confidence interval (CI), 0.88 to 0.95], a rate of complete occlusion of 79% (95% CI, 0.73 to 0.84), a recurrence rate of 2% (95% CI, 0.00 to 0.04), a rebleed rate of 2% (95% CI, 0.00 to 0.04), and the perioperative stroke rate was 8% (95% CI, 0.04 to 0.11). The perioperative mortality was 4% (95% CI, 0.01 to 0.07). The long-term good clinical outcome rate was 85% (95% CI, 0.80 to 0.90). The mortality rate was 6% (95% CI, 0.03 to 0.09). Results from the subgroup analysis illustrated that the FDAC strategy for BBAs had a significantly higher immediate postoperative complete occlusion rate (P < 0.001), total occlusion rate (P = 0.016), and a good outcome rate (P = 0.041) compared with the FD strategy. The FDAC strategy can yield a higher rate of good outcomes than the FD strategy. The PEISSERM technique employed by the FDAC is a reliable and effective treatment approach as it can minimize the hemodynamic burden of BBA's fragile dome, thereby achieving an excellent occlusion rate. The PEISSERM technique in the FDAC strategy contributes to understanding the BBA's treatment and offers a potentially optimal treatment for BBA.