Diagnostic and prognostic value of parameters of erector spinae in patients with uremic sarcopenia

AIM

This study aimed to investigate whether computed tomography (CT)-measured erector spinae parameters (ESPs) have diagnostic, severity assessment, and prognostic predictive value in uremic sarcopenia (US).

MATERIALS AND METHODS

A total of 202 uremic patients were enrolled and divided into two groups: a control group and a sarcopenia group. Sarcopenia was classified into two types: severe and nonsevere. The area, volume, and density of the erector spinae (ES) were measured using chest CT images, and the relevant ESP, including the erector spinae index (ESI), total erector spinae volume (TESV), erector spinae density (ESD), and erector spinae gauge (ESG) were calculated. The occurrence of adverse events was followed-up for 36 months. The diagnostic value and severity of US were determined using the receiver operating characteristic (ROC) curve. Survival curves diagnosed using CT were plotted and compared with the curve drawn using the gold standard. Cox regression analysis was used to identify independent risk factors associated with survival in US.

RESULTS

With an area under the curve (AUC) of 0.840 and 0.739, the combined ESP has diagnostic value and the ability to assess the severity of US. There was no significant difference in the survival curve between the combined ESP for the diagnosis of US and the gold standard (P > 0.05). ESI is a standalone predictor of survival in patients with US.

CONCLUSION

ESP measured by CT has diagnostic values for US and its severity, as well as being a predictive value for the prognosis of US.

[Epidemiological characteristics of early-onset colorectal cancer: a prospective cohort study from a single center]

Objective: To explore the differences in distribution of colorectal cancer-related risk factors between patients with early-onset colorectal cancer (EOCRC) and those with late-onset colorectal cancer (LOCRC) in a Chinese cohort, and to provide reference and guidance for the prevention, diagnosis, and treatment of EOCRC. Methods: Using data from the National Colorectal Cancer Cohort study cohort, 5377 patients with newly diagnosed colorectal cancer (CRC) attending the Department of Colorectal Surgery and Oncology of the Second Affiliated Hospital, Zhejiang University School of Medicine from June 2018 to February 2023 were included in the study cohort. Questionnaires capturing epidemiological features, including lifestyle and dietary habits, were administered. The patients were divided into two groups, the cut-off age being 50 years. Those aged ≥50 years were defined as having LOCRC and those aged <50 years as having EOCRC. Wilcoxon (continuous variates) or χ2 tests (categorical variates) were performed to compare differences in epidemiological features. Results: A total of 3799 people who had completed the questionnaire were included in this study, 491 of whom had EOCRC and 3308 LOCRC. The response rate to the questionnaire was 70.7%. The median ages of patients in the EOCRC and LOCRC groups were 43 and 66 years, respectively. There was a higher proportion of female patients (48.5% [253/491] vs. 35.8% [1184/3308], χ2=28.8, P<0.001) in the EOCRC than the LOCRC group. Patients with EOCRC and lower body mass index (medium 22.1 kg/m2 vs. 22.9 kg/m2, W=744 793, P=0.005) and lower proportion of abdominal obesity (87.2% [428/491] vs. 93.8% [3103/3308], χ2=38.3, P<0.001). Patients with EORC significantly less commonly reported a history of hypertension (5.9% [29/491] vs. 41.6% [1375/3308], χ2=231.8, P<0.001), diabetes (1.4% [7/491] vs. 14.4% [476/3308], χ2=63.6, P<0.001) and cardiovascular and cerebrovascular diseases (0.8% [4/491] vs. 7.3% [241/3308], χ2=28.6, P<0.001). However, the proportion of patients with a family history of CRC was significantly higher (P<0.05) in the EOCRC group (10.2% [50/491] vs. 6.9% [227/3 308], χ2=6.5, P=0.010]. In terms of lifestyle, patients with EOCRC had shorter sleep duration (median: 8.0 hours vs. 8.5 hours, W=578 989, P<0.001), and were less likely to participate in physical exercise (29.5% [145/491] vs. 38.7% [1281/3308] χ2=15.0, P<0.001) or engage in physical work (65.2% [320/491] vs. 74.1% [2450/3308], χ2=16.7, P<0.001). Meanwhile, in the EOCRC group a lower percentage of patients were smokers (29.3% [144/491] vs. 42.7% [1411/3308], χ2=46.9,P<0.001) and they smoked less (median 17.6 pack/year vs. 30.0 pack/year,W=55 850,P<0.001). Fewer patients in the EOCRC group habitually drank alcohol (21.0% [103/491] vs. 38.0% [1257/3308], χ2=57.5, P<0.001) or tea (17.5% [86/491] vs. 28.7% [948/3308], χ2=26.2, P<0.001) than in the LOCRC group. Compared with the LOCRC group, patients with EOCRC had a higher frequency of intake of fresh meat, fresh fruit, eggs, and dairy products and a lower frequency of intake of preserved meat and pickled vegetables; these differences are statistically significant (all P<0.05). There was no statistically significant difference in consumption of fresh vegetables or a high-sugar diet between the two groups (both P>0.05). Conclusions: This study highlights disparities in adverse lifestyle and dietary habits between patients in China with EOCRC versus LOCRC.

[Trends in the distribution of Oncomelania hupensis in forestlands in Songjiang District, Shanghai Municipality from 2009 to 2023]

OBJECTIVE

To investigate the changes in distribution of Oncomelania hupensis snails in forestlands in Songjiang District, Shanghai Municipality from 2009 to 2023, so as to provide insights into formulation of O. hupensis snail surveillance programs.

METHODS

The reports on O. hupensis snail surveillance in Songjiang District, Shanghai Municipality from 2009 to 2023 were collected, and the snail surveillance data in forestlands were extracted. The trends in the proportion of areas with snails in forestlands in total areas with snails, occurrence of frames with living snails and density of living snails were evaluated using a Joinpoint regression model in Songjiang District from 2009 to 2023, and the annual percent change (APC) and average annual percent change (AAPC).

RESULTS

A total of 40 sites with snails were found in forestlands in 14 administrative villages of 4 townships, Songjiang District, Shanghai Municipality from 2009 to 2023. A total of 39 065 frames were surveyed for snails in settings covering an area of 609 600 m2, and there were 6 084 frames with snails, covering 151 250 m2 snail habitats. A total of 22 210 snails were captured, with the highest density of 260.00 snails/0.1 m2, and 6 262 snails were dissected, with no Schistosoma japonicum infection identified in snails. The proportion of areas with snails in forestlands in total areas with snails appeared a tendency towards a rise in forestlands in Songjiang District, Shanghai Municipality from 2009 to 2023 (APC = AAPC = 24.9%, P > 0.05); however, there were no turning points in the trend curve, with the highest proportion seen in 2009 (53.81%), the lowest in 2011 and 2023 (both 0) and a mean proportion of 24.81%. The occurrence of frames with living snails appeared a tendency towards a rise from 2009 to 2023 (APC = AAPC = 41.5%, P > 0.05); however, there were no turning points in the trend curve, with the highest occurrence in 2009 (53.81%), the lowest in 2011 and 2013 (both 0), and the mean occurrence of 15.57%. In addition, the density of living snails appeared a tendency towards a rise from 2009 to 2023 (APC = AAPC = 55.0%, P > 0.05); however, there were no turning points in the trend curve, with the highest density in 2023 (0.96 snails/0.1 m2), the lowest in 2011 and 2013 (both 0), and a mean density of 0.57 snails/0.1 m2.

CONCLUSIONS

The difficulty in O. hupensis snail control and risk of imported snails appeared a tendency towards a rise in forestlands in Songjiang District, Shanghai Municipality over years from 2009 to 2023. Supervision and assessment prior to seedling transplantation and intensified surveillance post-transplantation are recommended to reduce the risk of O. hupensis snail importation and spread.

[Efficacy evaluation of short-term personalized vestibular rehabilitation in the treatment of acute unilateral vestibulopathy]

Objective: To explore the efficacy and effective node of short-term personalized vestibular rehabilitation (ST-PVR) in treating acute unilateral vestibulopathy (AUVP). Methods: A randomized controlled trial was carried out. The AUVP patients who were admitted to the First Affiliated Hospital of Zhengzhou University from July 2022 to March 2023 were selected and randomized to the vestibular rehabilitation (VR) group and control group via computer-generated randomization. Standard care was the medical treatment with betahistine and prednisolone. Meanwhile, the VR group received ST-PVR. All the patients completed the baseline assessment and underwent follow-up assessments at 1 month and 3 months after the treatment. The assessments were consisted of spontaneous nystagmus (NYS), Romberg test (ROM), head thrust test (HTT), visual analogue scale (VAS) for vertigo, dizziness handicap inventory scale (DHI), activities-specific balance confidence scale (ABC), caloric test using video-electronystagmograph (VNG), and video-head impulse test (vHIT). The measurement data that did not conform to normal distribution were represented by M (Q1, Q3). Generalized estimating equation (GEE) was used to analyze the influence of the ST-PVR on the values of these clinical indicators and the VR grading score. The values of clinical indicators and the VR grading score were compared between the two groups at each follow-up point. Results: Seventy-one AUVP patients were included, with 35 cases in the VR group [14 males and 21 females, aged 51 (33, 55) years] and 36 cases in control group [17 males and 19 females, aged 46 (34, 59) years]. There were statistically significant differences in the impact of ST-PVR on the values of clinical indicators between the two groups (ABC: β=10.89, P<0.001; VAS: β=-1.64, P<0.001; DHI: β=-8.70, P<0.001; NYS: β=26.73, P<0.001; vHIT: β=1.41, P=0.047; the VR grading score: β=1.03, P=0.045). The assessments of the VR group in the positive rate of NYS [14.3% (5/35) vs 50.0% (18/36), P<0.001], ROM [48.6% (17/35) vs 55.6% (20/36), P<0.001], directional preponderance (DP) [34.3% (12/35) vs 75.0% (27/36), P<0.001] and DHI [26 (22, 32) vs 36 (30, 60), P=0.001] were significantly lower than that of the control group at 1 month after the treatment. The results showed a statistically significant difference in ABC [88 (80, 90) vs 76 (61, 88), P<0.001], VAS [2 (1, 3) vs 3 (2, 5), P<0.001] at 3-months after the treatment. The VR grading score of the VR group was improved significantly than those of the control group at 1 month after treatment [21 (17, 21) vs 16 (13, 20), P=0.001]. Conclusion: ST-PVR could improve the results of clinical indicators and VR grading score of the AUVP patients effectively after 1 month of the systematical treatment, and alleviate the symptoms and signs of dizziness in the acute phase as early as possible.

[Clinical features and temporal CT findings in patients with Branchio-Oto-Renal or Branchio-Oto Syndrome]

Objective: To assess the clinical features and CT diagnostic characteristics of Branchio-Oto-Renal or Branchio-Oto Syndrome. Methods: The temporal CT findings and clinical features observations of 13 patients with Branchio-Oto-Renal Syndrome (BORS) or Branchio-Oto Syndrome(BOS) confirmed by genetic testing were retrospectively analyzed. There were 8 males and 5 females, aged from 1 to 39 years, with a median age of 9 years, in which 3 pairs (6 cases) were parent-child relationship. Results: All of 13 cases had hearing loss and preauricular fistula, 11 cases accompanied by 2nd branchial fistulas. There were 20 ears of mixed hearing loss, 3 ears of sensorineural hearing loss, and 2 ears of conductive hearing loss. The mutation point of gene testing was located in EYA1 in 12 cases and SIX1 in 1 case. Twenty ears showed gradually narrowing of the diameter of basal turn, with hypoplasia in the second turn and aplasia in apical turn. There were irregular wall of vestibule and horizontal semicircular canal in 10 ears,widened vestibular in 7 ears, and vestibular fusion with horizontal semicircular canal in 3 ears. Three ears had an enlarged vestibular aqueduct, 8 ears showed enlargement of internal auditory canal. Seventeen ears had adhesion of malleolus to tympanic cavity. Six ears could not measured the incudostapedial joint angle by reason of tympanic inflammatory cover, 3 ears could not show incudostapedial joint, and 8 ears showed the incudostapedial joint angle more than 122°. Six ears showed poor oval window, and 1 ear had poor round window. Eighteen ears showed distended eustachian tube, and accompanied by tympanic or mastoiditis in 11 ears. Anterolateral shift of tympanum was found in 22 ears, 17 ears had low middle cranial fossa, and 3 ears had stenotic external auditory canal. Conclusions: Cochlear dysplasia, ossicular chain malformation and distended eustachian tube comprise the characteristic CT signs of BOS/BORS, which possesses versatile and complex CT findings. Temporal CT can accurately assess the important structures such as cochlea, ossicles, vestibule, semicircular canal, vestibular aqueduct and internal auditory canal. Combing with the clinical characteristics of bilateral, mixed hearing loss, preauricular fistula and branchial fistula can provide valuable information for early diagnosis and treatment.

Medical expenses of patients with severe mental disorders in Beijing, China

OBJECTIVES

Mental health has become a significant public health problem that impacts both economic and social development, with severe mental disorders (SMDs) being the top priority. Over recent years, Beijing, China, has introduced several policies to reduce the economic burden on patients with mental health disorders. The aim of this study was to investigate the current status and composition of patients' medical expenses following the introduction of multiple medical policies, explore the factors that may impact the utilisation of medical services and provide a reference and basis for subsequent policy improvements.

STUDY DESIGN

Multistage sampling was used to select a representative study population. A retrospective survey was used to collect patient information and data on medical expenses in 2019.

METHODS

Descriptive statistics were applied to analyse the current status of patients' medical expenses, and a two-part model was used to examine the factors influencing healthcare utilisation and to model predicted expenses.

RESULTS

Among 4940 participants, the average outpatient expenses of patients with SMD who incurred medical expenses were 8373.61 Yuan, and the average hospitalisation expenses were 81,594.05 Yuan. The out-of-pocket expenses were 29.22% of outpatient expenses and 8.13% of inpatient expenses. Factors such as age, household status, economic status, marital status, participation in the Community Free-Medication Service (CFMS) and the type of disease diagnosed influenced the differences in medical expenses and utilisation of services.

CONCLUSIONS

The medical expenses of patients with SMD in Beijing are high, but a number of introduced policies have effectively reduced these costs for patients. Future studies should focus on the impact of factors such as age, economic status, participation in the CFMS and the type of disease diagnosed on medical expenses.

[Timing and surgery option of keratinized mucosa augmentation around implant site]

In recent years, clinicians have paid more attention to the biological and esthetic effects of the 2 mm keratinized mucosa width (KMW) around dental implant. How to increase the keratinized mucosa is the focus of clinicians. While the free gingival graft (FGG) is still the gold standard of keratinized mucosa augmentation, alveolar ridge preservation (ARP), connective tissue graft (CTG) and apically positioned flap (APF) can also be used to obtain more than 2 mm keratinized mucosa width when they are used before implantation, with implantation, within the implant-healing phase, with second stage of implantation or after rehabilitation according to different indications. This article comprehensively summarizes the influencing factors of timing and surgical procedures for keratinized mucosa augmentation, providing guidance for clinicians to treat peri-implant keratinized mucosa deficiencies.

Vegetation-fire feedbacks increase subtropical wildfire risk in scrubland and reduce it in forests

Climate dictates wildfire activity around the world. But East and Southeast Asia are an apparent exception as fire-activity variation there is unrelated to climatic variables. In subtropical China, fire activity decreased by 80% between 2003 and 2020 amid increased fire risks globally. Here, we assessed the fire regime, vegetation structure, fuel flammability and their interactions across subtropical Hubei, China. We show that tree basal area (TBA) and fuel flammability explained 60% of fire-frequency variance. Fire frequency and fuel flammability, in turn, explained 90% of TBA variance. These results reveal a novel system of scrubland-forest stabilized by vegetation-fire feedbacks. Frequent fires promote the persistence of derelict scrubland through positive vegetation-fire feedbacks; in forest, vegetation-fire feedbacks are negative and suppress fire. Thus, we attribute the decrease in wildfire activity to reforestation programs that concurrently increase forest coverage and foster negative vegetation-fire feedbacks that suppress wildfire.

A Frameshift Variant of GluN2A Identified in an Epilepsy Patient Results in NMDA Receptor Mistargeting

N-methyl-D-aspartate receptors (NMDARs) are crucial for neuronal development and synaptic plasticity. Dysfunction of NMDARs is associated with multiple neurodevelopmental disorders, including epilepsy, autism spectrum disorder, and intellectual disability. Understanding the impact of genetic variants of NMDAR subunits can shed light on the mechanisms of disease. Here, we characterized the functional implications of a de novo mutation of the GluN2A subunit (P1199Rfs*32) resulting in the truncation of the C-terminal domain. The variant was identified in a male patient with epileptic encephalopathy, multiple seizure types, severe aphasia, and neurobehavioral changes. Given the known role of the CTD in NMDAR trafficking, we examined changes in receptor localization and abundance at the postsynaptic membrane using a combination of molecular assays in heterologous cells and rat primary neuronal cultures. We observed that the GluN2A P1199Rfs*32-containing receptors traffic efficiently to the postsynaptic membrane but have increased extra-synaptic expression relative to WT GluN2A-containing NMDARs. Using in silico predictions, we hypothesized that the mutant would lose all PDZ interactions, except for the recycling protein Scribble1. Indeed, we observed impaired binding to the scaffolding protein postsynaptic protein-95 (PSD-95); however, we found the mutant interacts with Scribble1, which facilitates the recycling of both the mutant and the WT GluN2A. Finally, we found that neurons expressing GluN2A P1199Rfs*32 have fewer synapses and decreased spine density, indicating compromised synaptic transmission in these neurons. Overall, our data show that GluN2A P1199Rfs*32 is a loss-of-function variant with altered membrane localization in neurons and provide mechanistic insight into disease etiology.

A modular table-top setup for ultrafast x-ray diffraction

We present a table-top setup for femtosecond time-resolved x-ray diffraction based on a Cu Kα (8.05 keV) laser driven plasma x-ray source. Due to its modular design, it provides high accessibility to its individual components (e.g., x-ray optics and sample environment). The Kα-yield of the source is optimized using a pre-pulse scheme. A magnifying multilayer x-ray mirror with Montel-Helios geometry is used to collect the emitted radiation, resulting in a quasi-collimated flux of more than 105 Cu Kα photons/pulse impinging on the sample under investigation at a repetition rate of 10 Hz. A gas ionization chamber detector is placed right after the x-ray mirror and used for the normalization of the diffraction signals, enabling the measurement of relative signal changes of less than 1% even at the given low repetition rate. Time-resolved diffraction experiments on laser-excited epitaxial Bi films serve as an example to demonstrate the capabilities of the setup. The setup can also be used for Debye-Scherrer type measurements on poly-crystalline samples.

[Analysis of perrault syndrome caused by pathogenic variants in LARS2 and HARS2 genes]

Objective: To investigate the molecular etiology of Perrault syndrome by analyzing the clinical phenotype and pathogenic gene variants of 2 male patients with bilateral severe sensorineural deafness. Methods: Two male patients with Perrault syndrome characterized by severe sensonrineual deafness adimitted to the First Affiliated Hospital of Zhengzhou University between February 2021 and March 2022 were selected, and the clinical phenotype and pathogenic gene variants of them and their family members were summarized. The whole exome sequencing technology was used to screen the pathogenic variants of the probands, and the candidate variants were determined by combining with clinical phenotype. The probands and their family members were verified by the Sanger sequencing method. Results: The whole exome sequencing results showed that the proband of family 1 had a compound heterozygous variants of the LARS2 (NM_015340.4) gene c.1565C>A (p.Thr522Asn) and c.1079T>C (p.Ile360Thr). The reported pathogenic variant c.1565C>A came from the mother, and the novel variant c.1079T>C came from the father. The second proband harbored compound heterozygous variants of HARS2 gene (NM_012208.4) c.1273C>T (p.Arg425Trp) and c.1403G>C (p.Gly468Ala), with the former from the proband's mother, the latter from the father. The c.1273C>T was novel and c.1403G>C was the reported pathogenic variant. All above variants were respectively classified as pathogenic, uncertain significance, uncertain significance and likely pathogenic based on the ACMG guidelines. Conclusion: This study expands the mutational spectrum of LARS2 and HARS2 genes, which highlights that genetic testing plays an important role in the early diagnosis of syndromic deafness.

A luminous fast radio burst that probes the Universe at redshift 1

Fast radio bursts (FRBs) are millisecond-duration pulses of radio emission originating from extragalactic distances. Radio dispersion is imparted on each burst by intervening plasma, mostly located in the intergalactic medium. In this work, we observe the burst FRB 20220610A and localize it to a morphologically complex host galaxy system at redshift 1.016 ± 0.002. The burst redshift and dispersion measure are consistent with passage through a substantial column of plasma in the intergalactic medium and extend the relationship between those quantities measured at lower redshift. The burst shows evidence for passage through additional turbulent magnetized plasma, potentially associated with the host galaxy. We use the burst energy of 2 × 1042 erg to revise the empirical maximum energy of an FRB.

Overall Survival Prediction in Stereotactic Radiosurgery Patients with Glioblastoma Via a Deep-Learning Approach

PURPOSE/OBJECTIVE(S)

Accurate and automated early survival prediction is critical for glioblastoma (GBM) patients as their poor prognosis requires timely treatment decision-making. We have developed a deep learning (DL)-based GBM overall survival (OS) prediction model based on a multi-institutional public dataset using only pre-operative basic structural multi-parametric magnetic resonance images (MRIs). The purpose of this study is to evaluate this DL-based OS prediction model with an institutional stereotactic radiosurgery (SRS) clinical trial dataset.

MATERIALS/METHODS

The task of this study is to classify GBM patients into 3 OS classes: long-survivors (>15 months), mid-survivors (between 10 and 15 months) and short-survivors (< 10 months). The proposed OS prediction model is an ensemble of a ResNet-based classifier and a K-NN classifier. The ResNet-based classifier is trained in a Siamese fashion to explore inter-class differences. During testing, training sample features are implemented with a K-NN classifier to ensemble with the ResNet-based classifier. A public dataset from Medical Image Computing and Computer Assisted Intervention (MICCAI) Brain Tumor Segmentation (BraTS) challenge 2020 (235 patients) were used for model establishing and initial validation. Then the validated model was evaluated on 19 GBM patients from an institutional SRS clinical trial. Each data entry consists of pre-operative basic structural multi-parametric MRIs and survival days, as well as patient ages for BraTS data and basic clinical characteristics for institutional data. GBM sub-regions, including contrast-enhancing tumor, peri-tumoral edema, and necrotic/non-enhancing tumor core, were segmented in the multi-parametric MRIs by an in-house DL model for both datasets. The OS prediction model was trained on 90% of the segmented BraTS data and validated on the rest 10%, then further evaluated on the institutional data. The model performance was assessed by prediction accuracy (ACC) and the area under the curve (AUC).

RESULTS

For this 3-class OS classification task, our DL-based prediction model achieved an ACC of 65.22% and an AUC of 0.81 on the BraTS dataset compared with the top-ranked result from the BraTS challenge 2020 (Rank 1st: ACC 61.7%), and an ACC of 52.63% and an AUC of 0.69 on the institutional dataset. Further analysis of the institutional dataset found that the predicted OS class had a statistically significant correlation with treatment volume (p = 0.012) and age (p = 0.006), which matches the analysis that the patients' ground truth OS class is statistical significantly correlated with treatment volume (p = 0.045).

CONCLUSION

Our DL-based OS prediction model for GBM using basic structural multi-parametric pre-operative MRIs has demonstrated promising performance in both public and institutional dataset with minimal manual processing requirements. This OS prediction model can be potentially applied to assist timely clinical decision-making.

An Online AI-Powered Interactive Histological Image Annotation Platform for Analyzing Intestinal Regenerating Crypts in Post-Irradiated Mice

PURPOSE/OBJECTIVE(S)

The goal of this project is to build an online AI-powered interactive annotation platform to accurately and efficiently annotate intestinal regenerating crypts in histological images of mice after abdominal irradiation.

MATERIALS/METHODS

The proposed platform is developed by the seamless integration of a front-end web client and a back-end server. Such client/server design allows the users to access the platform without software installation on local computers. Our front-end client is developed with SvelteJS + WebGL technology stack, allowing access from any common web browsers and enabling user interaction, such as image importing/visualization, interactive crypt annotating, and annotation saving/deleting. The back-end server is responsible for executing the tasks requested from the web client, for instance, image pre-processing, AI-based crypts automatic identification, and database management. The image preprocessing is designed to extract a single cross section image using morphological operations because multiple hematoxylin and eosin (H&E) stained jejunum cross sections from post-irradiated mice are scanned within one slide. The auto-crypt identification is powered by a trained and validated AI engine U-Net, classifying image grid tiles into two groups with and without regenerating crypts. The database is implemented with the self-contained SQLite to support recording and indexing the annotated grid tiles with regenerating crypts. The workflow for crypt analysis on this interactive platform has 5 steps: 1) manually import a whole H&E slide image; 2) auto-preprocess the slide by extracting single cross-section images; 3) auto-identify regenerating crypts with an AI engine; 4) interactively annotate (add, delete, modify) auto-identified crypt markers; 5) save and/or output the annotation to the database or the local drive.

RESULTS

The performance of the developed interactive crypt analysis platform was evaluated in aspects of accuracy and efficiency. The AI-powered crypt auto-identification accuracy was assessed by computing the mean absolute error (MAE) on crypt number per cross section between manual and auto annotation using a testing dataset containing 80 cross sections. It achieved an MAE of 3.5±4.8 crypts per cross section, and 81.25% of the cross sections have no more than 5 crypts difference. The efficiency was assessed under two conditions with the server on the cloud and a local computer. It took about 2-3 minutes to finish the entire workflow on the cloud, while 1-2 minutes on the local by saving ∼1 minute on image uploading.

CONCLUSION

The developed web client/server platform enables online automatic identification and interactive annotation of mice crypts in minutes. It is a convenient tool that allows accurate and efficient crypt analysis and can be extended for other histologic image analyses.

Intelligent Interactive Deformable Image Registration for Online Adaptive Radiotherapy

PURPOSE/OBJECTIVE(S)

The goal of this study is to streamline the time-consuming contouring process in online adaptive radiotherapy (ART) by utilizing a deep learning-based interactive deformable image registration (DIR) algorithm. The objective is to minimize manual review and editing of automatically generated initial contours of organs-at-risk (OARs) and targets, thereby improving the efficiency and effectiveness of the treatment process.

MATERIALS/METHODS

Our proposed method reforms the current DIR-based contour propagation method in clinical practice through the implementation of a deep learning-based interactive approach. The steps include: 1) generation of an initial deformable vector field (DVF) using a DL model, based on fixed and moving image pairs, resulting in the initial contours of OARs and targets; 2) clinician review/edit one the OAR/target contours as needed; 3) updated contour is sent to DL model to update the DVF and the remaining OARs/targets contours. Repeat this process until satisfactory contour qualities are achieved. We used the Open Access Series of Imaging Studies (OASIS) as the testbed, including 394 (train) and 20 (test) brain T1-weighted MRI scans, each containing 35 annotated organs. The U-Net architecture was employed to update the DVF from fixed/moving images, initial contours, and updated contours. We compared our approach to traditional manual editing without interaction and quantified the effort reduction using the added path length (APL) metric which is supposed to be proportional to the absolute time spent on the contour editing. We conducted paired t-test to show the significance. For comparison purpose, we assumed the clinicians edit the contours with the largest APL, i.e., the contours that require the most editing efforts.

RESULTS

The editing effort, as measured by APL, was reduced by 18.5% to 25.4% with a mean of 23.3%, median of 23.6%, and standard deviation of 1.9%. The significance of the results was confirmed with a p-value of 1.47e-24.

CONCLUSION

Our study demonstrates a significant reduction in editing effort, as measured by APL, compared to traditional manual contour editing. These results demonstrate the potential of our deep learning-based interactive approach to improve the efficiency and accuracy of the contouring process in clinical practice.

Favorable Survival after Definitive Ablative RT in Surgically Resectable Pancreatic Cancer Patients

PURPOSE/OBJECTIVE(S)

Surgical resection has been considered the only curative option for patients with pancreatic adenocarcinoma (PDAC). Ablative RT ≥100Gy BED10 (A-RT) is associated with favorable survival in patients with locally advanced unresectable disease. We sought to evaluate A-RT outcomes in patients with technically resectable disease who did not undergo surgery.

MATERIALS/METHODS

Our prospectively maintained database of patients treated with A-RT was queried for consecutive patients with radiographic T1/T2 resectable PDAC. Patients were treated with a standardized technique within a large academic cancer center regional network. Ablative RT using several hypofractionated regimens was delivered on either standard Linacs with respiratory motion management, CBCT image guidance and selective adaptive replanning or MR-Linac with compression belt and daily on-line adaptive replanning. Freedom from local progression (FFLP), distant metastasis-free and overall survival (DMFS and OS, respectively) were analyzed using the Kaplan Meier estimates.

RESULTS

Between 2016 and 2022, 28 patients (54% male) with radiographically resectable PDAC received definitive A-RT. Median age was 80 (interquartile range, 77-84) years and 23 (82.1%) had KPS of 80 or below. Eighteen patients (64.3%) had T2 cancer, 5 (17.9%) were node positive, and 23 (82.1%) had head location. Median size was 2.6 (range, 1.6-4.0) cm with a median carbohydrate antigen 19-9 (CA19-9) of 160.5 (0-1823) U/mL. Twenty patients (71.4%) received induction chemotherapy for a median of 2.4 (0-6.2) months. RT regimens delivered on conventional Linacs unless otherwise indicated included 75Gy in 25 fractions (n = 15), 67.5Gy in 15 fractions (n = 10), 50Gy in 5 (N = 2, MR Linac), 60Gy in 10 (n = 1). 24-month FFLP and DMFS were 78.8% (52.3-91.7%) and 17.7% (95% CI, 5.8%-34.8%), respectively. 24-month and 48-month rate of OS from A-RT were 49.1% (95% CI, 27.53-67.5%) and 36.3 (95%16.0-57.1%). Grade 3 acute and late GI toxicity was noted in 3 and 1 patients, respectively, including 2 bleeding events treated with transfusions. There were no ≥ grade 4 events.

CONCLUSION

In patients with surgically resectable PDAC we found that definitive A-RT following multiagent induction therapy was associated with oncologic outcomes similar to resection with minimal toxicity.

Multi-Institutional Phase II Trial Using Dose Escalated Five Fraction Stereotactic Partial Breast Irradiation (S-PBI) with GammaPodTM for Early-Stage Breast Cancer

PURPOSE/OBJECTIVE(S)

We report on our early experience of a multi-institutional phase II study of dose escalated five fraction stereotactic partial breast irradiation (S-PBI) for early-stage breast cancer after partial mastectomy using the GammaPodTM stereotactic radiation system.

MATERIALS/METHODS

Patient eligibility included DCIS or invasive epithelial histologies, AJCC clinical stage 0, I, or II with tumor size < 3 cm, and negative margins. Prior safety of Phase I dose escalation has been reported. Dose was 40 Gy delivered in 5 fractions to the CTV, and minimum dose 30 Gy in 5 fractions to the PTV. CTV margin was 1 cm and PTV margin 3 mm. For PTV cavities larger than 100cc, dose was reduced to 35Gy in 5 fractions to the CTV and 30 Gy in 5 fractions to the PTV. Primary endpoint of the study is to determine the 3-year patient global cosmesis score (4-point scale excellent, good, fair, or poor) and adverse cosmesis using a dose escalated approach with smaller PTV margins than conventional methods. Both patients and physicians completed baseline and subsequent cosmesis outcome questionnaires. Treatment related toxicity was graded using the NCI version 4.0 and RTOG/EORTC late radiation scale.

RESULTS

From 3/2019-10/2021, 74 patients were treated respectively. Of these, 38 were treated to 40Gy and 36 were treated to 35 Gy. Median follow up (f/u) was 24 months (mo), range (r) 3-39mo. Median age was 63 years (r 43-77). Histology included 28 DCIS, and 46 invasive carcinomas. 45/46 invasive tumors were ER+. 60/74 (81%) patients received endocrine therapy, and 7/74 patient received chemotherapy. There were 221 acute grade 1 toxicities, and 28 Grade 2 toxicities. No grade 3 or higher acute toxicities were reported (< 90 days). The most common Grade 2 toxicities were radiation dermatitis (10), breast pain (8), blister (4), skin infection (2), nipple discharge (2), and fatigue (2). In the late period, there were 54 Grade 1 late toxicities, 4 Grade 2 late toxicities, and no Grade 3 or higher late toxicities. Grade 2 toxicities included fibrosis (2), and pain (2). Two patients developed grade 1 asymptomatic nonpalpable fat necrosis both diagnosed at 12 months after radiation treatments. The most common grade 1 late toxicities were breast pain (14), hyperpigmentation (8), fibrosis (10), and fatigue (5). Physicians scored cosmesis excellent or good 70/73 (95.8%), 58/60 (96.7%), 36/36 (100%),17/17(100%) respectively at baseline, 12 months, 24 months, and 36months post SBRT, while patients scored the same periods 62/71 (83.7%), 53/59 (89.8%), 33/36 (91.6%), 17/18 (94.4%). There have been no reports of disease recurrences.

CONCLUSION

Results at 24-month median follow-up, of our dose escalated stereotactic partial breast 5 fraction regimen, has low acute and late toxicity, while maintaining high proportion of excellent/good cosmetic outcomes. Continued analysis of all cohorts is in progress.

CLINICAL TRIALS

gov identifier is NCT03581136.

Deep Learning-Based Pipeline for Automatic Identification of Intestinal Regenerating Crypts in Mouse Histological Images

PURPOSE/OBJECTIVE(S)

A classical approach for evaluating normal tissue radiation response is to count the number of intestinal regenerating crypts in mouse histological images acquired after abdominal radiation. However, manual counting is time-consuming and subject to inter-observer variations. The goal of this study is to build a deep learning-based pipeline for automatically identifying intestinal regenerating crypts to facilitate high-throughput studies.

MATERIALS/METHODS

Sixty-six healthy C57BL/6 female mice underwent 16 MeV whole abdominal electron irradiation. The small bowel was collected from each mouse 4 days post-irradiation, and 9 jejunal cross-sections from each were processed together in a single slide. The slides were stained with hematoxylin and eosin (H&E) and subsequently scanned (x20), providing one electronic histological image per mouse. Regenerating crypts, consisting of more than 10 basophilic crypt epithelial cells, were manually identified using point annotations in histological images. The pipeline was built to take the input of the image containing 9 cross sections and automatically identify the regenerating crypts on each cross section. It mainly consists of two components, cross section segmentation using intensity thresholding and morphological operations and crypt identification using a UNet. The dataset was randomly split into 46, 10, and 10 slide images for UNet training, validation, and testing. Each slide image was split into grid tiles with a voxel size of 200 × 200, and 40 × 40 square masks were placed with centers at manual point annotations on tiles with regenerating crypts. 5203/5198 tiles (w/wo crypt mask) were extracted to train UNet by minimizing dice loss. The mask probability map generated by the UNet was post-processed to identify the crypt position. Postprocessing hyperparameters were tuned using the validation dataset. The model accuracy was evaluated using the testing dataset by computing the mean absolute error (MAE) of the crypt number averaged across all cross sections.

RESULTS

The number of regenerating crypts on testing cross sections ranges from 1 to 63. The testing cross-section-wise MAE achieved by the platform is 3.5±4.8 crypts. 81.25% of testing cross sections have absolute number differences less than or equal to 5 crypts.

CONCLUSION

Our established deep learning-based pipeline can accurately count the number of regenerating crypts in mouse intestinal histological images. We have integrated it into an online platform that enables automatic crypt identification and allows users to interactively modify auto-identified crypt annotations. The acquired annotations from the platform will be used to finetune the deep learning model to achieve better identification performance.

Equivalent Dose Estimation in FLASH Irradiation with a Deep Learning Approach

PURPOSE/OBJECTIVE(S)

Ultra-high dose rate (FLASH) irradiation has been reported to provide decreased normal tissue toxicity without compromising tumor control compared with conventional (CONV) irradiation. However, a comprehensive understanding of the FLASH biological effect requires precise quantification of radiobiology. The study is to explore whether deep learning (DL) can tackle the task. As a proof of concept, we investigate a DL model for estimating FLASH dose to its equivalent CONV dose.

MATERIALS/METHODS

Healthy C57Bl/6 female mice underwent FLASH (200Gy/s; n = 43) or CONV (0.12Gy/s; n = 41) whole abdominal irradiation using ∼16 MeV electron beams with a dose escalation scheme of 5 groups (n = 8 or 9) at 1Gy increments: 12-16Gy FLASH, 11-15Gy CONV. 4 days post-irradiation, 9 jejunum cross-sections per mouse were H&E stained for histological analysis. Each cross-section image was processed to remove lumen background and oversampled into multiple large-scale and small-scale patches along jejunal circumference. In CONV dataset, we randomly selected the data of 32 mice (80%) for model training and the rest (20%) for model validation. A ResNet101-based DL model, pre-trained with an unsupervised contrastive learning scheme, was retrained with only CONV training set to estimate corresponding CONV dose. For comparison, a crypt counting (CC) approach was implemented by manually counting the number of regenerating crypts on each cross-section image. An exponential function of dose vs crypt number was fitted with the CONV training set and used for dose estimation on the testing set. Mean squared error (MSE) was used to assess the accuracy of DL and CC approaches in estimating dose levels in CONV irradiation. The validated DL model was applied to the FLASH set to project FLASH dose into corresponding CONV dose that results in equivalent biological response.

RESULTS

The CONV dose estimated by DL and CC approaches and DL-estimated FLASH equivalent dose were summarized in Table 1. The DL model achieved an MSE of 0.21 Gy2 on CONV testing set compared with 0.32 Gy2 of the CC approach. FLASH equivalent dose estimated by DL model for 12, 13, 14, 15 and 16Gy were 12.16±0.40, 12.53±0.32, 12.72±0.24, 12.85±0.20 and 13.04±0.27 Sv, respectively.

CONCLUSION

Our proposed DL model can accurately estimate the CONV dose based on histological images. The DL predictions of FLASH dataset demonstrate that FLASH may reduce normal tissue toxicity with a lower equivalent dose, especially at high irradiated dose levels. Our study indicates that deep learning can be potentially used to assess the equivalent dose of FLASH irradiation to normal tissue.

Assessment of Cardiac Radiation Dose in the Co-60 Prone Based Stereotactic Partial Breast Irradiation (CP-sPBI) Using the Distance from the Heart to the Planning Treatment Volume as a Surrogate Marker

PURPOSE/OBJECTIVE(S)

Irradiation of the breast has shown to provide sharp dose gradients using Co-60 prone based stereotactic partial breast irradiation (CP-sPBI), a contemporary device for stereotactic radiotherapy for breast cancer (BC) for accelerated partial breast irradiation (APBI). In addition, the precise setup of CP-sPBI permits a small planning treatment volume (PTV) margin of 3 mm creating a greater distance from PTV to organs at risk. However, to date the factors that influence dose gradients and subsequent cardiac doses of ionizing radiation using CP-sPBI have not been well-studied. Here we evaluate distance of the heart to the lumpectomy PTV cavity and how this effects cardiac dose.

MATERIALS/METHODS

A retrospective database of 113 consecutive patients treated by CP-sPBI for APBI from March 2019 to February 2023 who were treated with 30 Gy in 5 fractions were queried for analysis. The minimum distance from the heart to the PTV (hP) was measured in either the axial or sagittal view. A group of 28 patient cases were randomly selected to achieve an even distribution of 28 cases with hP < 2.75 cm and hP ≥ 2.75 cm to compare cardiac toxicities based on hP. Descriptive analyses were performed to evaluate various cardiac dosimetric parameters based on laterality of BC and hP, using the student's t test.

RESULTS

The mean (range) hP was 4.58 cm (0.80-12.23) for all cases. The subgroup analyses of 28 patient cases with cardiac parameters showed the heart mean (range) dose of 1.20 Gy (0.01-2.11). The mean and max heart dose to the left-sided BC were similar to those to the right-sided BC (mean dose: 1.20 vs. 1.19 Gy; P = 0.97 and max dose: 10.47 vs. 5.66 Gy; P = 0.06). An inverse correlation between hP and mean heart dose was shown with the correlation coefficient of -0.81. Using a cutoff of 2.75 cm hP, the differences between hP < 2.75 and hP ≥ 2.75 cm for all cardiac dosimetric evaluations were all statistically significant, including mean (1.67 vs. 0.79 Gy; p<0.01) and maximal heart dose (14.48 vs. 4.11 Gy; p<0.01) CONCLUSION: CP-sPBI treatment delivery system was able to achieve acceptable clinically relevant heart dosimetric parameters when delivering 5 fraction APBI with a mean heart dose of 1.20 Gy for all locations of PTV cavity volume in the breast. Due to CP-sPBIs excellent dose fall-off characteristics, APBI using CP-SPBI showed clinically acceptable cardiac dosimetric parameters, particularly for PTVs located > 2.75 cm from the heart.

Predicting Neurocognitive Decline in Multiple Brain Metastases Patients Undergoing Distributed Stereotactic Radiosurgery

PURPOSE/OBJECTIVE(S)

Stereotactic radiosurgery (SRS) is the standard of care for treating a limited number (<3) of brain metastasis (BMs), which offers reduced neurotoxicity compared to whole brain radiotherapy (WBRT). Contemporary advancements in SRS made it possible to also commonly treat multiple (>4) BMs (mBMs). Emphasizing the value of preserving quality of life (QoL) after SRS, there is an urgent need for a systematic study of potential neurocognitive decline in patients receiving SRS treatment for mBMs. The purpose of this study is to use routine MRIs to predict neurocognitive decline for patients treated with distributed SRS, allowing for timely and effective treatment strategy design.

MATERIALS/METHODS

This study uses data from an institutional phase I/II clinical trial to determine the neurocognitive decline in patients with (>6) mBMs treated with distributed SRS. In the first 12 months post-SRS, participants are followed and evaluated with routine MRIs and the Hopkins Verbal Learning Test-Revised (HVLT-R) at 2 to 3-month intervals. Changes in HVLT-Delayed Recall scores between two visits are used to define neurocognitive decline. For each visit, an in-house deep learning model segments 66 cortical and 55 subcortical brain regions of interest (ROIs) from the T1 structural MRI and extracts 253 ROI features, including the surface area and thickness of cortical ROIs, and the volume of all ROIS. The difference in ROI features between two visits, together with other clinical factors (e.g., prescription, number of BMs, etc.), is considered as one sample. The study included 22 subjects with 91 visits, resulting in 171 samples with neurocognitive decline labels. The entire sample set is split into 10 folds on patient level for cross validation. In each fold, feature engineering is conducted to remove redundancy and to select the most-important features. The top 20% most frequently selected features are applied with Support Vector Machine to predict the neurocognitive decline label of each sample.

RESULTS

As a preliminary result, the proposed method achieves an accuracy of 76%, with an area under the curve (AUC) of 0.75, sensitivity of 0.65 and specificity of 0.83 for predicting neurocognitive decline in mBMs SRS patients using only routine T1 MRIs. The volume of lateral occipital complex, the thickness of inferior parietal lobe and postcentral gyrus, and the surface area of lateral orbitofrontal cortex and pars triangularis are identified as the 5 most important features for this task.

CONCLUSION

Our method shows promising findings for post-SRS neurocognitive decline prediction solely based on routine baseline and follow-up MRIs. In addition, it can identify critical brain ROIs associated with the post-SRS cognitive function. This method has the potential to assist treatment planning strategy to help preserve patients' QoL.

A Comprehensive Deep Learning Framework for Automatic Target Volumes Segmentation in Post-Operative Stereotactic Partial Breast Irradiation (S-PBI)

PURPOSE/OBJECTIVE(S)

In S-PBI, accurate delineation of post-surgical tumor bed volume (TBV) and clinical target volume (CTV) are crucial tasks to achieve effective radiotherapy outcomes. However, manual contouring is labor intensive, time consuming, and largely relies on the experience of clinicians. We aimed to propose a deep learning (DL) approach which mimics physicians' contouring practice to accurately segment target volumes in post-operative breast CT images.

MATERIALS/METHODS

Our approach incorporated domain knowledge into a 3D U-Net based DL model for breast target volumes (TBV and CTV) delineation. Our TBV segmentation approach was inspired by the marker-guidance procedure in manual delineation, where the visual clues provided by the markers assist physicians in defining TBV. For this purpose, a distance-transformation coupled with a Gaussian filter was adopted to convert markers' locations on the CT images to saliency maps. Subsequently, the CT images and the corresponding saliency maps formed a two-channel input for the segmentation model. For CTV segmentation, TBV was incorporated as an input in addition to the CT images, guiding the model to encode the location-related image features. The architecture allowed the network to emulate the oncologist's manual delineation where CTV is derived from TBV via a margin expansion, followed by correcting the extensions for anatomical barriers of tumor invasion (e.g., skin, chest wall). We retrospectively collected 175 prone CT images from 35 post-operative breast cancer patients who received 5-fraction partial breast irradiation (PBI) regimen on a Co-60 prone based S-PBI unit. The 35 patients were randomly split into 25, 5, and 5 for model training, validation, and testing respectively.

RESULTS

We evaluated the performance of the developed DL model on the testing dataset by comparing the predicted volumes with the manually delineated contours (ground truth) using Dice similarity coefficient (DSC), 95th percentile Hausdorff distance (HD95), and average symmetric surface distance (ASD). For TBV segmentation, our model achieved mean (standard deviation) of 0.76 (±2.7), 6.76 (±1.83) mm, and 1.9 (±0.66) mm for DSC, HD95, and ASD respectively. For CTV segmentation, our model achieved 0.94 (±0.02), 2.46 (±0.5) mm, and 0.53 (±0.14) mm for DSC, HD95, and ASD respectively. The proposed auto-segmentation approach generated TBV and CTV masks in ∼11 seconds per CT volume, implying significantly improved efficiency compared to manual contouring.

CONCLUSION

We developed a comprehensive DL framework mimicking clinical contouring practice for auto-segmentation of target volumes in S-PBI. The results demonstrated high levels of agreement between the predicted contours and physicians' manual contours. The approach is promising for improving the efficiency and accuracy of the on-line treatment planning workflow, such as adaptive based S-PBI.

[Application of different prognostic scores in liver transplantation decision-making for acute-on-chronic liver failure]

Objective: To compare the impact of different prognostic scores in patients with acute-on-chronic liver failure (ACLF) in order to provide treatment guidance for liver transplantation. Methods: The information on inpatients with ACLF admitted at Beijing You'an Hospital Affiliated to Capital Medical University and the First Affiliated Hospital of Zhejiang University School of Medicine from January 2015 to October 2022 was collected retrospectively. ACLF patients were divided into liver transplantation and non-liver transplantation groups, and the two groups prognostic conditions were followed-up. Propensity score matching was carried out between the two groups on the basis of liver disease (non-cirrhosis, compensated cirrhosis, and decompensated cirrhosis), the model for end-stage liver disease incorporating serum sodium (MELD-Na), and ACLF classification as matching factors. The prognostic condition of the two groups after matching was compared. The difference in 1-year survival rate between the two groups was analyzed under different ACLF grades and MELD-Na scores. The independent sample t-test or rank sum test was used for inter-group comparison, and the χ (2) test was used for the comparison of count data between groups. Results: In total, 865 ACLF inpatients were collected over the study period. Of these, 291 had liver transplantation and 574 did not. The overall survival rates at 28, 90, and 360 days were 78%, 66%, and 62%, respectively. There were 270 cases of matched ACLF post-liver transplantation and 270 cases without ACLF, in accordance with a ratio of 1:1. At 28, 90, and 360 days, patients with non-liver transplantation had significantly lower survival rates (68%, 53%, and 49%) than patients with liver transplantation (87%, 87%, and 78%, respectively; P < 0.001). Patients were classified into four groups according to the ACLF classification criteria. Kaplan-Meier survival analysis showed that the survival rates of liver transplantation and non-liver transplantation patients in ACLF grade 0 were 77.2% and 69.4%, respectively, with no statistically significant difference (P = 0.168). The survival rate with an ACLF 1-3 grade was significantly higher in liver transplantation patients than that of non-liver transplantation patients (P < 0.05). Patients with ACLF grades 1, 2, and 3 had higher 1-year survival rates compared to non-liver transplant patients by 50.6%, 43.6%, and 61.7%, respectively. Patients were divided into four groups according to the MELD-Na score. Among the patients with a MELD-Na score of < 25, the 1-year survival rates for liver transplantation and non-liver transplantation were 78.2% and 74.0%, respectively, and the difference was not statistically significant (P = 0.149). However, among patients with MELD-Na scores of 25-30, 30-35, and≥35, the survival rate was significantly higher in liver transplantation than that of non-liver transplantation, and the 1-year survival rate increased by 36.4%, 54.9%, and 62.5%, respectively (P < 0.001). Further analysis of the prognosis of patients with different ACLF grades and MELD-Na scores showed that ACLF grades 0 or 1 and MELD-Na score of < 30 had no statistically significant difference in the 1-year survival rate between liver transplantation and non-liver transplantation (P > 0.05), but in patients with MELD-Na score≥30, the 1-year survival rate of liver transplantation was higher than that of non-liver transplantation patients (P < 0.05). In the ACLF grade 0 and MELD-Na score of≥30 group, the 1-year survival rates of liver transplantation and non-liver transplantation patients were 77.8% and 25.0% respectively (P < 0.05); while in the ACLF grade 1 and MELD-Na score of≥30 group, the 1-year survival rates of liver transplantation and non-liver transplantation patients were 100% and 20.0%, respectively (P < 0.01). Among patients with ACLF grade 2, the 1-year survival rate with MELD-Na score of < 25 in patients with liver transplantation was 73.9% and 61.6%, respectively, and the difference was not statistically significant (P > 0.05); while in the liver transplantation patients group with MELD-Na score of ≥25, the 1-year survival rate was 79.5%, 80.8%, and 75%, respectively, which was significantly higher than that of non-liver transplantation patients (36.6%, 27.6%, 15.0%) (P < 0.001). Among patients with ACLF grade 3, regardless of the MELD-Na score, the 1-year survival rate was significantly higher in liver transplantation patients than that of non-liver transplantation patients (P < 0.01). Additionally, among patients with non-liver transplantation with an ACLF grade 0~1 and a MELD-Na score of < 30 at admission, 99.4% survived 1 year and still had an ACLF grade 0-1 at discharge, while 70% of deaths progressed to ACLF grade 2-3. Conclusion: Both the MELD-Na score and the EASL-CLIF C ACLF classification are capable of guiding liver transplantation; however, no single model possesses a consistent and precise prediction ability. Therefore, the combined application of the two models is necessary for comprehensive and dynamic evaluation, but the clinical application is relatively complex. A simplified prognostic model and a risk assessment model will be required in the future to improve patient prognosis as well as the effectiveness and efficiency of liver transplantation.

Current status and research progress of nanoparticle application in superficial fungal infection

Superficial fungal infections (SFIs) are characterized by diverse etiologies, complex pathogenesis, and marked geographical differences in patient symptoms. Conventional management of SFIs is associated with complications such as hepatotoxicity, skin problems, severe headaches, and clinical difficulties including intractable relapses and drug-drug interactions in patients with chronic diseases remain to be addressed. Moreover, in topical treatment, low penetration of antifungal drugs in hard tissues such as finger (toe) nails and drug-resistant fungi are emerging concerns in current antifungal therapy. Nanotechnology has been a leading research topic in recent years for new dosing forms of antifungal drugs, chemical modification of traditional drugs, and pharmacokinetic improvement, providing potential opportunities for the effective treatment of SFIs. The present study reviewed the direct use of nanoparticles in SFIs and the use of nanoparticles as carriers in SFIs and discussed their future medicinal applications.

Graphical Abstract

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