Optimal Threshold Research Articles

Diagnostic accuracy of node-RADS for the detection of lymph node invasion: a systematic review and meta-analysis.

To conduct a meta-analysis assessing the diagnostic performance of the node reporting and data system (Node-RADS) for detecting lymph node (LN) invasion. We performed a systematic literature search of online scientific publication databases from inception up to July 31, 2024. We used the quality assessment of diagnostic accuracy studies-2 (QUADAS-2) to assess the study quality, and heterogeneity was determined by the Q-test and measured with I2 statistics. We employed the hierarchic summary ROC (HSROC) model to estimate the summary sensitivity and specificity. Subgroup analyses were conducted according to the imaging modality and cutoff values. A total of 13 studies involving 1341 participants met the inclusion criteria. Pooled summary estimates of sensitivity, specificity, and area under the curve of HSROC were 0.79 (95% CI: 0.66-0.88), 0.86 (95% CI: 0.80-0.90), and 0.90 (95% CI: 0.87-0.92). Subgroup analysis showed that the pooled sensitivity and specificity for CT were 0.74 (95% CI: 0.63-0.83) and 0.84 (95% CI: 0.74-0.91), whereas for MRI were 0.84 (95% CI: 0.59-0.95) and 0.88 (95% CI: 0.81-0.93), respectively. Node-RADS demonstrates the promising potential for the prediction of LN invasion, with high specificity but moderate sensitivity, particularly with optimal cutoff value ≥ 3. Indirect comparisons showed no significant difference between CT and MRI regarding overall diagnostic accuracy. Question Since the Node-RADS has been proposed, a number of studies have assessed its diagnostic performance for evaluating LN invasion. Findings Node-RADS demonstrated high specificity but moderate sensitivity, and cutoff ≥ 3 is the optimal threshold; indirect comparison suggested no significant difference between CT and MRI. Clinical relevance This study synthesized currently available evidence on studies of utilizing Node-RADS for assessing LNI in patients with various cancers, providing valuable insights for radiologists for utilizing this new risk scoring system in clinical practice.

Pentraxin-3 as a novel prognostic biomarker in non-neutropenic invasive pulmonary aspergillosis patients.

The incidence of invasive pulmonary aspergillosis (IPA) in non-neutropenic patients is increasing. This study aimed to evaluate the clinical outcomes and risk factors for mortality in non-neutropenic IPA patients. We conducted a prospective, multicenter study from August 2020 to February 2024, enrolling 565 patients with suspected IPA. The study cohort comprised 195 IPA (non-neutropenic) cases and 370 non-IPA cases. Peripheral blood and bronchoalveolar lavage fluid (BALF) specimens were collected to measure pentraxin-3 (PTX3) levels. Additionally, demographic data, clinical characteristics, and antifungal therapy of each patient were recorded. We analyzed factors associated with 30- and 90-day mortality. IPA patients exhibited higher mortality rates compared to non-IPA patients, with 30-day rates of 26.15% versus 8.38% (P < 0.001) and 90-day rates of 34.36% versus 13.24% (P < 0.001). Higher plasma and BALF PTX3 levels were associated with poor prognosis in IPA patients. ROC curve analysis identified optimal PTX3 thresholds of 4.29 ng/mL in BALF (sensitivity, 67.1%; specificity, 81.4%) and 7.11 ng/mL in plasma (sensitivity, 73.4%; specificity, 82.8%) for predicting mortality. Multivariate Cox regression analysis confirmed PTX3 levels in plasma (hazard ratio [HR] 3.87, 95%CI [1.87-8.00], P＜0.001) and BALF (HR 2.40 [1.19-4.84], P = 0.014) were independent prognostic factors for IPA mortality. Additionally, positive galactomannan test results in both BALF and plasma were initially correlated with increased mortality in IPA patients. However, after adjusting for potential confounding factors, this correlation no longer remained statistically significant. In conclusion, PTX3 is a promising prognostic biomarker of mortality in IPA patients.IMPORTANCEStudies have confirmed the value of pentraxin-3 (PTX3) in the diagnosis of invasive pulmonary aspergillosis (IPA), yet its prognostic significance in IPA remains unclear. This study found that in non-neutropenic IPA patients, plasma and bronchoalveolar lavage fluid (BALF) levels of PTX3 are independently associated with poor outcomes. Furthermore, the optimal cutoff values of PTX3 for predicting a poor prognosis of IPA are 4.29 ng/mL in BALF and 7.11 ng/mL in plasma. These findings could help us better manage IPA in non-neutropenic patients, potentially enhancing the prognosis of patients with this condition.

Clinical utility of regions of homozygosity (ROH) identified in exome sequencing: when to pursue confirmatory uniparental disomy testing for imprinting disorders?

Regions of homozygosity (ROH) could implicate uniparental disomy (UPD) on specific chromosomes associated with imprinting disorders. Though the algorithms for ROH detection in exome sequencing (ES) have been developed, optimal reporting thresholds and when to pursue confirmatory UPD testing for imprinting disorders remain in ambiguity. This study used a data-driven approach to assess optimal reporting thresholds of ROH in clinical practice. ROH analysis was performed using Automap in a retrospective cohort of 8,219 patients and a prospective cohort of 1,964 patients with ES data. Cases with ROH on imprinting-disorders related chromosomes were selected for additional methylation-specific confirmatory testing. The diagnostic yield, the ROH pattern of eventually diagnosed cases and optimal thresholds for confirmatory testing were analyzed. In the retrospective analysis, 15 true UPD cases of imprinting disorders were confirmed among 51 suspected cases by ROH detection. Pattern of ROH differed between confirmed UPD and non-UPD cases. Maximized yield and minimized false discovery rate of confirmatory UPD testing was achieved at the thresholds of >20 Mb or >25 % chromosomal coverage for interstitial ROH, and >5 Mb for terminal ROH. Current recommendation by ACMG was nearly optimal, though refined thresholds as proposed in this study could reduce the workload by 31 % without losing any true UPD diagnosis. Our refined thresholds remained optimal after independent evaluation in a prospective cohort. ROH identified in ES could implicate the presence of clinically relevant UPD. This study recommended size and coverage thresholds for confirmatory UPD testing after ROH detection in ES, contributing to the development of evidence-based reporting guidelines.

The Value of Lacrimal Gland Ultrasonography and Shear Wave Elastography in the Evaluation of Primary Sjögren's Syndrome: A Cross-Sectional Study.

This study evaluates the effectiveness of lacrimal gland ultrasonography (LGUS) and shear wave elastography (SWE) in distinguishing primary Sjögren's syndrome (PSS) patients from healthy controls and examines their role in assessing disease activity and prognosis. A total of 35 PSS patients and 23 age- and gender-matched healthy controls were included. LGUS was used to grade lacrimal gland structure, while SWE assessed gland elasticity. Disease activity and prognosis were evaluated using european league against rheumatism sjögren's syndrome disease activity index (ESSDAI)and serologic markers. Compared with healthy controls, LGUS, Emean, and shear wave velocity (SWV) were significantly higher in PSS patients. The optimal cut-off value of LGUS for diagnosis of PSS was 2 (area under the curve [AUC]: 0.832, sensitivity: 80.0%, specificity: 69.6%), the optimal thresholds for diagnosis of PSS using Emean and SWV values are 9.4 kPa (AUC: 0.768, sensitivity: 65.7%, specificity: 82.6%) and 1.7 m/s (AUC: 0.823, sensitivity: 71.4%, specificity: 91.3%), respectively. There are statistical differences in Emean and SWV between subgroups based on european league against rheumatism sjögren's syndrome disease activity index (ESSDAI); there are statistical differences in LGUS, Emean, and SWV between subgroups based on IgG levels and complement titers. LGUS and SWE are accurate, noninvasive diagnostic tools for PSS and may serve as indicators of disease activity and prognosis.

A comparative study on the diagnostic value of 18F-PSMA PET/CT PRIMARY score and PSMA expression score for clinically significant prostate cancer

Objective: To compare the diagnostic value of fluorine 18-labelled prostate-specific membrane antigen (PSMA) PET/CT PRIMARY score and PSMA expression score for clinically significant prostate cancer (csPCa). Methods: The data of 70 patients with prostate cancer who underwent radical prostatectomy at Beijing Hospital from February 1, 2019 to February 29, 2024 were retrospectively analyzed. All patients underwent whole body 18F-PSMA PET/CT examination before surgery and pathological large sections of prostate specimens were made after surgery. According to the pathological section results, the lesions were divided into csPCa group (Gleason scores≥7) and non-csPCa group (Gleason scores=6 or benign). The PRIMARY score and PSMA expression score were used to evaluate prostatic lesions on PSMA PET/CT images, respectively. The differences in PRIMARY score, PSMA expression score, maximum standardized uptake value (SUVmax), lesion-to-background ratios (LBR), PSMA uptake characteristics, and location distribution were compared between csPCa group and non-csPCa group. Multivariate logistic regression analysis was performed to determine the correlation factors for the incidence of csPCa. By plotting the receiver operator characteristic (ROC) curve and calculating the area under the curve (AUC), the optimal diagnostic threshold for csPCa of each factor was determined. The differences in AUC were compared using the Delong test. Quantitative data was represented as M (Q1, Q3). Results: The 70 patients aged 70 (64, 75) years with a total of 108 lesions, including 83 lesions (76.9%) in the csPCa group and 25 lesions (23.1%) in the non-csPCa group. There were differences between csPCa group and non-csPCa group in PRIMARY score [4 (3, 5) vs 2 (1, 4)], PSMA expression score [2 (2, 2) vs 1 (1, 2)], SUVmax [9.10 (5.70, 15.80) vs 5.40 (3.35, 6.90)], LBR [2.86 (2.09, 4.53) vs 1.96 (1.42, 2.58)], and proportion of focal uptake patterns [74.7% (62/83) vs 32.0% (8/25)] (all P<0.05). There was no statistically significant difference in the location distribution between the two groups (P>0.05). Multivariate logistic regression analysis indicated the higher the PRIMARY score, the higher the risk of developing csPCa (OR=1.863, 95%CI: 1.360-2.552). ROC curves revealed that the AUCs of the PRIMARY score and PSMA expression score for csPCa were 0.751 (95%CI: 0.659-0.829) and 0.697 (95%CI: 0.601-0.781), respectively, without statistically difference (Z=1.438, P>0.05). The cut-off values for diagnosing csPCa were 3 score for PRIMARY score and 2 score for PSMA expression score, respectively. Conclusions: The higher the 18F-PSMA PET/CT PRIMARY score, the higher the risk of developing csPCa. The PRIMARY score has good diagnostic efficacy for csPCa.

Adaptive Multi-Kernel Graph Neural Network for Drug-Drug Interaction Prediction.

Combination therapy, which synergistically enhances treatment efficacy and inhibits disease progression through the combined effects of multiple drugs, has emerged as a mainstream approach for treating complex diseases and alleviating symptoms. However, drug-drug interactions (DDIs) can sometimes lead to adverse reactions, potentially endangering lives. Therefore, developing efficient and accurate DDI prediction methods is crucial for elucidating drug mechanisms and preventing side effects. Current prediction methods often focus solely on the presence of interactions between drugs when constructing DDI graphs, neglecting the specific types of DDIs. This oversight can result in a decline in predictive performance. To address this issue, we propose an Adaptive Multi-Kernel Graph Neural Network (AMKGNN) for DDI prediction. AMKGNN differentiates DDIs into increase-type and decrease-type interactions, constructing separate increased DDI and decreased DDI graphs as convolutional kernels. AMKGNN employs a graph kernel learning mechanism that adaptively determines the optimal threshold between high-frequency and low-frequency signals in the network to capture node embeddings. Initially, AMKGNN learns drug embedding representations based on these two graph convolutional kernels and various drug features. These representations are then concatenated and input into a deep neural network to predict potential DDIs. The results show that our model achieved AUC and AUPR values above 90% across three sub-tasks on two datasets, significantly outperforming the other five comparison models. Furthermore, ablation experiments and case studies validate the superiority of AMKGNN.

Understanding sustainability of woody species suitability zones on the Loess Plateau for optimal creation zone selection in response to future climate change.

Climate change has profound implications for the distribution of suitable habitats for woody species. In this study, we assessed the optimal distribution thresholds for twelve woody species on the Loess Plateau using the Maximum Entropy (MaxEnt) model, incorporating sample points of tree species alongside relevant environmental variables. We analyzed the sustainability of potentially suitable zones and proposed a framework for selecting a regulatory model to establish the most suitable creation zones in response to future climate change. The results indicated that: (1) The distributions potentially suitable for Platycladus orientalis and Pinus tabuliformis were predominantly influenced by mean annual temperatures, whereas Pinus armandii and Quercus aliena var. acutiserrata exhibited optimal conditions at temperatures around -4°C. Both Hippophae rhamnoides and Larix gmelinii var. principis-rupprechtii had suitable threshold precipitation levels exceeding 200mm, with optimal thresholds surpassing 250mm. (2) Most high-suitability zones for woody species across various future climate scenarios were primarily located in southern regions, including examples such as Betula platyphylla Sukaczev, Platycladus orientalis, Pinus sylvestris var. mongholica. Some of these high-suitability areas displayed insular and linear distributions, notably Larix gmelinii var. principis-rupprechtii, Quercus aliena var. acutiserrata, Salix cheilophila. (3) There was no southward shift in the northern boundary of the sustainability zones for any woody species across the different scenarios. Betula platyphylla and Salix babylonica exhibited the broadest distribution of sustainability zones. (4) The most suitable areas for the establishment of woody species were primarily found in the western, southern, and eastern regions, whereas the northern and central areas were less favorable for tree growth. Among the scenarios analyzed, SSP585 presents the most extensive distribution area. This study is expected to improve the distribution structure of woody species and the implementation of management policies.

Optimal calorie restriction threshold: effect of FATmax exercise combined with different proportions of calorie restriction on hypercholesterolemia

Background/ObjectivesTo evaluate the impact of maximal fat oxidation intensity exercise combined with calorie restriction intervention on lipid-related parameters in a hypercholesterolemic population, and to determine if an optimal range of calorie restriction exists for effectively enhancing blood lipid profiles.MethodsA 4-week intervention study combined exercise and calorie restriction for 64 patients aged 18–60 with secondary hypercholesterolemia. Ultimately, 43 participants completed the study. The dietary intervention adhered to the principles of a balanced diet, with meal plans designed to provide three meals per day for the duration of the study. Each subject’s daily calorie intake was set to match their individual resting energy expenditure (REE) plus varying proportions of physical activity (PA) calories. Participants were divided into four groups based on these proportions: REE only, REE + PA33%, REE + PA67%, and REE + PA100%. FATmax exercises were conducted 5 times per week, lasting 1 h each.Results1) Compared with baseline, subjects’ body weight, fat mass and body fat rate decreased significantly; fat-free mass also decreased significantly in the REE, REE + PA33%, and REE + PA67% groups. 2) Subjects’ serum TC decreased significantly; serum LDL-C and ApoB decreased significantly in the REE, REE + PA33%, and REE + PA67% groups; there were no significant changes in serum HDL-C and ApoA1. 3) Serum PCSK9 was significantly decreased in the REE and the REE + PA 67% groups; serum LDLR was significantly decreased in all groups of subjects. 4) Between the groups, the rate of change in serum LDL-C was significantly different.ConclusionFATmax exercise combined with proper proportions of calorie restriction can significantly decrease serum cholesterol levels and fat mass in hypercholesterolemic patients. Nevertheless, it is misleading to assume that a drastic reduction in calorie intake invariably results in superior outcomes. Optimal cost-effectiveness may be achieved within a calorie restriction range of REE + PA33-67%.

Multilevel support-assisted prototype optimization network for few-shot medical segmentation of lung lesions

Medical image annotation is scarce and costly. Few-shot segmentation has been widely used in medical image from only a few annotated examples. However, its research on lesion segmentation for lung diseases is still limited, especially for pulmonary aspergillosis. Lesion areas usually have complex shapes and blurred edges. Lesion segmentation requires more attention to deal with the diversity and uncertainty of lesions. To address this challenge, we propose MSPO-Net, a multilevel support-assisted prototype optimization network designed for few-shot lesion segmentation in computerized tomography (CT) images of lung diseases. MSPO-Net learns lesion prototypes from low-level to high-level features. Self-attention threshold learning strategy can focus on the global information and obtain an optimal threshold for CT images. Our model refines prototypes through a support-assisted prototype optimization module, adaptively enhancing their representativeness for the diversity of lesions and adapting to the unseen lesions better. In clinical examinations, CT is more practical than X-rays. To ensure the quality of our work, we have established a small-scale CT image dataset for three lung diseases and annotated by experienced doctors. Experiments demonstrate that MSPO-Net can improve segmentation performance and robustness of lung disease lesion. MSPO-Net achieves state-of-the-art performance in both single and unseen lung disease segmentation, indicating its potentiality to reduce doctors’ workload and improve diagnostic accuracy. This research has certain clinical significance. Code is available at https://github.com/Tian-Yuan-ty/MSPO-Net.

An optimal path threshold method for rigorously identifying extreme climate events

Abstract The frequent occurrence of extreme hydroclimate events has a significant impact on ecosystems and socio-economic systems. However, intercomparisons of extreme events are often hampered by inconsistent definitions and standardizations for different types of events. Here we introduce the OPT method, a dynamic programming-based approach that adaptively determines the optimal thresholds for defining extreme events at specific severity levels. Two case studies demonstrate its applicability. The first case study presents a long-term comparison of air heatwaves and lake heatwaves in Lake Mead. The algorithm adaptively selects thresholds to identify a comparable number of events at various severity levels. The second case study examines compound hot, dry, and windy events in California, exploring threshold selection for multivariable extremes and investigating their potential relationship with wildfires. The OPT method proves effective for adaptably and objectively analyzing complex and multifactorial extreme events.&amp;#xD;

P0449 qFIT as a predictor of relapse in quiescent Crohn’s disease – initial results from the Stratifying Crohn’s Using Biomarker Assessment (SCUBA) study

Abstract Background The Stratifying Crohn’s Using Biomarker Assessment (SCUBA) study assessed a number of biomarkers (Faecal Calprotectin (FCP), quantitative faecal immunochemical testing (qFIT), C reactive protein (CRP), plasma and faecal zinc) in their ability to predict relapse in quiescent Crohn’s disease (CD). FCP is widely utilised as a surrogate marker in the monitoring of CD but is labour intensive and expensive. Population qFIT testing is established in colorectal cancer screening and is relatively cheap and simple to analyse. qFIT has been shown to predict relapse in ulcerative colitis1. Here we present a comparison of qFIT and FCP at predicting relapse in quiescent luminal CD. Methods A single centre prospective cohort study was performed. Patients with clinically quiescent CD (Harvey Bradshaw Index ≤3) were identified and provided paired, baseline FCP, qFIT and routine biochemical workup. Patients over 50 years were excluded due to overlay with bowel cancer screening programmes as were those with isolated upper GI or perianal disease. Patients were followed up over 1 year or until relapse defined by need for escalation of CD related treatment, steroids, surgery or hospitalisation for CD. Results 274 patients were recruited with 211 returning paired baseline faecal samples. Median age was 34 years (range 18-49) and 108/211 (51.1%) were female. Median HBI at submission was 1 and median FCP, qFIT and CRP was 61µg/g stool, 9 µg Hb/g and 2 mg/l respectively. 42/211 (19.9%) experienced a relapse during follow up. Both FCP and qFIT showed good ability to predict relapse at 1 year, performing comparably, with the area under the receiver operating characteristic curves (AUROC) 0.80 (95% CI 0.74- 0.85) vs 0.75 (95% CI 0.68-0.80)(p=0.28). Combination biomarker use did not significantly improve performance, AUROC 0.82 (95%CI 0.76- 0.87) p=0.34 and p=0.07 respectively. Optimal threshold for prediction of relapse was &amp;gt;180 µg/g stool for FCP (sensitivity 0.69 and specificity 0.85) and &amp;gt;9 µg Hb/g for qFIT (sensitivity 0.65 and specificity 0.82). Utilising these thresholds (figure 1) patients with both FCP and qFIT above threshold had a probability of relapse free survival of 16.7% (95% CI 0.20%-31.6%) at 1 year vs 95.4% (95% CI 91.7%-99.0%, p&amp;lt;.0001) in patients under threshold. In combination, FCP and qFIT had a positive predictive value of 50.1% and negative predictive value (NPV) of 97.6%. Conclusion qFIT performs well and comparably to FCP in predicting relapse in clinically quiescent luminal CD and may be used in preference to FCP being an easier and cheaper test to undertake. When combined at optimal thresholds, qFIT &amp; FCP show significant discriminatory ability in prediction of CD relapse-free survival with an excellent NPV.

P0666 Early symptom improvements predict later clinical response and remission at week 12 for patients with ulcerative colitis treated with mirikizumab in the LUCENT-1 study

Abstract Background Mirikizumab, a p19-directed interleukin-23 monoclonal antibody, is effective in inducing clinical remission at Week(W) 12 and maintaining clinical remission through 3 years in patients with moderately-to-severely active ulcerative colitis (UC) (LUCENT-1, NCT03518086; LUCENT-2, NCT03524092; LUCENT-3, NCT03519945).1, 2 Here we determine whether early symptom response predicts clinical response and clinical remission at the end of induction. Methods Receiver operating characteristic (ROC) curves were used to assess if LUCENT-1 patients’ symptomatic improvement (≥ 30% symptom response of stool frequency and rectal bleeding) at W2, W4, W6, and W8, in response to mirikizimab therapy predicts W12, clinical remission and clinical response. Sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) were used to assess predictive value while the area under the ROC curve (AUC) provided the overall predictability. PPV was defined as the percentage of patients with clinical response and remission at W12 after achieving symptomatic score improvement from baseline. NPV was defined as the percentage of patients without clinical response (or clinical remission) at W12 when achieving symptom improvement from baseline. Youden’s Index, defined as sensitivity + specificity - 1, was used to identify the optimum prediction threshold. Results A significantly greater proportion of patients treated with mirikizumab achieved symptom improvements compared to placebo as early as W2 and through W12 (Figure 1). ROC curve analysis of symptomatic improvement over time versus W12 clinical remission, showed increasing predictability from W2 (66%), and W4 (76%), to W6 (79%), and W8 (78%). Similar predictabilities of symptomatic improvement from W2 (69%), W4 (78%), W6 (82%), to W8 (83%) versus W12 clinical response were observed (Figure 2). As early as W2, patients with symptomatic improvement of ≥30% from baseline, had 83% NPV and the NPV reached 90%, 97%, and 96%, respectively at W4, W6, W8 for achieving clinical remission at W12. Conclusion Patients treated with mirikizumab for induction achieved significantly greater symptom response or greater symptom improvements (≥30%) versus placebo as early as W2. A minimum of 30% improvement in symptomatic scores at W4 and W6 could provide an optimum prediction for both clinical response and clinical remission at W12. Additional studies need to be done to assess the value of these thresholds.

Correlations Between MR Apparent Diffusion Coefficients and PET Standard Uptake Values in Simultaneous MR-PET Imaging of Prostate Cancer

This study evaluated the hypothesis that 68Ga-PSMA-11 PET SUV, obtained via an advanced DL approach, correlates better with MR ADC maps than values from conventional PET-MR. Additionally, we aimed to identify the optimal SUV threshold for maximum correlation with ADC values. A cohort of 32 prostate cancer patients underwent CT and corresponding PET-MR imaging. The dataset underwent K-fold cross-validation, dividing it into four folds. In each fold, 24 patients were used for training, and 8 for validation to create DL models. ADC maps from 27 out of 32 patients were successfully aligned with T2 images for detailed analysis, revealing an inverse correlation (ρ = −0.20 to −0.51) between ADC and SUV values in prostate cancer zones. Statistically significant differences in mean SUV values were observed between PETMRI and PETDL. DL-based SUV values show a stronger correlation with ADC than conventional PET-MR values in our investigation.

P0919 Correlation between trough levels of risankizumab and clinical and biological remission in patients with moderate to severe Crohn’s disease: a retrospective multicenter study (RISE-CD)

Abstract Background Inflammatory bowel disease management has evolved in recent years, with the emergence of new biotherapies such as risankizumab,(RZB) an interleukin (IL) 23 p19 inhibitor, with demonstrated efficacy in moderate-to-severe Crohn’s disease. While the relationship between trough levels and clinical remission is well established for anti-TNF alpha agents, it has yet to be demonstrated for new molecules of interest. The aim of this study was to investigate the correlation between RZB trough levels and clinical and biological remission at 6, 12 and 18 months. Methods This retrospective multicenter study included patients with moderate-to-severe Crohn’s disease from 4 centers, who were being treated with RZB after failure of all other approved biotherapy lines. Clinical activity, assessed by the Harvey-Bradshaw Index (HBI) and biological activity with CRP and fecal calprotectin, as well as serum RZB levels by Elisa technique (Biosynex) were collected. The primary endpoint was clinical and biological remission at 12 months, defined as HBI &amp;lt; 4, CRP &amp;lt; 5 mg/L and fecal calprotectin &amp;lt; 250 µg/g of stool. Secondary objectives were the correlation between RZB levels and clinical and biological remission at 6 and 18 months, treatment persistence, and safety. Results Overall, 43 patients were included in 4 centers. Most patients had ileocolic Crohn’s disease (44.7%), 50% had ano-perineal lesions, 23.7% had extra-intestinal manifestations and 71.7% had a history of bowel resection. Six patients (15.8%) were receiving a combination of advanced therapies with upadacitinib or golimumab. At 12 months, 30.2% of patients were in clinical and biological remission (n=13) and had significantly higher RZB trough levels than patients who were not in remission (8.26 ± 4.66 vs. 4.44 ± 2.37 respectively; p=0.002). The ROC curve identified an optimal risankizumab trough levels threshold of 7.7 µg/mL for predicting clinical and biological remission at 12 months (sensitivity 61.5%; specificity 92%). At 6 and 18 months, 11.7% (n=5) and 34.9% (n=15) of patients were in clinical remission and had significantly higher RZB trough levels. At 6 months, 12 months and 18 months, 43 (100%), 38 (88.4%) and 31 (72%) patients were still on RZB. No patient developed anti-risankizumab antibodies. Conclusion In our multicenter study, with the largest number of patients analyzed to date, trough levels of risankizumab were correlated with clinical and biological response at 12 months in patients with moderate-to-severe Crohn’s disease, in line with data from previous single-center studies but larger prospective studies are still needed.

Mechanical Properties and Microscopic Fractal Characteristics of Lime-Treated Sandy Soil

In order to reveal the intrinsic mechanism of the mechanical properties of lime-treated sandy soil from a microscopic perspective, triaxial tests were conducted to analyze the macroscopic mechanical characteristics of sandy soil with different lime contents (0%, 5%, 8%, and 12%). The changes in the microstructure of the lime-treated sandy soil were studied through scanning electron microscopy, energy-dispersive spectroscopy, and mercury intrusion tests, combined with fractal theory for quantitative characterization. The results indicate that the stress–strain curve of lime-treated sandy soil can be divided into four stages: linear elastic, non-linear, failure, and residual strength. With the increase in lime content, the peak stress and cohesion first increase and then decrease, while the internal friction angle first decreases and then increases, suggesting the presence of an optimal threshold for lime content between 5% and 12%. The failure mode transitions from diagonal shear failure to bulging failure, significantly enhancing stability; both the fitted Mohr–Coulomb and Drucker–Prager failure criteria effectively reflect the failure patterns of the specimens in principal stress space. The results based on the three fractal dimensions demonstrate that lime-treated sandy soil exhibits clear fractal characteristics, with the highest fractal dimension value at a lime content of 8%, corresponding to the highest overall strength. In addition, the fractal dimension shows a binomial relationship with pore characteristic parameters and shear strength parameters; it can effectively characterize the complexity of the microstructure and accurately predict changes in shear strength parameters.

P0399 Combination of MR Cell Size Imaging and Magnetization Transfer Imaging Reflecting Intestinal Fibrosis to Predict Intestinal Disease Progression in Patients with Crohn’s Disease

Abstract Background More than half of Crohn’s disease (CD) patients develop complications such as strictures due to intestinal fibrosis1. Intestinal fibrosis is characterized by proliferation of mesenchymal cells, especially myofibroblasts transdifferentiated from fibroblasts, and thus excessive accumulation of extracellular collagen2. Therefore, simultaneously assessing mesenchymal cells and extracellular collagen can offer a more comprehensive perspective of intestinal fibrosis and enhance predictions of disease progression. Magnetization transfer imaging (MTI) can accurately quantify intestinal collagen levels3. Recently, time-dependent diffusion MRI (TD-dMRI) demonstrated the efficacy in mapping cellular microstructures4. Methods From July 2023 through March 2024, 124 CD patients were prospectively enrolled with 31 underwent surgery at baseline. Participants underwent TD-dMRI to obtain microstructural parameters, such as cell diameter (d), intracellular volume fraction (fin), extracellular diffusivity (Dex) and Cellularity. MT-MRI were performed to obtain the normalized MT ratio (MTR) with a reported threshold of ≥0.71 indicating high collagen levels. For surgical patients, the target intestines, including diseased and normal segments were collected and myofibroblasts/fibroblasts-area-ratio was calculated to reflect mesenchymal cell states and correlated with TD-dMRI parameters. 93 nonsurgical patients were followed up for at least 6 months to evaluate intestinal disease progression. Results In 63 samples from 31 surgical patients, d had the highest correlation with myofibroblasts/fibroblasts-area-ratio (r=0.58; P&amp;lt;0.001). d, fin, cellularity and Dex were significantly different between diseased and normal samples (all P&amp;lt;0.05). Among TD-dMRI parameters, d had the highest AUC (AUC=0.86; P&amp;lt;0.001) for distinguishing diseased and normal samples. The optimal threshold of d was 11 μm and d≥11 μm indicated an activated profibrotic mesenchymal cell state. Therefore, 93 nonsurgical patients were divided into four groups based on the baseline d and normalized MTR: group 1 (d&amp;lt;11 μm, normalized MTR&amp;lt;0.71), group 2 (d≥11 μm, normalized MTR&amp;lt;0.71), group 3 (d≥11 μm, normalized MTR≥0.71), and group 4 (d&amp;lt;11 μm, normalized MTR≥0.71). In follow-up cohort, group 3 had the shortest disease-progression-free survival, followed by groups 2, 4, and 1 (P=0.002). Additionally, multivariable Cox regression analysis indicated that d was the only significant risk factor for disease progression (HR: 1.2; P=0.001). Conclusion TD-dMRI-derived d effectively characterizes fibrosis-associated cell features in CD, and combined with normalized MTR enables a comprehensive assessment of intestinal fibrosis and accurate prediction of disease progression.

P0345 Tailoring Crohn’s disease surveillance in clinical remission: new insights from the Lewis score

Abstract Background Optimal thresholds for Lewis score in the surveillance of patients with known Crohn’s disease (CD) in clinical remission remain uncertain. The aim of this study was to evaluate predictive factors of clinical exacerbation in patients with small bowel inflammatory-type CD in clinical remission, focusing on the yield of the Lewis score. Methods Retrospective, unicentric cohort study including adult patients with known small bowel inflammatory-type, non-stricturing and non-penetrating CD, in clinical remission, who were submitted to small bowel capsule endoscopy for evaluation of mucosal healing. Clinical exacerbation was defined as the need for corticosteroid administration, biological/immunomodulator treatment initiation, intensification or switch, intestinal surgery, or CD-related hospitalization, with a minimum follow-up time of 24 months. Results A total of 63 patients were included, and clinical exacerbation occurred in 18 patients (28.6%), with 8 patients requiring oral corticosteroid administration (12.7%), 12 needing biological/immunomodulator treatment initiation or switch (19.0%), and 2 needing both (3.2%). An age ≤33 years and a Lewis score &amp;gt;225 were found to be independent predictive factors of clinical exacerbation (OR 7.145, p=0.028 and OR 12.585, p=0.005, respectively). Patients who were not in biochemical remission were 14 times more likely to have a clinical exacerbation during follow-up (83.3% vs 42.2%, p=0.003). Furthermore, patients who were not in biochemical remission and who had a Lewis score &amp;gt;225 were 16 times more likely to have a clinical exacerbation (66.7% vs 13.3%, p&amp;lt;0.001). Patients with a Lewis score &amp;gt;225 had an overall risk for clinical exacerbation of 59.1%, compared to 12.2% in those with a Lewis score ≤225 (p&amp;lt;0.001). Additionally, patients with a Lewis score &amp;gt;225 had a shorter period of time free from clinical exacerbation (32±5 vs 80±5 months, χ2=22.414, p&amp;lt;0.001) (figure 1). Conclusion Clinical exacerbation occurred in almost one third of patients with small bowel inflammatory-type CD in clinical remission. An age ≤33 years and a Lewis score &amp;gt;225 were independent predictive factors of clinical exacerbation. The absence of biochemical remission was also associated with clinical exacerbation. A Lewis score &amp;gt;225 was the best threshold to predict clinical exacerbation and shorter period of time free from clinical exacerbation. Therefore, in small bowel CD patients with a Lewis score &amp;lt;225, a wait and watch therapeutic strategy can be applied, since the risk of clinical exacerbation for a minimum 24-month follow-up period is low. However, those with a Lewis score &amp;gt;225 should be considered for therapeutic intensification, especially if younger, in order to prevent clinical exacerbation in the long term.

P0342 Quantitative faecal immunochemical test (qFIT) is comparable to calprotectin as a biomarker of IBD: Prospective longitudinal analysis of disease activity and endoscopic mucosal healing

Abstract Background Quantitative faecal immunochemical test (qFIT) to detect stool haemoglobin is used for colorectal cancer screening at a population level in UK (&amp; Europe) with high patient acceptability due to its ease of use and relative low cost . We evaluate the clinical utility of qFIT with faecal calprotectin (fCal) in IBD. Methods UC and CD patients from the prospective, multi-centre longitudinal MUSIC study (2020-2024; www.musicstudy.uk) were included. qFIT and fCal samples were collected every three months at five time points. qFIT analysis was conducted using the HM-JACKarc automated analyser. Blinded qFIT results were compared with physician global assessment, clinical indices (HBI, SCCAI)*, and endoscopic findings. All patients had active disease at baseline, with a repeat colonoscopy at timepoint 3 to assess for complete mucosal healing (CMH), defined as Mayo-score or SES-CD of 0 in UC and CD respectively. Results 357 qFIT results were analysed from 124 patients (58 colonic CD/ 66 UC). qFIT was significantly higher in active disease compared to remission (n=227 vs. 130; 100µgHb/g vs 2.5 µgHb/g; p&amp;lt;0.001). The ability of qFIT to predict active disease was higher in those with UC than colonic CD AUC 0.77 and 0.69 respectively (in 179 UC /178 CD samples). Optimal threshold for predicting remission was &amp;lt;14µgHb/g, with a sensitivity of 0.73, specificity of 0.66. 27 qFIT results from ileal CD patients showed no significant difference between active disease and remission (p=0.2). 339 qFIT results had paired FCal results. The ability of fCal to predict active disease was higher in UC than colonic CD with AUC of 0.82 and 0.77 respectively. For both IBD types, the AUC was 0.81 [Figure 1]. The optimal fCal level was 240 µg/g for remission, with a sensitivity of 0.76 and specificity of 0.72. Combining qFIT and fCal improved prediction of remission to an AUC of 0.82. qFIT performed better than fCal at predicting mucosal inflammation with an AUC 0.74 vs. 0.67 respectively. In 76 UC patients, Mayo endoscopy scores were paired with mean qFIT levels, showing a correlation: score 0 = 32 µgHb/g, score 1 = 181 µgHb/g, score 2 = 217 µgHb/g, and score 3 = 295 µgHb/g (one-way ANOVA, p = &amp;lt;0.001). 20 patients (from 52) achieving CMH, showed significant reduction in qFIT using paired T-test (107 vs 37 µgHb/g, p=0.026). In the 32 patients with ongoing inflammation, qFIT remained high (213 vs. 170 µgHb/g, p=0.23). Conclusion qFIT is comparable to fCal as a biomarker of IBD activity. With its superior patient acceptability and intrinsic test qualities, it should be considered as routine clinical test in IBD. Further large scale validation is warranted to establish its clinical utility. References *AUC – Area Under Curve **HBI-Harvey Bradshaw Index ***SCCAI – Simple Colitis Activity Index

Analysis of skew, examination of intercorrelations, and determining the optimal threshold for performance invalidity when 10 performance validity tests are administered during a neuropsychological evaluation

ABSTRACT Introduction This study cross-validates and expands upon previous research by examining the optimal number of PVT failures necessary to determine invalid performance when 10 PVTs are administered during a neuropsychological evaluation. Additionally, the study assessed the degree of skewness of individual PVTs and PVT intercorrelations for the overall sample and by validity group. Method Participants were 283 adult neuropsychology outpatients evaluated at an academic medical center. Participants were initially classified as having valid (≤1 PVT failure; n = 225) or invalid (≥2 PVT failures; n = 58; base rate of 20% performance invalidity) performance based on four independent criterion PVTs. Failure rates of 10 additional PVTs were then compared, and sensitivity and specificity were calculated at different thresholds (e.g. ≥1, ≥2, ≥3, ≥4 PVT failures) to determine the optimal threshold for detecting invalid performance while maintaining ≥ 90% specificity. Results Findings indicate that failing ≥ 2 PVTs yielded 86% sensitivity/76% specificity, failing ≥ 3 PVTs yielded 69% sensitivity/92% specificity, failing ≥ 4 PVTs yielded 57% sensitivity/96% specificity, failing ≥ 5 PVTs yielded 29% sensitivity/99% specificity, and failing ≥ 6 PVTs yielded 22% sensitivity/100% specificity. PVT intercorrelations were generally small for the overall sample and by validity group. As expected, data were more highly skewed for patients with valid performance. Conclusions Findings were consistent with previous research and demonstrate that the three-failure threshold optimally detects invalid performance when 10 PVTs are administered. These findings inform the use of multiple PVTs in clinical settings and aid in the interpretation of PVT results.

Optimizing energy threshold selection for low-concentration contrast agent quantification in small animal photon-counting CT.

Gold nanoparticles (GNPs) are widely used for biological research and applications. The in-vivo concentration of GNPs is usually low due to biological safety concerns, thus posing a challenge for imaging. This work investigates on optimal energy threshold selection in photon-counting detector(PCD)-based CT (PCCT) for the quantification of low-concentration GNPs. &#xD;Approach. We derived the mathematical expression of the upper bound of the material decomposition error in the gold image. Comprehensive simulations were implemented for cylindrical phantom with inserts of different GNPs concentrations. CT scans of this phantom were simulated with a 140 kVp x-ray beam under realistic pre-clinical CT dose range. The PCD energy thresholds from 30 to 110 keV were enumerated for 2,3-channel PCCT and the optimal energy thresholds were determined by searching for the lowest decomposition error. &#xD;Main results. The optimal energy threshold(s) to minimize the decomposition error in gold image was 44 keV for the 2-channel PCCT and {34,40} keV for the 3-channel case. Numerical results also validated the derived upper bounds of the decomposition error. &#xD;Significance. This work addressed the need for selecting appropriate energy thresholds for accurate quantification of contrast agent distributions in pre-clinical PCCT. Both the analytical expression of the upper bound of material decomposition error and simulation results showed that the balanced consideration on photon counting noise levels and the numerical properties of the decomposition matrix is required in selecting the appropriate energy thresholds to achieve the most accurate material decomposition. &#xD.