Understanding symptom contribution to sex inequality in bladder and renal cancer stage at diagnosis.

Background: Understanding sex-specific factors contributing to advanced-stage diagnosis can guide interventions to reduce sex inequality in patients with urological cancers. Method: We used linked primary care and cancer registry data to examine associations between symptoms and advanced-stage in 1151 bladder cancer and 440 renal cancer patients diagnosed between January 2012 and December 2015 in England. We performed logistic regression, adjusting for sex, age, deprivation and routes to diagnosis, including interaction terms between symptoms and sex and symptoms and age. Results: Female sex (OR vs. men 1.89 [1.28-2.79]; p = 0.001) and patients presenting with urinary tract infections (OR 2.22 [1.34-3.69]) and abdominal symptoms (OR 2.19 [1.30-3.70]) were associated with increased odds of advanced-stage bladder cancer (vs. haematuria, p = 0.016 for both). Women with haematuria and men with abdominal symptoms (compared with the opposite sex with the same presenting symptom) were more likely to have advanced-stage bladder cancer. Neither sex nor symptom associations were observed for renal cancer. Conclusion: Non-haematuria symptoms are associated with higher risk of advanced-stage bladder cancer. Greater risk of advanced-stage bladder cancer in women may reflect biological differences in haematuria onset and sex differences during diagnostic process. Identifying higher risk women with haematuria may reduce sex inequalities in bladder cancer outcomes.

Plasma-based near-infrared spectroscopy for early diagnosis of lung cancer.

Lung cancer (LC) continues to be a leading death cause in China, primarily due to late diagnosis. This study aimed to evaluate the effectiveness of using plasma-based near-infrared spectroscopy (NIRS) for LC early diagnosis. A total of 171 plasma samples were collected, including 73 healthy controls (HC), 73 LC, and 25 benign lung tumors (B). NIRS was utilized to measure the spectra of samples. Pre-processing methods, including centering and scaling, standard normal variate, multiplicative scatter correction, Savitzky-Golay smoothing, Savitzky-Golay first derivative, and baseline correction were applied. Subsequently, 4 machine learning (ML) algorithms, including partial least squares (PLS), support vector machines (SVM), gradient boosting machine, and random forest, were utilized to develop diagnostic models using train set data. Then, the predictive performance of each model was evaluated using test set samples. The study was conducted in 5 comparisons as follows: LC and HC, LC and B, B and HC, the diseased group (D) and HC, as well as LC, B and HC. Among the 5 comparisons, SVM consistently generated the best performance with a certain pre-processing method, achieving overall accuracy of 1.0 (kappa: 1.0) in the comparisons of LC and HC, B and HC, as well as D and HC. Pre-processing was identified as a crucial step in developing ML models. Interestingly, PLS demonstrated remarkable stability and relatively high predictive performance across the 5 comparisons, even though it did not achieve the top results like SVM. However, none of these algorithms were able to effectively distinguish B from LC. These findings indicate that the combination of plasma-based NIRS with ML algorithms is a rapid, non-invasive, effective, and economical method for LC early diagnosis.

Artificial intelligence breakthroughs in pioneering early diagnosis and precision treatment of breast cancer: A multimethod study.

This article delves into the potential of artificial intelligence (AI) to enhance early breast cancer (BC) detection for improved treatment outcomes and patient care. Utilizing a multimethod approach comprising literature review and experiments, the study systematically reviewed 310 articles utilizing 30 diverse datasets. Among the techniques assessed, recurrent neural network (RNN) emerged as the most accurate, achieving 98.58 % accuracy, followed by genetic principles (GP), transfer learning (TL), and artificial neural networks (ANNs), with accuracies exceeding 96 %. While conventional machine learning (ML) methods demonstrated accuracies above 90 %, DL techniques outperformed them. Evaluation of BC diagnostic models using the Wisconsin breast cancer dataset (WBCD) highlighted logistic regression (LR) and support vector machine (SVM) as the most accurate predictors, with minimal errors for clinical data. Conversely, decision trees (DT) exhibited higher error rates due to overfitting, emphasizing the importance of algorithm selection for complex datasets. Analysis of ultrasound images underscored the significance of preprocessing, while histopathological image analysis using convolutional neural networks (CNNs) demonstrated robust classification capabilities. These findings underscore the transformative potential of ML and DL in BC diagnosis, offering automated, accurate, and accessible diagnostic tools. Collaboration among stakeholders is crucial for further advancements in BC detection methods.

Early monitoring values of oncogenic signalling molecules for hepatocellular carcinoma.

The prevention and early diagnosis of liver cancer remains a global medical challenge. During the malignant transformation of hepatocytes, a variety of oncogenic cellular signalling molecules, such as novel high mobility group-Box 3, angiopoietin-2, Golgi protein 73, glypican-3, Wnt3a (a signalling molecule in the Wnt/ß-catenin pathway), and secretory clusterin, can be expressed and secreted into the blood. These signalling molecules are derived from different signalling pathways and may not only participate in the malignant transformation of hepatocytes but also become early diagnostic indicators of hepatocarcinogenesis or specific targeted molecules for hepatocellular carcinoma therapy. This article reviews recent progress in the study of several signalling molecules as sensitive biomarkers for monitoring hepatocarcinogenesis.

Early detection of pancreatic cancer in patients with recurrent pancreatitis: A case report.

BACKGROUND: Pancreatic cancer presents a challenge with its low early diagnosis and treatment rates, leading to high metastasis and mortality rates. The median survival time for advanced pancreatic cancer is a mere 3 months. However, there's hope: small pancreatic cancers diagnosed at an early stage (T1) or those less than or equal to 1 cm in diameter boast an impressive 5-year survival rate of nearly 100%. This underscores the critical importance of early pancreatic cancer detection for significantly improving prognosis. CASE SUMMARY: Pancreatic cancer, a malignant tumor of the digestive tract, poses challenges in both diagnosis and treatment due to its occult and atypical clinical symptoms. Clinically, patients with recurrent pancreatitis should be vigilant, as it may be indicative of pancreatic cancer, particularly in middle-aged and elderly patients. Here, we presented the case of a patient who experienced recurrent acute pancreatitis within a span of 2 months. During the initial episode of pancreatitis, routine imaging failed to identify the cause of pancreatic cancer. However, upon recurrence of acute pancreatitis, endoscopic ultrasonography (EUS) revealed a space-occupying lesion approximately 1 cm in size in the pancreatic body. Subsequent EUS coupled with fine-needle aspiration examination demonstrated atypical pancreatic gland epithelium. Ultimately, the patient underwent surgery and was diagnosed with an intraductal papillary mucinous tumor of the pancreas (severe epithelial dysplasia, focal cancer). CONCLUSION: We recommend EUS for patients with recurrent pancreatitis of unknown etiology to exclude early pancreatic cancer.

Application of neutrophil-lymphocyte ratio and red blood cell distribution width in diabetes mellitus complicated with heart failure.

BACKGROUND: Accumulating clinical evidence has shown that diabetes mellitus (DM) is a serious risk factor for cardiovascular disorders and an important factor for adverse cardiovascular events. AIM: To explore the value of the combined determination of the neutrophil-lymphocyte ratio (NLR) and red blood cell distribution width (RDW) in the early diagnosis and prognosis evaluation of DM complicated with heart failure (HF). METHODS: We retrospectively analyzed clinical data on 65 patients with type 2 DM (T2DM) complicated with HF (research group, Res) and 60 concurrent patients with uncomplicated T2DM (control group, Con) diagnosed at Zhejiang Provincial People's Hospital between January 2019 and December 2021. The NLR and RDW values were determined and comparatively analyzed, and their levels in T2DM + HF patients with different cardiac function grades were recorded. The receiver operating characteristic (ROC) curves were plotted to determine the NLR and RDW values (alone and in combination) for the early diagnosis of HF. The correlation between NLR and RDW with the presence or absence of cardiac events was also investigated. RESULTS: Higher NLR and RDW levels were identified in the Res vs the Con groups (P < 0.05). The NLR and RDW increased gradually and synchronously with the deterioration of cardiac function in the Res group, with marked differences in their levels among patients with grade II, III, and IV HF (P < 0.05). ROC curve analysis revealed that NLR combined with RDW detection had an area under the curve of 0.915, a sensitivity of 76.9%, and a specificity of 100% for the early diagnosis of HF. Furthermore, HF patients with cardiac events showed higher NLR and RDW values compared with HF patients without cardiac events. CONCLUSION: NLR and RDW were useful laboratory indicators for the early diagnosis of DM complicated with HF, and their joint detection was beneficial for improving diagnostic efficiency. Additionally, NLR and RDW values were directly proportional to patient outcomes.

Identification and Application of Emerging Biomarkers in Treatment of Non-Small-Cell Lung Cancer: Systematic Review.

Non-small-cell lung cancer (NSCLC) comprises approximately 85% of all lung cancer cases, often diagnosed at advanced stages, which diminishes the effective treatment options and survival rates. This systematic review assesses the utility of emerging biomarkers-circulating tumor DNA (ctDNA), microRNAs (miRNAs), and the blood tumor mutational burden (bTMB)-enhanced by next-generation sequencing (NGS) to improve the diagnostic accuracy, prognostic evaluation, and treatment strategies in NSCLC. Analyzing data from 37 studies involving 10,332 patients from 2020 to 2024, the review highlights how biomarkers like ctDNA and PD-L1 expression critically inform the selection of personalized therapies, particularly beneficial in the advanced stages of NSCLC. These biomarkers are critical for prognostic assessments and in dynamically adapting treatment plans, where high PD-L1 expression and specific genetic mutations (e.g., ALK fusions, EGFR mutations) significantly guide the use of targeted therapies and immunotherapies. The findings recommend integrating these biomarkers into standardized clinical pathways to maximize their potential in enhancing the treatment precision, ultimately fostering significant advancements in oncology and improving patient outcomes and quality of life. This review substantiates the prognostic and predictive value of these biomarkers and emphasizes the need for ongoing innovation in biomarker research.

Trends in primary care blood tests prior to lung and colorectal cancer diagnosis-A retrospective cohort study using linked Australian data.

INTRODUCTION: Abnormal results in common blood tests may occur several months before lung cancer (LC) and colorectal cancer (CRC) diagnosis. Identifying early blood markers of cancer and distinct blood test signatures could support earlier diagnosis in general practice. METHODS: Using linked Australian primary care and hospital cancer registry data, we conducted a cohort study of 855 LC and 399 CRC patients diagnosed between 2001 and 2021. Requests and results from general practice blood tests (six acute phase reactants [APR] and six red blood cell indices [RBCI]) were examined in the 2 years before cancer diagnosis. Poisson regression models were used to estimate monthly incidence rates and examine pre-diagnostic trends in blood test use and abnormal results prior to cancer diagnosis, comparing patterns in LC and CRC patients. RESULTS: General practice blood test requests increase from 7 months before CRC and 6 months before LC diagnosis. Abnormalities in many APR and RBCI tests increase several months before cancer diagnosis, often occur prior to or in the absence of anaemia (in 51% of CRC and 81% of LC patients with abnormalities), and are different in LC and CRC patients. CONCLUSIONS: This study demonstrates an increase in diagnostic activity in Australian general practice several months before LC and CRC diagnosis, indicating potential opportunities for earlier diagnosis. It identifies blood test abnormalities and distinct signatures that are early markers of LC and CRC. If combined with other pre-diagnostic information, these blood tests have potential to support GPs in prioritising patients for cancer investigation of different sites to expedite diagnosis.

Circulating tumor DNA mutation analysis: advances in its application for early diagnosis of hepatocellular carcinoma and therapeutic efficacy monitoring.

In recent years, the detection and analysis of circulating tumor DNA (ctDNA) have emerged as a new focus in the field of cancer research, particularly in the early diagnosis of hepatocellular carcinoma (HCC) and monitoring of therapeutic efficacy. ctDNA, which refers to cell-free DNA fragments released into the bloodstream from tumor cells upon cell death or shedding, carries tumor-specific genetic and epigenetic alterations, thereby providing a non-invasive approach for cancer diagnosis and prognosis. The concentration of ctDNA in the blood is higher compared to that in healthy individuals or other liquid biopsies from early-stage cancers, which is closely associated with the early diagnosis and comprehensive sequencing studies of HCC. Recent studies have indicated that sequential ctDNA analysis in patients receiving primary or adjuvant therapy for HCC can detect treatment resistance and recurrence before visible morphological changes in the tumor, making it a valuable basis for rapid adjustment of treatment strategies. However, this technology is continuously being optimized and improved. Challenges such as enhancing the accuracy of ctDNA sequencing tests, reducing the burden of high-throughput sequencing on a large number of samples, and controlling variables in the assessment of the relationship between ctDNA concentration and tumor burden, need to be addressed. Overall, despite the existing challenges, the examination and analysis of ctDNA have opened up new avenues for early diagnosis and therapeutic efficacy monitoring in hepatocellular carcinoma, expanding the horizons of this field.

Unveiling the untreated: development of a database algorithm to identify potential Fabry disease patients in Germany.

BACKGROUND: Fabry disease (FD), an X-linked lysosomal storage disorder, is caused by mutations in the gene encoding α-galactosidase A, resulting in lysosomal accumulation of globotriaosylceramide and other glycosphingolipids. Early detection of FD is challenging, accounting for delayed diagnosis and treatment initiation. This study aimed to develop an algorithm using a logistic regression model to facilitate early identification of patients based on ICD-10-GM coding using a German Sickness Fund Database. METHODS: The logistic regression model was fitted on a binary outcome variable based on either a treated FD cohort or a control cohort (without FD). Comorbidities specific to the involved organs were used as covariates to identify potential FD patients with ICD-10-GM E75.2 diagnosis but without any FD-specific medication. Specificity and sensitivity of the model were optimized to determine a likely threshold. The cut-point with the largest values for the Youden index and concordance probability method and the lowest value for closest to (0,1) was identified as 0.08 for each respective value. The sensitivity and specificity for this cut-point were 80.4% and 79.8%, respectively. Additionally, a sensitivity analysis of the potential FD patients with at least two codes of E75.2 diagnoses was performed. RESULTS: A total of 284 patients were identified in the potential FD cohort using the logistic regression model. Most potential FD patients were < 30 years old and female. The identification and incidence rates of FD in the potential FD cohort were markedly higher than those of the treated FD cohort. CONCLUSIONS: This model serves as a tool to identify potential FD patients using German insurance claims data.

Biomarkers of Parkinson's disease in perspective of early diagnosis and translation of neurotrophic therapies.

Parkinson's disease (PD) is a common neurodegenerative disorder characterized by progressive loss of dopamine neurons and aberrant deposits of alpha-synuclein (α-syn) in the brain. The symptomatic treatment is started after the onset of motor manifestations in a late stage of the disease. Preclinical studies with neurotrophic factors (NTFs) show promising results of disease-modifying neuroprotective or even neurorestorative effects. Four NTFs have entered phase I-II clinical trials with inconclusive outcomes. This is not surprising because the preclinical evidence is from acute early-stage disease models, but the clinical trials included advanced PD patients. To conclude the value of NTF therapies, clinical studies should be performed in early-stage patients with prodromal symptoms, that is, before motor manifestations. In this review, we summarize currently available diagnostic and prognostic biomarkers that could help identify at-risk patients benefiting from NTF therapies. Focus is on biochemical and imaging biomarkers, but also other modalities are discussed. Neuroimaging is the most important diagnostic tool today, but α-syn imaging is not yet viable. Modern techniques allow measuring various forms of α-syn in cerebrospinal fluid, blood, saliva, and skin. Digital biomarkers and artificial intelligence offer new means for early diagnosis and longitudinal follow-up of degenerative brain diseases.

Enhancing Early Detection of Necrotizing Soft Tissue Infections: The Role of the Laboratory Risk Indicator for Necrotizing Fasciitis (LRINEC) Score.

Background There is great variation in the etiology, predisposing organisms, incidence, clinical characteristics, severity, and consequences of skin and/or subcutaneous tissue infections. Extensive necrosis of the subcutaneous tissues and fascia is a characteristic of necrotizing soft tissue infections, which are frequently deadly. To change the course of treatment, this study highlights the need to find a tool that can quickly and accurately identify patients with necrotizing fasciitis (NF) and assist in making an early treatment decision. Methodology A prospective evaluation of 30 individuals with soft tissue infections was conducted using the laboratory risk indicator for necrotizing fasciitis (LRINEC). The patients were classified as low, intermediate, and high risk for the start of NF based on their LRINEC score. To assess the importance of the LRINEC score in forecasting the start of NF and its clinical consequences, patients in each group underwent appropriate management and statistical analysis. Results This study included 28 males (93.3%) and two females (6.7%). The associated p-value, recorded as 0.039, signifies statistical significance in the observed area under the receiver operating characteristic (ROC) curve. The p-value in risk categorization was found to be 0.296, which suggests that LRINEC helps in risk categorization with 100% sensitivity when used as a screening tool. Conclusion The early detection of necrotizing soft tissue infections, such as NF, is vital. The LRINEC score, based on routine lab tests, accurately distinguishes these infections. With high sensitivity and significant p-values, it helps stratify patients, guiding timely interventions and saving lives.

Spanish Translation and Cultural Adaptation of the Intensive Care Unit Delirium Playbook.

Background: A lack of high-quality provider education hinders the delivery of standard-of-care delirium detection and prevention practices in the intensive care unit (ICU). To fill this gap, we developed and validated an e-learning ICU Delirium Playbook consisting of eight videos and a 44-question knowledge assessment quiz. Given the increasing Spanish-speaking population worldwide, we translated and cross-culturally adapted the playbook from English into Spanish. Objective: To translate and culturally adapt the ICU Delirium Playbook into Spanish, the second most common native language worldwide. Methods: The translation and cross-cultural adaptation process included double forward and back translations and harmonization by a 14-person interdisciplinary team of ICU nurses and physicians, delirium experts, methodologists, medical interpreters, and bilingual professionals representing many Spanish-speaking global regions. After a preeducation quiz, a nurse focus group completed the playbook videos and posteducation quiz, followed by a semistructured interview. Results: The ICU Delirium Playbook: Spanish Version maintained conceptual equivalence to the English version. Focus group participants posted mean (standard deviation) pre- and post-playbook scores of 63% (10%) and 78% (12%), with a 15% (11%) pre-post improvement (P = 0.01). Participants reported improved perceived competency in performing the Confusion Assessment Method for the ICU and provided positive feedback regarding the playbook. Conclusion: After translation and cultural adaptation, the ICU Delirium Playbook: Spanish Version yielded significant knowledge assessment improvements and positive feedback. The Spanish playbook is now available for public dissemination.

Early detection of tuberculosis: a systematic review.

Tuberculosis remains a significant global health challenge. Tuberculosis affects millions of individuals worldwide. Early detection of tuberculosis plays a relevant role in the management of treatment of tuberculosis. This systematic review will analyze the findings of several published studies on the topic of the early detection of tuberculosis. This systematic review highlights their methodologies and limitations as well as their contributions to our understanding of this pressing issue. Early detection of tuberculosis can be achieved through tuberculosis screening for contacts. Comprehensive health education for household contacts can be used as early detection. The in-house deep learning models can be used in the X-ray used for automatic detection of tuberculosis. Interferon gamma release assay, routine passive and active case detection, portable X-ray and nucleic acid amplification testing, and highly sensitive enzyme-linked immunosorbent assay tests play critical roles in improving tuberculosis detection.

A near-infrared fluorescent probe for differentiating cancer cells from normal cells and early diagnosis of liver cirrhosis.

BACKGROUND: Cirrhosis represents the terminal stage of liver disease progression and timely intervention in a diseased liver can enhance the likelihood of recovery. Viscosity, a crucial parameter of the cellular microenvironment, is intricately linked to the advancement of cirrhosis. However, viscosity monitoring still faces significant challenges in achieving non-invasive and rapid early diagnosis of cirrhosis. Near-infrared (NIR) fluorescence imaging has the advantages of high sensitivity, non-destructive detection, and ignoring background fluorescence interference, plays an important role in diagnosing and treating various biological diseases. Hence, monitoring cellular viscosity changes with NIR fluorescence probe holds great significance in the early diagnosis of cirrhosis. RESULTS: In this study, the NIR fluorescence probe based on the intramolecular charge transfer (TICT) mechanism was developed for imaging applications in mouse model of liver cirrhosis. A molecular rotor-type viscosity-responsive probe was synthesized by linking dioxanthracene groups via carbon-carbon double bonds. The probe demonstrated remarkable sensitivity, high selectivity and photostability, with its responsiveness to viscosity largely unaffected by factors such as polarity, pH, and interfering ions. The probe could effectively detect various drug-induced changes in cellular viscosity, enabling the differentiation between normal cells and cancerous cells. Furthermore, the enhanced tissue penetration capabilities of probe facilitated its successful application in mouse model of liver cirrhosis, allowing for the assessment of liver disease severity based on fluorescence intensity and providing a powerful tool for early diagnosis of cirrhosis. SIGNIFICANCE: A NIR viscosity-sensitive fluorescent probe was specifically designed to effectively monitor alterations in cellular and organ viscosity, which could advance the understanding of the biological characteristics of cancer and provide theoretical support for the early diagnosis of cirrhosis. Overall, this probe held immense potential in monitoring viscosity-related conditions, expanding the range of biomedical tools available.

Recent progress in Surface-Enhanced Raman Spectroscopy detection of biomarkers in liquid biopsy for breast cancer.

Breast cancer is the most commonly diagnosed cancer in women globally and a leading cause of cancer-related mortality. However, current detection methods, such as X-rays, ultrasound, CT scans, MRI, and mammography, have their limitations. Recently, with the advancements in precision medicine and technologies like artificial intelligence, liquid biopsy, specifically utilizing Surface-Enhanced Raman Spectroscopy (SERS), has emerged as a promising approach to detect breast cancer. Liquid biopsy, as a minimally invasive technique, can provide a temporal reflection of breast cancer occurrence and progression, along with a spatial representation of overall tumor information. SERS has been extensively employed for biomarker detection, owing to its numerous advantages such as high sensitivity, minimal sample requirements, strong multi-detection ability, and controllable background interference. This paper presents a comprehensive review of the latest research on the application of SERS in the detection of breast cancer biomarkers, including exosomes, circulating tumor cells (CTCs), miRNA, proteins and others. The aim of this review is to provide valuable insights into the potential of SERS technology for early breast cancer diagnosis.

Assessment of body Schema distortions in early-onset schizophrenia.

Distorted body representations play a major role in the onset and maintenance of Schizophrenia. However, these distortions are difficult to assess because explicit assessments can provoke intense fears about the body and require a good insight. We proposed an implicit motor imagery task to a 14-year-old girl with Early-Onset Schizophrenia. The test consisted of presenting different openings varying in width. For each aperture, the young girl has to say if she could pass through without turning her shoulders. A critical aperture is determined as the first aperture for which she considered she could no longer pass, compared to her shoulders' width. The girl perceived herself as 51 % wider than she was, indicating a significant oversized body schema. The implicit assessments of body schema generate less anxiety and does not require a great level of insight; moreover, those are promising tools for early detection of disease in prodromal phases of Schizophrenia and assistance with differential diagnosis.

Clinical Management of Primary Aldosteronism: An Update.

Despite carrying an excess risk of cardiovascular events, primary aldosteronism (PA) is a commonly overlooked secondary form of arterial hypertension. An increased awareness of its high prevalence and broader screening strategies are urgently needed to improve its detection rate and allow early diagnosis and targeted treatment. For patients with unilateral PA, these measures can correct hyperaldosteronism and ensure cure of hypertension, even when resistant to drug treatment, thus preventing adverse cardiovascular events. Among these, atrial fibrillation is the most common, but left ventricular hypertrophy, stroke, chronic kidney disease, and myocardial infarction also occur more often than in patients with hypertension and no PA. Young patients, who have higher chances of being cured long term, and high-risk patients, such as those with stage III or resistant hypertension, are those who will benefit most from an early diagnosis of PA. Therefore, the implementation of strategies to detect PA by a simplified diagnostic algorithm is necessary. In the patients who seek for surgical cure, adrenal vein sampling is key for the identification of unilateral PA and the achievement of optimal outcomes. Unfortunately, being technically demanding and poorly available, adrenal vein sampling represents the bottleneck in the workup of PA. Considering the novel knowledge generated in the past 5 years in many studies, particularly in the AVIS-2 study (Atherothrombosis Intervention in High-Risk Patients Using Serelaxin), based on 4 decades of experience at our center and on the last guidelines, we herein provide an update on the management of PA with recommendations for drug treatment and strategies to avoid adrenal vein sampling wherever it is poorly, or not, available.

Refining the targeted population and achieving better for colorectal cancer screening.

This editorial comments on the article entitled "Stage at diagnosis of colorectal cancer through diagnostic route: Who should be screened?" by Agatsuma et al, who conducted a retrospective study aiming at clarifying the stage at colorectal cancer (CRC) diagnosis based on different diagnostic routes. We share our opinion about CRC screening programs. The current situation suggests the need for a more specific and targeted population for CRC screening.

Diagnostic Value of Superb Microvascular Imaging of the Rotator Cuff Interval for the Early Diagnosis of Frozen Shoulder.

Purpose: To explore the early diagnostic value of superb microvascular imaging (SMI) features within the rotator cuff gap for frozen shoulder. Patients and Methods: This prospective study enrolled patients with acute early-stage frozen shoulder seeking treatment at Zhabei Central Hospital in Jing'an District, Shanghai, between July 2021 and December 2022 were enrolled in this study. Healthy controls were collected in a 1:1 ratio from the same hospital's physical examination center. All participants underwent SMI and power Doppler ultrasound (PDUS) of the rotator cuff gap. Results: The study included 79 patients with frozen shoulder and 77 healthy controls. Compared with the healthy control group, the patient group had a higher proportion of hypoechoic rotator cuff gap (81.0% vs 48.1%, P<0.001), a thicker coracohumeral ligament (2.60±1.01 vs 2.03±0.97, P<0.001), a thicker glenohumeral joint capsule (3.10±0.99 vs 2.46±1.17, P<0.001), and elevated blood grading using SMI (P<0.001) and PDUS (P=0.014). The highest area under the curve (AUC) was observed for SMI blood flow grading (AUC=0.824, 95% CI: 0.755-0.880, P<0.001), resulting in 82% sensitivity and 77% specificity when using a cutoff of 1. SMI blood flow grading was associated with external rotation <30° (P=0.007) and abduction <30° (P=0.013) but not with internal rotation <30° (P=0.630) or flexion <30° (P=0.562). Conclusion: The grading of SMI blood flow may emerge as a valuable predictive indicator for the early stages of frozen shoulder. This simple ultrasound technique holds the potential to enhance the diagnostic process, enabling early initiation of treatment and potentially improving patient outcomes.