Diagnostics最新文献

{"title":"Spectralis Optical Coherence Tomography for Evaluating Ocular Hypertensive and Glaucoma Suspect Eyes: Real-World Data from Taiwan.","authors":"Man-Sze Wong, Chao-Wei Wu, Yue-Cune Chang, Hsin-Yi Chen","doi":"10.3390/diagnostics15101256","DOIUrl":"10.3390/diagnostics15101256","url":null,"abstract":"<p><p><b>Objectives</b>: The aim of this research was to evaluate the diagnostic performance of Spectralis optical coherence tomography (OCT) parameters for ocular hypertensive (OH) and glaucoma suspect (GS) eyes in an Asian population from Taiwan. <b>Methods</b>: This retrospective cross-sectional study included 258 OH (mean deviation [MD]: -1.10 ± 1.75 dB), 380 GS (MD: -1.24 ± 2.63 dB), and 742 normal (MD: -1.47 ± 3.29 dB) eyes. The diagnostic performance of Spectralis OCT parameters, including optic nerve head (ONH) and macular parameters, was compared among groups. The area under the receiver operating characteristic curve (AUC) of each parameter signified its power to differentiate between normal and OH or GS eyes. <b>Results</b>: In various scanning protocols, circumpapillary retinal nerve fiber layer (NFL)-temporal (AUC = 0.538), macular NFL-outer temporal (AUC = 0.611), and retinal average thickness (RAT)_1.8 (AUC = 0.578) were the best parameters in distinguishing OH eyes from normal eyes. Moreover, minimum rim width (MRW)-mean global (AUC = 0.737), macular NFL-outer temporal (AUC = 0.558), and RAT_2.8 (AUC = 0.543) were the best parameters in distinguishing GS eyes from normal eyes. After adjusting for age and refraction effects, we determined that the AUCs for OH and GS were 0.694 and 0.646, respectively. <b>Conclusions</b>: Our real-world data indicate that Spectralis OCT parameters show some potential for early glaucoma detection and monitoring, but their current diagnostic effectiveness remains limited. When managing OH eyes, caution is required in evaluating macular retinal NFL thickness in addition to the ONH. Bruch's membrane opening-MRW is a potential objective indicator of ONH changes in GS eyes.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110584/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157316","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Three Neglected STARD Criteria Reduce the Uncertainty of the Liver Fibrosis Biomarker FibroTest-T2D in Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD).","authors":"Thierry Poynard, Olivier Deckmyn, Raluca Pais, Judith Aron-Wisnewsky, Valentina Peta, Pierre Bedossa, Frederic Charlotte, Maharajah Ponnaiah, Jean-Michel Siksik, Laurent Genser, Karine Clement, Gilles Leanour, Dominique Valla","doi":"10.3390/diagnostics15101253","DOIUrl":"10.3390/diagnostics15101253","url":null,"abstract":"<p><p><b>Background/Objectives:</b> Bariatric surgery (BS), drugs approved for type-2-diabetes (T2D), obesity, and liver fibrosis (resmetirom) announce the widespread use of fibrosis tests in patients with metabolic liver disease (MASLD). An unmet need is to reduce the uncertainty of biomarkers for the diagnosis of the early stage of clinically significant fibrosis (eF). This can be achieved if three essential but neglected STARD methods (3M) are used, which have a more sensitive histological score than the standard comparator (five-tiers), the weighted area under the characteristic curve (wAUROC) instead of the binary AUROC, and biopsy length. We applied 3M to FibroTest-T2D to demonstrate this reduction of uncertainty and constructed proxies predicting eF in large populations. <b>Methods:</b> For uncertainty, seven subsets were analyzed, four included biopsies (<i>n</i> = 1903), and to assess eF incidence, three MASLD-populations (<i>n</i> = 299,098). FibroTest-T2D classification rates after BS and in outpatients-T2D (<i>n</i> = 402) were compared with and without 3M. In MASLD, trajectories of proxies and incidence against confounding factors used hazard ratios. <b>Results:</b> After BS (110 biopsies), reversal of eF was observed in 16/29 patients (84%) using seven-tier scores vs. 3/20 patients (47%) using five-tier scores (<i>p</i> = 0.005). When the biopsy length was above the median, FibroTest-T2D wAUROC was 0.90 (SD = 0.01), and the wAUROC was 0.88 (SD = 0.1) when the length was below the median (<i>p</i> < 0.001). For the first time, obesity was associated with eF before T2D (<i>p</i> < 0.001), and perimenopausal age with apoA1 and haptoglobin increases (<i>p</i> < 0.0001). <b>Conclusions:</b> Validations of circulating biomarkers need to assess their uncertainty. FibroTest-T2D predicts fibrosis regression after BS. Applying 3M and adjustments could avoid misinterpretations in MASLD surveillance.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110081/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Object Detection in Laparoscopic Surgery: A Comparative Study of Deep Learning Models on a Custom Endometriosis Dataset.","authors":"Andrey Bondarenko, Vilen Jumutc, Antoine Netter, Fanny Duchateau, Henrique Mendonca Abrão, Saman Noorzadeh, Giuseppe Giacomello, Filippo Ferrari, Nicolas Bourdel, Ulrik Bak Kirk, Dmitrijs Bļizņuks","doi":"10.3390/diagnostics15101254","DOIUrl":"10.3390/diagnostics15101254","url":null,"abstract":"<p><p><b>Background:</b> Laparoscopic surgery for endometriosis presents unique challenges due to the complexity of and variability in lesion appearances within the abdominal cavity. This study investigates the application of deep learning models for object detection in laparoscopic videos, aiming to assist surgeons in accurately identifying and localizing endometriosis lesions and related anatomical structures. A custom dataset was curated, comprising of 199 video sequences and 205,725 frames. Of these, 17,560 frames were meticulously annotated by medical professionals. The dataset includes object detection annotations for 10 object classes relevant to endometriosis, alongside segmentation masks for some classes. <b>Methods:</b> To address the object detection task, we evaluated the performance of two deep learning models-FasterRCNN and YOLOv9-under both stratified and non-stratified training scenarios. <b>Results:</b> The experimental results demonstrated that stratified training significantly reduced the risk of data leakage and improved model generalization. The best-performing FasterRCNN object detection model achieved a high average test precision of 0.9811 ± 0.0084, recall of 0.7083 ± 0.0807, and mAP50 (mean average precision at 50% overlap) of 0.8185 ± 0.0562 across all presented classes. Despite these successes, the study also highlights the challenges posed by the weak annotations and class imbalances in the dataset, which impacted overall model performances. <b>Conclusions:</b> In conclusion, this study provides valuable insights into the application of deep learning for enhancing laparoscopic surgical precision in endometriosis treatment. The findings underscore the importance of robust dataset curation and advanced training strategies in developing reliable AI-assisted tools for surgical interventions. The latter could potentially improve the guidance of surgical interventions and prevent blind spots occurring in difficult to reach abdominal regions. Future work will focus on refining the dataset and exploring more sophisticated model architectures to further improve detection accuracy.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110204/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144156691","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diagnostic Performance of Magnetic Resonance Sequences in Staging Lymph Node Involvement and Extranodal Extension in Head and Neck Squamous Cell Carcinoma.","authors":"Giovanni Lorusso, Nicola Maggialetti, Francesca Laugello, Annalisa Garofalo, Ilaria Villanova, Sara Greco, Chiara Morelli, Pasquale Pignataro, Nicola Maria Lucarelli, Amato Antonio Stabile Ianora","doi":"10.3390/diagnostics15101251","DOIUrl":"10.3390/diagnostics15101251","url":null,"abstract":"<p><p><b>Objectives:</b> This study aimed to evaluate the diagnostic performance of various MRI sequences in detecting nodal metastasis (N+) and extranodal extension (ENE+) in patients with head and neck squamous cell carcinoma (HNSCC). <b>Methods</b>: A retrospective analysis was conducted on 42 patients with HNSCC who underwent preoperative MRI and subsequent surgical lymph node dissection between June 2021 and December 2023. Lymph node MRI features were evaluated on five different MRI sequences. For each rN+ case, the presence of radiological extranodal extension (rENE+) was assessed independently in every MRI sequence by analyzing three characteristics. ENE was deemed positive if at least one of three criteria considered was present. <b>Results</b>: All of the MRI sequences demonstrated slightly high accuracy (~76%) for detecting N+, with T1WI, STIR, and CE THRIVE showing comparable sensitivities (60-65%). The STIR sequence exhibited the highest sensitivity (75%) and nearly the highest accuracy (91%) for detecting ENE+. Capsular irregularity and necrosis showed high specificity across sequences, while the loss of fatty hilum and nodal size had lower performance. <b>Conclusions</b>: Tailoring MRI protocols to leverage the strengths of specific sequences can significantly improve the diagnostic accuracy, aiding in better patient management and treatment outcomes.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110374/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Investigating the Role of Intravoxel Incoherent Motion Diffusion-Weighted Imaging in Evaluating Multiple Sclerosis Lesions.","authors":"Othman I Alomair, Sami A Alghamdi, Abdullah H Abujamea, Ahmed Y AlfIfi, Yazeed I Alashban, Nyoman D Kurniawan","doi":"10.3390/diagnostics15101260","DOIUrl":"10.3390/diagnostics15101260","url":null,"abstract":"<p><p><b>Background</b>: Multiple sclerosis (MS) is a chronic and heterogeneous disease characterized by demyelination and axonal loss and damage. Magnetic resonance imaging (MRI) has been employed to distinguish these changes in various types of MS lesions. <b>Objectives:</b> We aimed to evaluate intravoxel incoherent motion (IVIM) diffusion and perfusion MRI metrics across different brain regions in healthy individuals and various types of MS lesions, including enhanced, non-enhanced, and black hole lesions. <b>Methods:</b> A prospective study included 237 patients with MS (65 males and 172 females) and 29 healthy control participants (25 males and 4 females). The field strength was 1.5 Tesla. The imaging sequences included three-dimensional (3D) T₁, 3D fluid-attenuated inversion recovery, two-dimensional (2D) T₁, T₂-weighted imaging, and 2D diffusion-weighted imaging (DWI) sequences. IVIM-derived parameters-apparent diffusion coefficient (ADC), pure molecular diffusion (<i>D</i>), pseudo-diffusion (<i>D</i>*), and perfusion fraction (<i>f</i>)-were quantified for commonly observed lesion types (2506 lesions from 224 patients with MS, excluding 13 patients due to MRI artifacts or not meeting the diagnostic criteria for RR-MS) and for corresponding brain regions in 29 healthy control participants. A one-way analysis of variance, followed by post-hoc analysis (Tukey's test), was performed to compare mean values between the healthy and MS groups. Receiver operating characteristic curve analyses, including area under the curve, sensitivity, and specificity, were conducted to determine the cutoff values of IVIM parameters for distinguishing between the groups. A <i>p</i>-value of ≤0.05 and 95% confidence intervals were used to report statistical significance and precision, respectively. <b>Results:</b> All IVIM parametric maps in this study discriminated among most MS lesion types. ADC, <i>D</i>, and <i>D</i>* values for MS black hole lesions were significantly higher (<i>p</i> < 0.0001) than those for other MS lesions and healthy controls. ADC, <i>D</i>, and <i>D</i>* maps demonstrated high sensitivity and specificity, whereas <i>f</i> maps exhibited low sensitivity but high specificity. <b>Conclusions:</b> IVIM parameters provide valuable diagnostic and clinical insights by demonstrating high sensitivity and specificity in evaluating different categories of MS lesions.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110058/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157382","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Management of Postoperative Pancreatic Fluid Collection and Role of Endoscopy: A Case Series and Review of the Literature.","authors":"Chiara Coluccio, Ilaria Tarantino, Maria Chiara Petrone, Edoardo Forti, Stefano Francesco Crinò, Alessandro Fugazza, Roberto Di Mitri, Cecilia Binda, Davide Trama, Arnaldo Amato, Alessandro Redaelli, Germana De Nucci, Fabia Attili, Mario Luciano Brancaccio, Claudio Giovanni De Angelis, Mauro Lovera, Antonio Facciorusso, Andrea Anderloni, Carlo Fabbri","doi":"10.3390/diagnostics15101258","DOIUrl":"10.3390/diagnostics15101258","url":null,"abstract":"<p><p><b>Background:</b> Postoperative fluid collections (POFCs) after abdominal surgeries, particularly pancreatic surgeries, are associated with high morbidity and mortality rates and were historically managed with surgical re-exploration and drainage. In particular, postoperative pancreatic fluid collections (PPFCs) are the most common complications after pancreatic surgery resulting from pancreatic leaks. They occur in up to 50% of cases, and approximately 10% of them need to be drained to avoid further sequelae. Endoscopic ultrasonography (EUS)-guided drainage of PPFCs represents the first-line treatment nowadays, but many aspects are still debated. <b>Methods:</b> We describe a retrospective case series of patients from multiple Italian centers who underwent EUS-guided drainage (EUS-D) of POFCs, aiming to provide data on the efficacy and safety of this procedure, supported by a review of the existing literature on this topic. The primary outcomes were technical and clinical success, and the secondary outcomes were the type and rate of adverse events (AEs) and the rate of recurrence. <b>Results:</b> A total of 47 patients were included. The procedure demonstrated a technical success rate of 98% (46/47) and a clinical success rate of 96% (45/47). The rate of AEs was 11% (5/47), represented by bleeding (3/5), stent occlusion (1/5), and buried syndrome (1/5). <b>Conclusions:</b> Management of POFCs has shifted over time towards an endoscopic approach with optimal efficacy and safety.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109864/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157315","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deep Reinforcement Learning for CT-Based Non-Invasive Prediction of SOX9 Expression in Hepatocellular Carcinoma.","authors":"Minghui Liu, Yi Wei, Tianshu Xie, Meiyi Yang, Xuan Cheng, Lifeng Xu, Qian Li, Feng Che, Qing Xu, Bin Song, Ming Liu","doi":"10.3390/diagnostics15101255","DOIUrl":"10.3390/diagnostics15101255","url":null,"abstract":"<p><p><b>Background:</b> The transcription factor SOX9 plays a critical role in various diseases, including hepatocellular carcinoma (HCC), and has been implicated in resistance to sorafenib treatment. Accurate assessment of SOX9 expression is important for guiding personalized therapy in HCC patients; however, a reliable non-invasive method for evaluating SOX9 status remains lacking. This study aims to develop a deep learning (DL) model capable of preoperatively and non-invasively predicting SOX9 expression from CT images in HCC patients. <b>Methods:</b> We retrospectively analyzed a dataset comprising 4011 CT images from 101 HCC patients who underwent surgical resection followed by sorafenib therapy at West China Hospital, Sichuan University. A deep reinforcement learning (DRL) approach was proposed to enhance prediction accuracy by identifying and focusing on image regions highly correlated with SOX9 expression, thereby reducing the impact of background noise. <b>Results:</b> Our DRL-based model achieved an area under the curve (AUC) of 91.00% (95% confidence interval: 88.64-93.15%), outperforming conventional DL methods by over 10%. Furthermore, survival analysis revealed that patients with SOX9-positive tumors had significantly shorter recurrence-free survival (RFS) and overall survival (OS) compared to SOX9-negative patients, highlighting the prognostic value of SOX9 status. <b>Conclusions:</b> This study demonstrates that a DRL-enhanced DL model can accurately and non-invasively predict SOX9 expression in HCC patients using preoperative CT images. These findings support the clinical utility of imaging-based SOX9 assessment in informing treatment strategies and prognostic evaluation for patients with advanced HCC.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110404/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144157255","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Early Detection of Fetal Health Conditions Using Machine Learning for Classifying Imbalanced Cardiotocographic Data.","authors":"Irem Nazli, Ertugrul Korbeko, Seyma Dogru, Emin Kugu, Ozgur Koray Sahingoz","doi":"10.3390/diagnostics15101250","DOIUrl":"10.3390/diagnostics15101250","url":null,"abstract":"<p><p><b>Background:</b> Cardiotocography (CTG) is widely used in obstetrics to monitor fetal heart rate and uterine contractions. It helps detect early signs of fetal distress. However, manual interpretation of CTG can be time-consuming and may vary between clinicians. Recent advances in machine learning provide more efficient and consistent alternatives for analyzing CTG data. <b>Objectives:</b> This study aims to investigate the classification of fetal health using various machine learning models to facilitate early detection of fetal health conditions. <b>Methods:</b> This study utilized a tabular dataset comprising 2126 patient records and 21 features. To classify fetal health outcomes, various machine learning algorithms were employed, including CatBoost, Decision Tree, ExtraTrees, Gradient Boosting, KNN, LightGBM, Random Forest, SVM, ANN and DNN. To address class imbalance and enhance model performance, the Synthetic Minority Oversampling Technique (SMOTE) was employed. <b>Results:</b> Among the tested models, the LightGBM algorithm achieved the highest performance, boasting a classification accuracy of 90.73% and, more notably, a balanced accuracy of 91.34%. This superior balanced accuracy highlights LightGBM's effectiveness in handling imbalanced datasets, outperforming other models in ensuring fair classification across all classes. <b>Conclusions:</b> This study highlights the potential of machine learning models as reliable tools for fetal health classification. The findings emphasize the transformative impact of such technologies on medical diagnostics. Additionally, the use of SMOTE effectively addressed dataset imbalance, further enhancing the reliability and applicability of the proposed approach.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110323/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144156004","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Lesion Length on Doppler Velocities Used Routinely to Determine Carotid Stenosis Cross-Sectional Severity.","authors":"Wladyslaw Dabrowski, Lukasz Tekieli, Anna Kablak-Ziembicka, Justyna Stefaniak, Karolina Dzierwa, Adam Mazurek, Piotr Paluszek, Krzysztof Zmudka, Piotr Pieniazek, Piotr Musialek","doi":"10.3390/diagnostics15101259","DOIUrl":"10.3390/diagnostics15101259","url":null,"abstract":"<p><p><b>Background/Objective</b>: Transcutaneous Doppler ultrasound is a fundamental tool in evaluating carotid stenosis cross-sectional severity (CS-CSS) in clinical practice because peak-systolic and end-diastolic velocities (PSV, EDV) increase with angiographic diameter stenosis. We tested the hypothesis that lesion length (LL) may affect PSV and EDV. <b>Methods</b>: CARUS (Carotid Artery IntravasculaR Ultrasound Study) prospectively enrolled 300 consecutive patients (age 47-83 years, 64.3% men, 63.3% symptomatic) with carotid stenosis ≥50% by Doppler ultrasound considered diagnostic (corelab analyst). We correlated stenosis LL (mm) and minimal lumen area (MLA, mm²) with PSV and EDV. <b>Results</b>: IVUS imaging (20 MHz Volcano/Philips) was uncomplicated. As IVUS probe forward/backward movement with systole/diastole (\"jumping\"-related artifact superimposed on motorized pullback) restrained LL (but not MLA) determination, LL measurement was angiographic. Final data set included 293 patients/stenoses (applicable to seven angiograms unsuitable for LL measurement). Irrespective of CS-CSS, a significant LL effect on PSV and EDV occurred with LL ≥ 7 mm (n = 224/293, i.e., 76.5% study patients/lesions; r = 0.38 and r = 0.35); for MLA irrespective of CS-CCS the coefficients were r = 0.49 (PSV) and r = 0.42 (EDV); <i>p</i> < 0.001 for all. For LL and MLA considered together, the correlations were stronger: r = 0.61 (PSV) and r = 0.54 (EDV); <i>p</i> < 0.0001 for both. Combined LL and MLA effect was represented by the following formulas: PSV = 0.31 × LL/MLA + 2.02 [m/s]; EDV = 0.12 × LL/MLA + 0.63 [m/s], enabling to correct the PSV (EDV)-based assessment of CS-CSS for the LL effect. <b>Conclusions</b>: This study provides, for the first time, systematic evidence that the length of carotid stenosis significantly affects lesional Doppler velocities. We established formulas incorporating the contribution of both stenosis length and its cross-sectional severity to PSV and EDV. We advocate including stenosis length measurement in duplex ultrasound reports when performing PSV (EDV)-based assessment of carotid cross-sectional stenosis severity.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12110091/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144156693","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Association of Placental Grading with Perinatal Outcomes: A Systematic Review and Meta-Analysis.","authors":"Antonios Siargkas, Christina Pachi, Meletios P Nigdelis, Sofoklis Stavros, Ekaterini Domali, Apostolos Mamopoulos, Ioannis Tsakiridis, Themistoklis Dagklis","doi":"10.3390/diagnostics15101264","DOIUrl":"10.3390/diagnostics15101264","url":null,"abstract":"<p><p><b>Objective</b>: Premature placental calcification (PPC) has been implicated in adverse perinatal outcomes, yet its clinical significance remains controversial. This meta-analysis aimed to quantitatively synthesize current data on the association between PPC, defined as grade 3 placental calcification before 36⁺⁶ weeks of gestation and adverse perinatal outcomes. Data Sources: A systematic search was conducted in MEDLINE, Scopus and The Cochrane Library from inception until 11 March 2025, to identify eligible studies. Study Eligibility Criteria: Observational studies including singleton pregnancies with PPC diagnosed via ultrasonography between 28⁺⁰ and 36⁺⁶ weeks of gestation and comparing them with pregnancies with Grannum grade 0, 1, or 2 placentas were considered eligible. <b>Methods</b>: Study quality was assessed using the Newcastle-Ottawa Scale, and the risk of bias was evaluated with the Quality In Prognosis Studies tool. The primary outcomes were small-for-gestational-age (SGA) neonates and preeclampsia. Heterogeneity was assessed using Cochran's Q test and the I² statistic. Meta-analyses were conducted using a random-effects model, with outcomes reported as relative risk (RR) or mean difference (MD) with 95% confidence intervals (CIs). <b>Results</b>: In total, nine cohort studies were included. PPC was associated with an increased risk of SGA (RR, 1.99; 95% CI, 1.46-2.70), preeclampsia (RR, 5.27; 95% CI, 2.24-12.40), fetal growth restriction (RR, 2.31; 95% CI, 1.30-4.09), preterm delivery (RR, 2.11; 95% CI, 1.00-4.45), suspected fetal hypoxia (RR, 1.71; 95% CI, 1.13-2.56), low 5 min Apgar score (RR, 2.28; 95% CI, 1.50-3.44) and neonatal intensive care unit admission (RR, 1.80; 95% CI, 1.02-3.18). No significant associations were found with fetal or neonatal death (RR, 2.75; 95% CI, 0.87-8.71), cesarean delivery (RR, 1.26; 95% CI, 0.90-1.78), gestational diabetes mellitus (RR, 1.17; 95% CI, 0.81-1.70), neonatal resuscitation (RR, 1.04; 95% CI, 0.92-1.16), birthweight (MD, -187.46 g; 95% CI, -413.14 to +38.21), or gestational age at birth (MD, -0.62 weeks; 95% CI, -1.36 to +0.11). A sensitivity analysis excluding high-risk-of-bias studies yielded consistent results. <b>Conclusions</b>: PPC is associated with several adverse perinatal outcomes, including SGA and preeclampsia. While the clinical significance of placental grading has remained limited in recent years, this study has shown that PPC may serve as an early indicator of placental insufficiency, warranting enhanced fetal surveillance and risk assessment in affected pregnancies. Further research is needed to refine its prognostic utility and integration into obstetric practice.</p>","PeriodicalId":11225,"journal":{"name":"Diagnostics","volume":"15 10","pages":""},"PeriodicalIF":3.0,"publicationDate":"2025-05-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12109751/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144155832","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}