Journal Description
Diagnostics
Diagnostics
is an international, peer-reviewed, open access journal on medical diagnosis published semimonthly online by MDPI. The British Neuro-Oncology Society (BNOS), the International Society for Infectious Diseases in Obstetrics and Gynaecology (ISIDOG) and the Swiss Union of Laboratory Medicine (SULM) are affiliated with Diagnostics and their members receive a discount on the article processing charges.
- Open Access— free for readers, with article processing charges (APC) paid by authors or their institutions.
- High Visibility: indexed within Scopus, SCIE (Web of Science), PubMed, PMC, Embase, Inspec, CAPlus / SciFinder, and other databases.
- Journal Rank: JCR - Q2 (Medicine, General & Internal)
- Rapid Publication: manuscripts are peer-reviewed and a first decision is provided to authors approximately 20.7 days after submission; acceptance to publication is undertaken in 2.8 days (median values for papers published in this journal in the second half of 2023).
- Recognition of Reviewers: reviewers who provide timely, thorough peer-review reports receive vouchers entitling them to a discount on the APC of their next publication in any MDPI journal, in appreciation of the work done.
- Companion journal: LabMed.
Impact Factor:
3.6 (2022);
5-Year Impact Factor:
3.7 (2022)
Latest Articles
Incidence of Carotid Blowout Syndrome in Patients with Head and Neck Cancer after Radiation Therapy: A Cohort Study
Diagnostics 2024, 14(12), 1222; https://doi.org/10.3390/diagnostics14121222 (registering DOI) - 9 Jun 2024
Abstract
Carotid blowout syndrome (CBS) is a rare yet life-threatening complication that occurs after radiation therapy (RT). This study aimed to determine the incidence of CBS in patients with head and neck cancer (HNC) undergoing contemporary RT and to explore potential discrepancies in the
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Carotid blowout syndrome (CBS) is a rare yet life-threatening complication that occurs after radiation therapy (RT). This study aimed to determine the incidence of CBS in patients with head and neck cancer (HNC) undergoing contemporary RT and to explore potential discrepancies in the risk of CBS between nasopharyngeal cancer (NPC) and non-NPC patients. A total of 1084 patients with HNC who underwent RT between 2013 and 2023 were included in the study. All patients were under regular follow-ups at the radio-oncology department, and underwent annual contrast-enhanced computed tomography and/or magnetic resonance imaging for cancer recurrence surveillance. Experienced neuroradiologists and vascular neurologists reviewed the recruited patients’ images. Patients were further referred to the neurology department for radiation vasculopathy evaluation. The primary outcome of this study was CBS. Patients were categorized into NPC and non-NPC groups and survival analysis was employed to compare the CBS risk between the two groups. A review of the literature on CBS incidence was also conducted. Among the enrolled patients, the incidence of CBS in the HNC, NPC, and non-NPC groups was 0.8%, 0.9%, and 0.7%, respectively. Kaplan–Meier analysis revealed no significant difference between the NPC and non-NPC groups (p = 0.34). Combining the findings for our cohort with those of previous studies revealed that the cumulative incidence of CBS in patients with HNC is 5% (95% CI = 3–7%) after both surgery and RT, 4% (95% CI = 2–6%) after surgery alone, and 5% (95% CI = 3–7%) after RT alone. Our findings indicate a low incidence of CBS in patients with HNC undergoing contemporary RT. Patients with NPC may have a CBS risk close to that of non-NPC patients. However, the low incidence of CBS could be a potentially cause of selection bias and underestimation bias.
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(This article belongs to the Special Issue Clinical Diagnosis of Otorhinolaryngology)
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Macular OCT’s Proficiency in Identifying Retrochiasmal Visual Pathway Lesions in Multiple Sclerosis—A Pilot Study
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Larisa Cujbă, Ana Banc, Cristina Stan, Tudor Drugan and Cristina Nicula
Diagnostics 2024, 14(12), 1221; https://doi.org/10.3390/diagnostics14121221 (registering DOI) - 9 Jun 2024
Abstract
Optical coherence tomography (OCT) is a non-invasive imaging technique based on the principle of low-coherence interferometry that captures detailed images of ocular structures. Multiple sclerosis (MS) is a neurodegenerative disease that can lead to damage of the optic nerve and retina, which can
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Optical coherence tomography (OCT) is a non-invasive imaging technique based on the principle of low-coherence interferometry that captures detailed images of ocular structures. Multiple sclerosis (MS) is a neurodegenerative disease that can lead to damage of the optic nerve and retina, which can be depicted by OCT. The purpose of this pilot study is to determine whether macular OCT can be used as a biomarker in the detection of retrochiasmal lesions of the visual pathway in MS patients. We conducted a prospective study in which we included 52 MS patients and 27 healthy controls. All participants underwent brain MRI, visual field testing, and OCT evaluation of the thicknesses of the peripapillary retinal nerve fiber layer (pRNFL), macular ganglion cell layer (GCL), and macular inner plexiform layer (IPL). OCT measurements were adjusted for optic neuritis (ON). VF demonstrated poor capability to depict a retrochiasmal lesion identified by brain MRI (PPV 0.50). In conclusion, the OCT analysis of the macula appears to excel in identifying retrochiasmal MS lesions compared to VF changes. The alterations in the GCL and IPL demonstrate the most accurate detection of retrochiasmal visual pathway changes in MS patients.
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(This article belongs to the Special Issue Advanced Role of Optical Coherence Tomography in Clinical Medicine)
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Establishing Quality Assurance for HIV-1 Rapid Test for Recent Infection in Thailand through the Utilization of Dried Tube Specimens
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Supaporn Suparak, Petai Unpol, Kanokwan Ngueanchanthong, Sirilada Pimpa Chisholm, Siriphailin Jomjunyoung, Wipawee Thanyacharern, Nitis Smanthong, Pojaporn Pinrod, Kriengkrai Srithanaviboonchai, Thitipong Yingyong, Theerawit Tasaneeyapan, Somboon Nookhai, Archawin Rojanawiwat and Sanny Northbrook
Diagnostics 2024, 14(12), 1220; https://doi.org/10.3390/diagnostics14121220 (registering DOI) - 9 Jun 2024
Abstract
The present study focuses on establishing the quality assurance of laboratories for recent infections (RTRI) in Thailand. We developed a cold-chain independent method, using fully characterized plasma obtained from the Thai Red Cross Society, and prepared as dried tube specimens (DTS). Twenty microliters
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The present study focuses on establishing the quality assurance of laboratories for recent infections (RTRI) in Thailand. We developed a cold-chain independent method, using fully characterized plasma obtained from the Thai Red Cross Society, and prepared as dried tube specimens (DTS). Twenty microliters of HIV-seronegative, recent, and long-term infected samples were aliquoted into individual tubes and dried at room temperature, 20–30 degrees Celsius, in a biosafety cabinet overnight to ensure optimal preservation. The DTS external quality control and external quality assessment were tested for homogeneity and stability following the ISO/Guide 35 guidelines. The DTS panels were distributed to 48 sites (FY 2022) and 27 sites (FY 2023) across 14 and 9 provinces, respectively, in Thailand. The results from participating laboratories were collected and evaluated for performance. The results were scored, and acceptable performance criteria were defined as the proportion of panels correctly tested, which was set at 100%. The satisfactory performance ranged from 96% to 100% and was not significantly different among the 13 health regions. The developed and implemented DTS panels can be used to monitor the quality of RTRI testing in Thailand.
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(This article belongs to the Special Issue 21st Century Point-of-Care, Near-Patient and Critical Care Testing)
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Changes of Dissociative Properties of Hemoglobin in Patients with Chronic Kidney Disease
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Justyna Korus, Maria Wydro, Maciej Gołębiowski, Kornelia Krakowska, Paweł Poznański, Kinga Musiał, Andrzej Konieczny, Hanna Augustyniak-Bartosik, Jakub Stojanowski, Mariusz Andrzej Kusztal and Tomasz Gołębiowski
Diagnostics 2024, 14(12), 1219; https://doi.org/10.3390/diagnostics14121219 (registering DOI) - 8 Jun 2024
Abstract
Background: The ability of hemoglobin to bind and dissociate oxygen is crucial in delivering oxygen to tissues and is influenced by a range of physiological states, compensatory mechanisms, and pathological conditions. This may be illustrated by the oxyhemoglobin dissociation curve (ODC). The
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Background: The ability of hemoglobin to bind and dissociate oxygen is crucial in delivering oxygen to tissues and is influenced by a range of physiological states, compensatory mechanisms, and pathological conditions. This may be illustrated by the oxyhemoglobin dissociation curve (ODC). The key parameter for evaluating the oxygen affinity to hemoglobin is p50. The aim of this study was to evaluate the impact of hemodialysis on p50 in a group of patients with chronic kidney disease (CKD). An additional goal was to assess the correlation between p50 and the parameters of erythropoiesis, point-of-care testing (POCT), and other laboratory parameters. Methods: One hundred and eighty patients (106 male, 74 female), mean age 62.5 ± 17 years, with CKD stage G4 and G5 were enrolled in this cross-sectional study. Patients were divided into two groups, including 65 hemodialysis (HD) patients and 115 patients not receiving dialysis (non-HD). During the standard procedure of arteriovenous fistula creation, blood samples from the artery (A) and the vein (V) were taken for POCT. The causes of CKD, as well as demographic and comorbidity data, were obtained from medical records and direct interviews. Results: The weekly dose of erythropoietin was higher in HD patients than in non-HD patients (4914 ± 2253 UI vs. 403 ± 798 UI, p < 0.01), but hemoglobin levels did not differ between these groups. In the group of non-HD patients, more advanced metabolic acidosis (MA) was found, compared to the group with HD. In arterial and venosus blood samples, the non-HD group had significantly lower pH, pCO2 and HCO3−. This group had a higher proportion of individuals with MA with HCO3− < 22 mmol/L (42% vs. 24%, p < 0.01). The absolute difference of p50 in arterial and venous blood was determined using the formula Δp50 = (p50-A) − (p50-V). Δp50 was significantly higher in the HD group in comparison to non-HD (0.08 ± 2.05 mmHg vs. −0.66 ± 1.93 mmHg, p = 0,02). There was a negative correlation between pH and the p50 value in arterial (pH-A vs. p50-A, r = −0.56, p < 0.01) and venous blood (pH-V vs. p50-V, r = −0.45, p < 0.01). In non-HD patients, hemoglobin levels correlated negatively with p50 (r = −0.29, p < 0.01), whereas no significant relation was found in HD patients. Conclusions: The ODC in pre-dialysis CKD (non-HD) patients is shifted to the right due to MA, and this is an additional factor influencing erythropoiesis. Hemodialysis restores the natural differences in hemoglobin’s dissociation characteristics in the arterial and venous circulation.
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(This article belongs to the Special Issue Advances in Diagnostics of Chronic Kidney Disease)
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Elastography of the Male Pelvic Region—Perspectives on Malignant Lesions
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Rute Santos, Martina Kastrup Loft and Malene Roland Vils Pedersen
Diagnostics 2024, 14(12), 1218; https://doi.org/10.3390/diagnostics14121218 (registering DOI) - 8 Jun 2024
Abstract
Ultrasound elastography is widely used to assess tissue stiffness for lesion characterization, including differentiation between benign and malignant lesions. This study focuses on the use of elastography in the male pelvis, including the prostate, testicles, and rectum, by comparing elastography types (shear wave
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Ultrasound elastography is widely used to assess tissue stiffness for lesion characterization, including differentiation between benign and malignant lesions. This study focuses on the use of elastography in the male pelvis, including the prostate, testicles, and rectum, by comparing elastography types (shear wave and strain). This article provides a summary of the existing literature on the use of elastography in the male pelvic region and outlines the clinical perspective. Ultrasound elastography is a good technique for evaluating and monitoring lesions in the male pelvic region.
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(This article belongs to the Special Issue Current Perspectives and Advances in Ultrasound Imaging)
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Segmentation and Multi-Timepoint Tracking of 3D Cancer Organoids from Optical Coherence Tomography Images Using Deep Neural Networks
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Francesco Branciforti, Massimo Salvi, Filippo D’Agostino, Francesco Marzola, Sara Cornacchia, Maria Olimpia De Titta, Girolamo Mastronuzzi, Isotta Meloni, Miriam Moschetta, Niccolò Porciani, Fabrizio Sciscenti, Alessandro Spertini, Andrea Spilla, Ilenia Zagaria, Abigail J. Deloria, Shiyu Deng, Richard Haindl, Gergely Szakacs, Agnes Csiszar, Mengyang Liu, Wolfgang Drexler, Filippo Molinari and Kristen M. Meiburgeradd
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Diagnostics 2024, 14(12), 1217; https://doi.org/10.3390/diagnostics14121217 (registering DOI) - 8 Jun 2024
Abstract
Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively
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Recent years have ushered in a transformative era in in vitro modeling with the advent of organoids, three-dimensional structures derived from stem cells or patient tumor cells. Still, fully harnessing the potential of organoids requires advanced imaging technologies and analytical tools to quantitatively monitor organoid growth. Optical coherence tomography (OCT) is a promising imaging modality for organoid analysis due to its high-resolution, label-free, non-destructive, and real-time 3D imaging capabilities, but accurately identifying and quantifying organoids in OCT images remain challenging due to various factors. Here, we propose an automatic deep learning-based pipeline with convolutional neural networks that synergistically includes optimized preprocessing steps, the implementation of a state-of-the-art deep learning model, and ad-hoc postprocessing methods, showcasing good generalizability and tracking capabilities over an extended period of 13 days. The proposed tracking algorithm thoroughly documents organoid evolution, utilizing reference volumes, a dual branch analysis, key attribute evaluation, and probability scoring for match identification. The proposed comprehensive approach enables the accurate tracking of organoid growth and morphological changes over time, advancing organoid analysis and serving as a solid foundation for future studies for drug screening and tumor drug sensitivity detection based on organoids.
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(This article belongs to the Special Issue Optical Coherence Tomography (OCT): State of the Art)
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Use of Deep-Amplicon Sequencing (DAS), Real-Time PCR and In Situ Hybridization to Detect H. pylori and Other Pathogenic Helicobacter Species in Feces from Children
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Yolanda Moreno Trigos, Miguel Tortajada-Girbés, Raquel Simó-Jordá, Manuel Hernández Pérez, Irene Hortelano, Miguel García-Ferrús and María Antonia Ferrús Pérez
Diagnostics 2024, 14(12), 1216; https://doi.org/10.3390/diagnostics14121216 (registering DOI) - 8 Jun 2024
Abstract
Background: Detecting Helicobacter pylori in fecal samples is easier and more comfortable than invasive techniques, especially in children. Thus, the objective of the present work was to detect H. pylori in feces from children by molecular methods as an alternative for diagnostic and
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Background: Detecting Helicobacter pylori in fecal samples is easier and more comfortable than invasive techniques, especially in children. Thus, the objective of the present work was to detect H. pylori in feces from children by molecular methods as an alternative for diagnostic and epidemiological studies. Methods: Forty-five fecal samples were taken from pediatric patients who presented symptoms compatible with H. pylori infection. HpSA test, culture, real-time quantitative PCR (qPCR), fluorescence in situ hybridization (FISH), direct viable count associated with FISH (DVC-FISH), and Illumina-based deep-amplicon sequencing (DAS) were applied. Results: No H. pylori colonies were isolated from the samples. qPCR analysis detected H. pylori in the feces of 24.4% of the patients. In comparison, DVC-FISH analysis showed the presence of viable H. pylori cells in 53.3% of the samples, 37% of which carried 23S rRNA mutations that confer resistance to clarithromycin. After DAS, H. pylori-specific 16S rDNA sequences were detected in 26 samples. In addition, DNA from H. hepaticus was identified in 10 samples, and H. pullorum DNA was detected in one sample. Conclusion: The results of this study show the presence of H. pylori, H. hepaticus, and H. pullorum in children’s stools, demonstrating the coexistence of more than one Helicobacter species in the same patient. The DVC-FISH method showed the presence of viable, potentially infective H. pylori cells in a high percentage of the children’s stools. These results support the idea that fecal–oral transmission is probably a common route for H. pylori and suggest possible fecal–oral transmission of other pathogenic Helicobacter species.
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(This article belongs to the Special Issue Diagnosis and Management of Gastrointestinal Infections)
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Magnetic Resonance Imaging Features of Plantar Vein Thrombosis
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Frederico Celestino Miranda, Adham do Amaral e Castro, Ariadne Moura Obrigon, Alexandre Leme Godoy-Santos, Durval do Carmo Barros Santos, Laercio Alberto Rosemberg and Atul Kumar Taneja
Diagnostics 2024, 14(12), 1215; https://doi.org/10.3390/diagnostics14121215 (registering DOI) - 8 Jun 2024
Abstract
Plantar vein thrombosis (PVT) is an underdiagnosed condition affecting the deep plantar veins, with challenging clinical diagnosis, often presenting with non-specific symptoms that mimic other foot pathologies. This study assessed the magnetic resonance imaging (MRI) features of patients diagnosed with PVT to contribute
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Plantar vein thrombosis (PVT) is an underdiagnosed condition affecting the deep plantar veins, with challenging clinical diagnosis, often presenting with non-specific symptoms that mimic other foot pathologies. This study assessed the magnetic resonance imaging (MRI) features of patients diagnosed with PVT to contribute to the understanding of this condition. We performed the comprehensive analysis of a substantial dataset, including 112 patients, with a total of 130 positive MRI scans (86 of the forefoot and 44 of the ankle) presenting with PVT. Upon evaluating all the veins of the feet, we observed a higher frequency of involvement of the lateral plantar veins (53.1%) when compared to the medial veins (3.8%). The most affected vascular segments in the forefeet were the plantar metatarsal veins (45.4%), the plantar venous arch (38.5%), and the plantar communicating veins (25.4%). The characteristic findings on MRI were perivascular edema (100%), muscular edema (86.2%), venous ectasia (100%), perivascular enhancement (100%), and intravenous filling defects (97.7%). Our study provides valuable insights into the imaging evaluation of PVT and shows that MRI is a reliable resource for such diagnosis.
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(This article belongs to the Special Issue Advances in Foot and Ankle Surgery: Diagnosis and Management)
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Diagnostic Role of Multi-Detector Computed Tomography in Acute Mesenteric Ischemia
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Francesco Michele Ronza, Teresa Letizia Di Gennaro, Gianfranco Buzzo, Luciana Piccolo, Marina Della Noce, Giovanni Giordano, Giuseppe Posillico, Luigi Pietrobono, Francesco Giuseppe Mazzei, Paolo Ricci, Salvatore Masala, Mariano Scaglione and Stefania Tamburrini
Diagnostics 2024, 14(12), 1214; https://doi.org/10.3390/diagnostics14121214 - 7 Jun 2024
Abstract
Mesenteric ischemia diagnosis is challenging, with an overall mortality of up to 50% of cases despite advances in treatment. The main problem that affects the outcome is delayed diagnosis because of non-specific clinical presentation. Multi-Detector CT Angiography (MDCTA) is the first-line investigation for
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Mesenteric ischemia diagnosis is challenging, with an overall mortality of up to 50% of cases despite advances in treatment. The main problem that affects the outcome is delayed diagnosis because of non-specific clinical presentation. Multi-Detector CT Angiography (MDCTA) is the first-line investigation for the suspected diagnosis of vascular abdominal pathologies and the diagnostic test of choice in suspected mesenteric bowel ischemia. MDCTA can accurately detect the presence of arterial and venous thrombosis, determine the extent and the gastrointestinal tract involved, and provide detailed information determining the subtype and the stage progression of the diseases, helping clinicians and surgeons with appropriate management. CT (Computed Tomography) can differentiate forms that are still susceptible to pharmacological or interventional treatment (NOM = non-operative management) from advanced disease with transmural necrosis in which a surgical approach is required. Knowledge of CT imaging patterns and corresponding vascular pathways is mandatory in emergency settings to reach a prompt and accurate diagnosis. The aims of this paper are 1. to provide technical information about the optimal CTA (CT Angiography) protocol; 2. to explain the CTA arterial and venous supply to the gastrointestinal tract and the relevant ischemic pattern; and 3. to describe vascular, bowel, and extraintestinal CT findings for the diagnosis of acute mesenteric ischemia.
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(This article belongs to the Special Issue Imaging Diagnosis in Abdomen, 2nd Edition)
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Few-Shot Learning for Medical Image Segmentation Using 3D U-Net and Model-Agnostic Meta-Learning (MAML)
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Aqilah M. Alsaleh, Eid Albalawi, Abdulelah Algosaibi, Salman S. Albakheet and Surbhi Bhatia Khan
Diagnostics 2024, 14(12), 1213; https://doi.org/10.3390/diagnostics14121213 - 7 Jun 2024
Abstract
Deep learning has attained state-of-the-art results in general image segmentation problems; however, it requires a substantial number of annotated images to achieve the desired outcomes. In the medical field, the availability of annotated images is often limited. To address this challenge, few-shot learning
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Deep learning has attained state-of-the-art results in general image segmentation problems; however, it requires a substantial number of annotated images to achieve the desired outcomes. In the medical field, the availability of annotated images is often limited. To address this challenge, few-shot learning techniques have been successfully adapted to rapidly generalize to new tasks with only a few samples, leveraging prior knowledge. In this paper, we employ a gradient-based method known as Model-Agnostic Meta-Learning (MAML) for medical image segmentation. MAML is a meta-learning algorithm that quickly adapts to new tasks by updating a model’s parameters based on a limited set of training samples. Additionally, we use an enhanced 3D U-Net as the foundational network for our models. The enhanced 3D U-Net is a convolutional neural network specifically designed for medical image segmentation. We evaluate our approach on the TotalSegmentator dataset, considering a few annotated images for four tasks: liver, spleen, right kidney, and left kidney. The results demonstrate that our approach facilitates rapid adaptation to new tasks using only a few annotated images. In 10-shot settings, our approach achieved mean dice coefficients of 93.70%, 85.98%, 81.20%, and 89.58% for liver, spleen, right kidney, and left kidney segmentation, respectively. In five-shot sittings, the approach attained mean Dice coefficients of 90.27%, 83.89%, 77.53%, and 87.01% for liver, spleen, right kidney, and left kidney segmentation, respectively. Finally, we assess the effectiveness of our proposed approach on a dataset collected from a local hospital. Employing five-shot sittings, we achieve mean Dice coefficients of 90.62%, 79.86%, 79.87%, and 78.21% for liver, spleen, right kidney, and left kidney segmentation, respectively.
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(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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Artificial Intelligence-Powered Imaging Biomarker Based on Mammography for Breast Cancer Risk Prediction
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Eun Kyung Park, Hyeonsoo Lee, Minjeong Kim, Taesoo Kim, Junha Kim, Ki Hwan Kim, Thijs Kooi, Yoosoo Chang and Seungho Ryu
Diagnostics 2024, 14(12), 1212; https://doi.org/10.3390/diagnostics14121212 - 7 Jun 2024
Abstract
The purposes of this study were to develop an artificial intelligence (AI) model for future breast cancer risk prediction based on mammographic images, investigate the feasibility of the AI model, and compare the AI model, clinical statistical risk models, and Mirai, a state
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The purposes of this study were to develop an artificial intelligence (AI) model for future breast cancer risk prediction based on mammographic images, investigate the feasibility of the AI model, and compare the AI model, clinical statistical risk models, and Mirai, a state of-the art deep learning algorithm based on screening mammograms for 1–5-year breast cancer risk prediction. We trained and developed a deep learning model using a total of 36,995 serial mammographic examinations from 21,438 women (cancer-enriched mammograms, 17.5%). To determine the feasibility of the AI prediction model, mammograms and detailed clinical information were collected. C-indices and area under the receiver operating characteristic curves (AUCs) for 1–5-year outcomes were obtained. We compared the AUCs of our AI prediction model, Mirai, and clinical statistical risk models, including the Tyrer–Cuzick (TC) model and Gail model, using DeLong’s test. A total of 16,894 mammograms were independently collected for external validation, of which 4002 were followed by a cancer diagnosis within 5 years. Our AI prediction model obtained a C-index of 0.76, with AUCs of 0.90, 0.84, 0.81, 0.78, and 0.81, to predict the 1–5-year risks. Our AI prediction model showed significantly higher AUCs than those of the TC model (AUC: 0.57; p < 0.001) and Gail model (AUC: 0.52; p < 0.001), and achieved similar performance to Mirai. The deep learning AI model using mammograms and AI-powered imaging biomarkers has substantial potential to advance accurate breast cancer risk prediction.
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(This article belongs to the Section Machine Learning and Artificial Intelligence in Diagnostics)
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Evaluating the Efficacy and Safety of Aspirin for Primary Cardiovascular Prevention in Asian Patients with Type 2 Diabetes: A Population-Based and Propensity Score-Matched Study
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Kai-Wei Chang, Jing-Yang Huang, Shun-Fa Yang and Kwo-Chang Ueng
Diagnostics 2024, 14(12), 1211; https://doi.org/10.3390/diagnostics14121211 - 7 Jun 2024
Abstract
The risk of developing cardiovascular disease is significantly higher for individuals with diabetes compared to those without. Aspirin has been widely used for primary prevention in diabetic patients. However, evidence is limited in the Asian population. We aimed to compare the effectiveness and
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The risk of developing cardiovascular disease is significantly higher for individuals with diabetes compared to those without. Aspirin has been widely used for primary prevention in diabetic patients. However, evidence is limited in the Asian population. We aimed to compare the effectiveness and safety of aspirin versus placebo for primary cardiovascular prevention in the Asian population with type 2 diabetes. In this study, we performed propensity score matching with non-aspirin users from January 2006 to December 2015 (n = 37,095 in each group after matching, PSM). We analyzed the incidence risk of all-cause mortality, composite cardiovascular events, and hospitalized major bleeding. The propensity score-matched (PSM) cohort of patients who received aspirin within one year of diabetes diagnosis was compared with the non-aspirin diabetic (DM) cohort. Baseline characteristics were balanced between the two groups. The median follow-up duration was 78 months. Aspirin users exhibited a slightly but significantly lower rate of all-cause mortality (HR: 0.92; 95% CI: 0.87 to 0.96). However, they also had a significantly higher composite cardiovascular risk (HR: 1.34; 95% CI: 1.28–1.40), including non-fatal acute myocardial infarction (HR: 1.33; 95% CI: 1.18 to 1.50), non-fatal ischemic stroke (HR: 1.38; 95% CI: 1.30 to 1.45), heart failure (HR: 1.18; 95% CI: 1.09 to 1.27), and coronary revascularization (HR: 1.94; 95% CI: 1.73 to 2.17). Aspirin users also faced a significantly higher risk of hospitalized major bleeding (HR: 1.08; 95% CI: 1.03 to 1.14). The presence of one or more additional risk factors did not influence the effectiveness and safety outcomes of aspirin, according to stratified analysis. In conclusion, in this real-world Asian diabetic population, aspirin was associated with a significantly lower mortality risk but also with higher risks of cardiovascular events and hospitalized bleeding. Aspirin may not play a role in the primary prevention of cardiovascular disease in such patients, regardless of additional risk factors.
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(This article belongs to the Topic Advances in Genetics and Precision Medicine in Human Diseases)
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Exploring the Susceptibility to Multiple Primary Tumors in Patients with Differentiated Thyroid Cancer
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Laura Valerio, Silvia Cantara, Elisa Mattii, Cristina Dalmiglio, Alfonso Sagnella, Antonia Salvemini, Alessandra Cartocci, Fabio Maino and Maria Grazia Castagna
Diagnostics 2024, 14(12), 1210; https://doi.org/10.3390/diagnostics14121210 - 7 Jun 2024
Abstract
Purpose: It was demonstrated that differentiated thyroid cancer (DTC) patients may develop multiple primary tumors (MPT) during follow-up. Many studies showed an association between reduced telomere length and cancer phenotype; in particular, the short telomeres were associated with the development of a primary
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Purpose: It was demonstrated that differentiated thyroid cancer (DTC) patients may develop multiple primary tumors (MPT) during follow-up. Many studies showed an association between reduced telomere length and cancer phenotype; in particular, the short telomeres were associated with the development of a primary tumor. However, the role of altered telomere length in MPT development has not yet been demonstrated. The aim of this study was to evaluate the possible correlation between a short telomere length in blood leukocytes and the risk of developing MPT in DTC patients. Patients and Methods: We retrospectively evaluated 167 DTC patients followed up for a median of 13.6 years. Our control group was represented by 105 healthy subjects without any thyroid disease or present or past history of tumors. Our study groups, age-matched, were evaluated for the relative telomere length measured in leukocytes of peripheral venous blood. Results: The relative telomere length (RTL) was significantly different in healthy subjects compared to the total group of differentiated thyroid cancer patients [p < 0.0001]. Shorter telomeres length was observed in DTC patients with (n = 32) and without (n = 135) MPT compared to healthy subjects (p < 0.0001 and p = 0.0002, respectively). At multivariate analysis, the parameters independently associated with the presence of MPT were RTL [OR: 0.466 (0.226–0.817), p = 0.018] and the familial DTC [OR: 2.949 (1.142–8.466), p = 0.032]. Conclusions: The results of this study suggest a role of the relative telomere length in predicting MPT development in DTC patients. Our results contribute to increasing the knowledge of the genetic mechanisms underlying MPT development in DTC patients, considering relative telomere length as a possible prognostic marker.
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(This article belongs to the Special Issue Recent Advances in Thyroid Carcinoma)
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A Novel Noninvasive Screening Tool for Dry Eye Disease
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Sabrina Vaccaro, Massimiliano Borselli, Giovanni Scalia, Costanza Rossi, Mario Damiano Toro, Robert Rejdak, Marco Pellegrini, Vincenzo Scorcia and Giuseppe Giannaccare
Diagnostics 2024, 14(12), 1209; https://doi.org/10.3390/diagnostics14121209 - 7 Jun 2024
Abstract
Purpose: To assess the feasibility and the diagnostic accuracy of the new tool, DEvice© (AI, Rome, Italy), for screening patients with dry eye disease (DED). Methods: This study was performed at the University Magna Græcia of Catanzaro. Enrolled patients were classified as affected
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Purpose: To assess the feasibility and the diagnostic accuracy of the new tool, DEvice© (AI, Rome, Italy), for screening patients with dry eye disease (DED). Methods: This study was performed at the University Magna Græcia of Catanzaro. Enrolled patients were classified as affected by DED (group 1) or not (group 2) using an already validated tool (Keratograph 5M, Oculus, Germany), evaluating the noninvasive keratograph breakup time (NIKBUT), tear meniscus height (TMH), meibomian gland loss (MGL), and bulbar redness. All the patients were then examined by means of DEvice©, which allowed the measurement of the relative humidity (RH) and temperature of the ocular surface. Symptoms were scored using the Ocular Surface Disease Index (OSDI) questionnaire. Results: Overall, 40 patients (17 males and 23 females, mean age 38.0 ± 17.1 years) were included: of these, 20 belonged to group 1 and the remaining 20 to group 2. Using Keratograph 5M, significant differences between groups 1 and 2 were detected for NIKBUT-first (respectively, 4.97 ± 1.85 vs. 13.95 ± 4.8 s; p < 0.0001) and for NIKBUT-average (10.55 ± 4.39 vs. 15.96 ± 4.08 s; p = 0.0003). No statistically significant changes were detected for TMH (p = 0.565), MGL (p = 0.051), and bulbar redness (p = 0.687). Using Device©, a statistically significant higher value of RH was found in group 1 compared to group 2 (respectively, 85.93 ± 10.63 vs. 73.05 ± 12.84%; p = 0.0049). A statistically significant correlation was found between RH and OSDI (r = 0.406; p = 0.009). The value RH showed a discriminating power to detect DED with an AUC = 0.782 (standard error 0.07264; 95% CI 0.6401–0.9249; p = 0.0022). Conclusions: The DEvice© can effectively discriminate DED patients from healthy subjects. The parameter RH showed good sensitivity, making this tool ideal for a fast and noninvasive DED screening.
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(This article belongs to the Special Issue Medical Optical Imaging: Current Diagnostics, Therapeutic and Surgical Applications in Ophthalmology—2nd Edition)
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Open AccessArticle
Clinical Validation of a Deep Learning-Based Software for Lumbar Bone Mineral Density and T-Score Prediction from Chest X-ray Images
by
Sheng-Chieh Tseng, Chia-En Lien, Cheng-Hung Lee, Kao-Chang Tu, Chia-Hui Lin, Amy Y. Hsiao, Shin Teng, Hsiao-Hung Chiang, Liang-Yu Ke, Chun-Lin Han, Yen-Cheng Lee, An-Chih Huang, Dun-Jhu Yang, Chung-Wen Tsai and Kun-Hui Chen
Diagnostics 2024, 14(12), 1208; https://doi.org/10.3390/diagnostics14121208 - 7 Jun 2024
Abstract
Screening for osteoporosis is crucial for early detection and prevention, yet it faces challenges due to the low accuracy of calcaneal quantitative ultrasound (QUS) and limited access to dual-energy X-ray absorptiometry (DXA) scans. Recent advances in AI offer a promising solution through opportunistic
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Screening for osteoporosis is crucial for early detection and prevention, yet it faces challenges due to the low accuracy of calcaneal quantitative ultrasound (QUS) and limited access to dual-energy X-ray absorptiometry (DXA) scans. Recent advances in AI offer a promising solution through opportunistic screening using existing medical images. This study aims to utilize deep learning techniques to develop a model that analyzes chest X-ray (CXR) images for osteoporosis screening. This study included the AI model development stage and the clinical validation stage. In the AI model development stage, the combined dataset of 5122 paired CXR images and DXA reports from the patients aged 20 to 98 years at a medical center was collected. The images were enhanced and filtered for hardware retention such as pedicle screws, bone cement, artificial intervertebral discs or severe deformity in target level of T12 and L1. The dataset was then separated into training, validating, and testing datasets for model training and performance validation. In the clinical validation stage, we collected 440 paired CXR images and DXA reports from both the TCVGH and Joy Clinic, including 304 pared data from TCVGH and 136 paired data from Joy Clinic. The pre-clinical test yielded an area under the curve (AUC) of 0.940, while the clinical validation showed an AUC of 0.946. Pearson’s correlation coefficient was 0.88. The model demonstrated an overall accuracy, sensitivity, and specificity of 89.0%, 88.7%, and 89.4%, respectively. This study proposes an AI model for opportunistic osteoporosis screening through CXR, demonstrating good performance and suggesting its potential for broad adoption in preliminary screening among high-risk populations.
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(This article belongs to the Special Issue Fifth Anniversary of "Machine Learning and Artificial Intelligence in Diagnostics" Section)
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Open AccessArticle
Development of Aptamers for RNase Inactivation in Xtract-Free™ Sample Collection and Transport Medium
by
Luke T. Daum, John D. Rodriguez and James P. Chambers
Diagnostics 2024, 14(12), 1207; https://doi.org/10.3390/diagnostics14121207 - 7 Jun 2024
Abstract
There is a significant need to develop new environmentally friendly, extraction-free sample collection mediums that can effectively preserve and protect genetic material for point-of-care and/or self-collection, home-collection, and mail-back testing. Systematic evolution of ligands by exponential enrichment (SELEX) was used to create anti-ribonuclease
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There is a significant need to develop new environmentally friendly, extraction-free sample collection mediums that can effectively preserve and protect genetic material for point-of-care and/or self-collection, home-collection, and mail-back testing. Systematic evolution of ligands by exponential enrichment (SELEX) was used to create anti-ribonuclease (RNase) deoxyribonucleic acid (DNA) aptamers against purified RNase A conjugated to paramagnetic carboxylated beads. Following eight rounds of SELEX carried out under various stringency conditions, e.g., selection using Xtract-Free™ (XF) specimen collection medium and elevated ambient temperature of 28 °C, a panel of five aptamers was chosen following bioinformatic analysis using next-generation sequencing. The efficacy of aptamer inactivation of RNase was assessed by monitoring ribonucleic acid (RNA) integrity via fluorometric and real-time RT-PCR analysis. Inclusion of aptamers in reaction incubations resulted in an 8800- to 11,200-fold reduction in RNase activity, i.e., digestion of viral RNA compared to control. Thus, anti-RNase aptamers integrated into XF collection medium as well as other commercial reagents and kits have great potential for ensuring quality intact RNA for subsequent genomic analyses.
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(This article belongs to the Special Issue Microbiology Laboratory: Sample Collection and Diagnosis Advances)
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Open AccessArticle
IL-6 Polymorphism as a Predisposing Genetic Factor for Gestational Diabetes or Preeclampsia Development in Pregnancy with Obesity in Relation to VEGF and VEGFF Receptor Gene Expression Modalities
by
Panagiotis Halvatsiotis, Theodora Tsokaki, Vasileios Tsitsis, Lina Palaiodimou, Georgios Tsivgoulis, Iraklis Tsangaris, Maria Ourania Panagiotou and Dimitra Houhoula
Diagnostics 2024, 14(11), 1206; https://doi.org/10.3390/diagnostics14111206 - 6 Jun 2024
Abstract
The increased prevalence of obesity worldwide has been implicated in the alarming rise of the incidence of gestational diabetes and preeclampsia, which are both considered threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6)
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The increased prevalence of obesity worldwide has been implicated in the alarming rise of the incidence of gestational diabetes and preeclampsia, which are both considered threatening conditions for both mother and fetus. We studied gene polymorphisms of the proinflammatory cytokine Interleukin 6 (IL-6) and the gene expression levels of VEGF (vascular endothelial growth factor) and VEGF-R (endothelial growth factor receptor), all known to be involved in pregnancy complications, aiming to identify possible predisposing risk factors in pregnancies with obesity. The G allele of IL-6 was found to correspond with an increased risk for gestational diabetes and preeclampsia occurrence. Furthermore, in obese pregnant mothers with either gestational diabetes or pre-existing type 2 diabetes and those who developed preeclampsia, it was confirmed that gene expression levels of VEGF were reduced while they were increased for VEGF receptors. We conclude that the genetic profile of an obese pregnant woman shares a common background with that of a patient with pre-existing type 2 diabetes mellitus, and therefore predisposes them to complications in pregnancy.
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(This article belongs to the Section Pathology and Molecular Diagnostics)
Open AccessArticle
Gastro-Esophageal Cancer: Can Radiomic Parameters from Baseline 18F-FDG-PET/CT Predict the Development of Distant Metastatic Disease?
by
Ricarda Hinzpeter, Seyed Ali Mirshahvalad, Roshini Kulanthaivelu, Andres Kohan, Claudia Ortega, Ur Metser, Amy Liu, Adam Farag, Elena Elimova, Rebecca K. S. Wong, Jonathan Yeung, Raymond Woo-Jun Jang and Patrick Veit-Haibach
Diagnostics 2024, 14(11), 1205; https://doi.org/10.3390/diagnostics14111205 - 6 Jun 2024
Abstract
We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to
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We aimed to determine if clinical parameters and radiomics combined with sarcopenia status derived from baseline 18F-FDG-PET/CT could predict developing metastatic disease and overall survival (OS) in gastroesophageal cancer (GEC). Patients referred for primary staging who underwent 18F-FDG-PET/CT from 2008 to 2019 were evaluated retrospectively. Overall, 243 GEC patients (mean age = 64) were enrolled. Clinical, histopathology, and sarcopenia data were obtained, and primary tumor radiomics features were extracted. For classification (early-stage vs. advanced disease), the association of the studied parameters was evaluated. Various clinical and radiomics models were developed and assessed. Accuracy and area under the curve (AUC) were calculated. For OS prediction, univariable and multivariable Cox analyses were performed. The best model included PET/CT radiomics features, clinical data, and sarcopenia score (accuracy = 80%; AUC = 88%). For OS prediction, various clinical, CT, and PET features entered the multivariable analysis. Three clinical factors (advanced disease, age ≥ 70 and ECOG ≥ 2), along with one CT-derived and one PET-derived radiomics feature, retained their significance. Overall, 18F-FDG PET/CT radiomics seems to have a potential added value in identifying GEC patients with advanced disease and may enhance the performance of baseline clinical parameters. These features may also have a prognostic value for OS, improving the decision-making for GEC patients.
Full article
(This article belongs to the Special Issue Abdominal Imaging: Recent Advances and Future Trends)
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Enhancing Medical Image Retrieval with UMLS-Integrated CNN-Based Text Indexing
by
Karim Gasmi, Hajer Ayadi and Mouna Torjmen
Diagnostics 2024, 14(11), 1204; https://doi.org/10.3390/diagnostics14111204 - 6 Jun 2024
Abstract
In recent years, Convolutional Neural Network (CNN) models have demonstrated notable advancements in various domains such as image classification and Natural Language Processing (NLP). Despite their success in image classification tasks, their potential impact on medical image retrieval, particularly in text-based medical image
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In recent years, Convolutional Neural Network (CNN) models have demonstrated notable advancements in various domains such as image classification and Natural Language Processing (NLP). Despite their success in image classification tasks, their potential impact on medical image retrieval, particularly in text-based medical image retrieval (TBMIR) tasks, has not yet been fully realized. This could be attributed to the complexity of the ranking process, as there is ambiguity in treating TBMIR as an image retrieval task rather than a traditional information retrieval or NLP task. To address this gap, our paper proposes a novel approach to re-ranking medical images using a Deep Matching Model (DMM) and Medical-Dependent Features (MDF). These features incorporate categorical attributes such as medical terminologies and imaging modalities. Specifically, our DMM aims to generate effective representations for query and image metadata using a personalized CNN, facilitating matching between these representations. By using MDF, a semantic similarity matrix based on Unified Medical Language System (UMLS) meta-thesaurus, and a set of personalized filters taking into account some ranking features, our deep matching model can effectively consider the TBMIR task as an image retrieval task, as previously mentioned. To evaluate our approach, we performed experiments on the medical ImageCLEF datasets from 2009 to 2012. The experimental results show that the proposed model significantly enhances image retrieval performance compared to the baseline and state-of-the-art approaches.
Full article
(This article belongs to the Special Issue Medical Data Processing and Analysis—2nd Edition)
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Open AccessArticle
Clinical and Hemodynamic Features of Aneurysm Rupture in Coil Embolization of Intracranial Aneurysms
by
Tomoaki Suzuki, Hitoshi Hasegawa, Kohei Shibuya, Hidemoto Fujiwara and Makoto Oishi
Diagnostics 2024, 14(11), 1203; https://doi.org/10.3390/diagnostics14111203 - 6 Jun 2024
Abstract
Intraprocedural rupture (IPR) during coil embolization (CE) of an intracranial aneurysm is a significant clinical concern that necessitates a comprehensive understanding of its clinical and hemodynamic predictors. Between January 2012 and December 2023, 435 saccular cerebral aneurysms were treated with CE at our
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Intraprocedural rupture (IPR) during coil embolization (CE) of an intracranial aneurysm is a significant clinical concern that necessitates a comprehensive understanding of its clinical and hemodynamic predictors. Between January 2012 and December 2023, 435 saccular cerebral aneurysms were treated with CE at our institution. The inclusion criterion was extravasation or coil protrusion during CE. Postoperative data were used to confirm rupture points, and computational fluid dynamics (CFD) analysis was performed to assess hemodynamic characteristics, focusing on maximum pressure (Pmax) and wall shear stress (WSS). IPR occurred in six aneurysms (1.3%; three ruptured and three unruptured), with a dome size of 4.7 ± 1.8 mm and a D/N ratio of 1.5 ± 0.5. There were four aneurysms in the internal carotid artery (ICA), one in the anterior cerebral artery, and one in the middle cerebral artery. ICA aneurysms were treated using adjunctive techniques (three balloon-assisted, one stent-assisted). Two aneurysms (M1M2 and A1) were treated simply, yet had relatively small and misaligned domes. CFD analysis identified the rupture point as a flow impingement zone with Pmax in five aneurysms (83.3%). Time-averaged WSS was locally reduced around this area (1.3 ± 0.7 [Pa]), significantly lower than the aneurysmal dome (p < 0.01). Hemodynamically unstable areas have fragile, thin walls with rupture risk. A microcatheter was inserted along the inflow zone, directed towards the caution area. These findings underscore the importance of identifying hemodynamically unstable areas during CE. Adjunctive techniques should be applied with caution, especially in small aneurysms with axial misalignment, to minimize the rupture risk.
Full article
(This article belongs to the Special Issue Advances in Cerebrovascular Imaging and Interventions)
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