Neoplasms

Skin and Connective Tissue Diseases

All Conditions

Blood and Lymph Conditions

Symptoms and General Pathology

Breast Neoplasms

Lymphedema

Breast Cancer Lymphedema

Breast Diseases

Skin Diseases

Lymphatic Diseases

Postoperative Complications

Baseline data measurement of this group of patients: arm circumference（positive） and ICG (positive).

Baseline data measurement of this group of patients: arm circumference（negative） and ICG (positive).

Baseline data measurement of this group of patients: arm circumference（negative） and ICG (negative).

No Intervention.Only learn ICG image features of different label groups

No Intervention.

Siyao Liu, Dr

liu siyao

Shu Wang, Dr

Breast cancer related lymphedema (BCRL) is the most common complication after breast cancer surgery, which brings a heavy psychological and spiritual burden to patients. For a long time, the diagnosis and treatment of lymphedema has been a difficult point in domestic and foreign research. To a large extent, it is because most of the patients who come to see a doctor have already developed obvious lymphedema, and the internal lymphatic vessels have undergone pathological remodeling\[1\] Therefore, it is particularly important to detect early lymphedema and intervene in time through the use of sensitive screening tools. Indocyanine green (ICG) lymphangiography is a relatively new method, which can display superficial lymph flow in real time and quickly, and will not be affected by radioactivity \[7\]. In 2007, indocyanine green lymphography was used for the first time to evaluate the function of superficial lymphatic vessels. In 2011, Japanese scholars found skin reflux signs based on ICG lymphography data of 20 patients with lymphedema after breast cancer surgery, and they were roughly divided into three types according to their severity: splash, star cluster, and diffuse (Figure 1) \[8\]. Later, in 2016, a prospective study involving 196 people affirmed the value of ICG lymphography in the early diagnosis of lymphedema, and made the images of ICG lymphography more specific stages 0-5 \[9\], but The staging is still based on the three types of skin reflux symptoms found in a small sample clinical study in 2011, which is not completely applicable in actual clinical applications. In addition, when abnormal skin reflux symptoms appear on ICG lymphangiography, the pathophysiological changes that occur in the body lack research and exploration. Therefore, this research hopes to refine the image features of ICG lymphography through machine learning (deep learning), and establish a PKUPH model for diagnosing early lymphedema by staging the image features.

Study on Classification Method of Indocyanine Green Lymphography Based on Deep Learning

Study on Classification Method of Indocyanine Green Lymphography in Diagnosing Breast Cancer-related Lymphedema Based on Deep Learning

there is no plan to make individual participant data (IPD) available to other researchers

Establish a PKUPH model for the diagnosis of lymphedema by ICG based on deep learning

Peking University People's Hospital

No interventions are administered. Data is retrospectively collected in an anonymized way after ethical approval at each site.

No intervention.

ODELIA is a project that aims to improve breast cancer detection in magnetic resonance imaging by utilizing artificial intelligence and swarm learning (MRI). The project will create an open-source swarm learning software framework that will be used to train AI models for breast cancer detection. These models' performance will be compared to that of conventional AI models, and the results will be used to assess the effectiveness of swarm learning in improving the accuracy and robustness of AI models. The project will use retrospective, anonymized breast MRI datasets with manual ground truth labels for cancer presence. The study is not associated with any patient treatment or intervention. The project's goal is to provide evidence of the clinical benefits of swarm learning in the context of breast cancer screening, such as accelerated development, improved performance, and robust generalizability.

Artificial Intelligence (AI) is set to revolutionize healthcare as its diagnostic performance approaches that of clinical experts. In particular, in cancer screening, AI could help patients to make better-informed decisions and reduce medical error. However, this requires large datasets whose collection faces severe practical, ethical and legal obstacles. These obstacles could potentially be overcome with swarm learning (SL) where partners jointly train AI models without sharing any data. Yet, access to SL technology is currently limited because no studies have implemented SL in a true multinational setup, no freely usable implementation of SL is available, researchers \& healthcare providers have no experience with setting up SL networks and policymakers are currently unaware of the broader implications of SL.

ODELIA will aim to solve these issues: ODELIA will build an open-source software framework for SL, providing an assembly line for the streamlined development of AI solutions in a preclinical setting. To serve as a blueprint for future SL-based AI systems, ODELIA partners collaborate as a consortium to develop AI models for the detection of breast cancer in magnetic resonance imaging (MRI). The size of ODELIA's distributed database will be substantial and ODELIA's AI models could reach expert-level performance for breast cancer screening.

Thereby, ODELIA will could not just deliver a useful medical application, but provide evidence to summarize the clinical benefit of SL in terms of accelerated development, increased performance and robust generalizability.

To achieve this, ODELIA partners will collect retrospective, anonymized breast MRI datasets with manual ground truth labels for the presence of cancer, and will train AI models conventionelly and via SL. The performance of these technical approaches will be compared. The aim of the study is to test the methodology of Swarm Learning and the performance of AI algorithms developed within ODELIA on retrospective data. There will be no effect on treatment of patients as all evaluations will be done retrospectively. No patient treatment or any intervention is associated with the study.

Female patients only, as defined per the European Society of Breast Imaging (EUSOBI) screening guidelins of 2023

A Retrospective Analysis of Magnetic Resonance Imaging Data for Breast Cancer Screening in the Open Consortium for Decentralized Medical Artificial Intelligence

Data are collected at multiple study centers and the decision whether or not to release IPD is made at each study center.

Diagnostic performance for breast cancer detection (Sensitivity and specificity) compared to the gold stnandard method of expert-based assessment of breast MRI, may be summarized in a receiver operating characteristic curve for multiple threshold values, comparing multiple technical approaches, including swarm-learning based AI models and local AI models.

European Institute for Biomedical Imaging Research (EIBIR), Austria

University Hospital, Aachen

Vall d'Hebron Institute of Oncology

Mitera Hospital

Radboud University Medical Center

UMC Utrecht

Ribera Salud Hospitals, Spain

Fraunhofer Institute for Digital Medicine (MEVIS), Germany

University Hospital, Zürich

Cambridge University Hospitals NHS Foundation Trust

Technische Universität Dresden

Head and Neck Neoplasms

Approximately 150 adults referred for suspected HNC will be recruited.

Approximately 15 ENT and Maxillofacial) clinicians will be recruited.

Sarah Webb

Unknown Unknown

James Moor

Shirley Pringle

Katharine Davies

Nithin George

Chrysostomos Tornari

Iqbal Mohammed

Stuart Winter

Vinidh Paleri

Can a patient-reported symptom-based risk stratification system improve the suspected head and neck cancer (HNC) pathway?

Our methodology includes six interlinked work packages to deliver our aim, with EVEREST-HN 1 encompassing the first of these and seeking to optimise a patient-reported symptom inventory for HNC and outline requirement specification for the SYmptom iNput Clinical (SYNC) system.

The EVEREST-HN pathway should be based on a comprehensive understanding of existing HNC diagnostic pathways and what patients and clinicians value in these. The language used within the EVEREST pathway needs to be accessible and optimal to elicit appropriate information.

EVEREST-HN 1: EVolution of a patiEnt-REported Symptom-based Risk Stratification sySTem

EVolution of a patiEnt-REported Symptom-based Risk Stratification sySTem to Redesign the Suspected Head and Neck Cancer Referral Pathway (Phase 1)

To optimise a patient-reported symptom inventory for HNC and outline requirement specification for the SYmptom iNput Clinical (SYNC) system

To understand how clinicians decide subsequent steps for patients referred with suspected HNC, the language patients and clinicians use to describe symptoms and patients' and clinicians' views and experiences of the current diagnostic process for HNC. with a focus on what would work for EVEREST-HN study.

University of Leeds

Royal Marsden NHS Foundation Trust

Infections

Rare Diseases

Leukemia

Hematologic Neoplasms

Communicable Diseases

Bacteremia

Neutropenia

Sepsis

Toxemia

Hematologic Diseases

Agranulocytosis

Leukopenia

Cytopenia

Leukocyte Disorders

Syndrome

Systemic Inflammatory Response Syndrome

Inflammation

Granulocytopenia

Acute Graft Versus Host Disease

Anti-Infective Agents

All Drugs and Chemicals

Fluoroquinolones

Receiving induction chemotherapy for acute leukemia, and receiving fluoroquinolone (FQ) prophylaxis.

Undergoing hematopoietic stem cell transplantation (HCT), and receiving fluoroquinolone (FQ) prophylaxis.

Observational study with no intervention.

Michael Satlin

Vance G Fowler, MD

This is a prospective, observational cohort study to assess the frequency with which neutropenic patients with hematologic malignancies and hematopoietic cell transplant (HCT) recipients are colonized with fluoroquinolone-resistant Enterobacterales (FQRE) and the clinical impact of FQRE colonization.

This is a prospective, observational cohort study to assess the frequency with which neutropenic patients with hematologic malignancies and hematopoietic cell transplant (HCT) recipients are colonized with fluoroquinolone-resistant Enterobacterales (FQRE) and the clinical impact of FQRE colonization.

The investigator will collect perianal swabs from patients receiving induction chemotherapy for acute leukemia or undergoing hematopoietic stem cell transplantation (HCT), and who are receiving fluoroquinolone (FQ) prophylaxis. FQRE colonization will be assessed by culture, and the investigator will correlate FQRE colonization with the risk of Gram-negative bacteremia during neutropenia.

Population: 410 adults with acute leukemia who are receiving induction chemotherapy and HCT recipients who are receiving FQ prophylaxis during neutropenia.

Results of this study will be combined with a portion of subject data from an identically-designed R01-funded study of FQRE colonization. The combined data will be used for study analysis and reporting.

Perianal swabs are collected from subjects and only isolates are retained. Bloodstream infection isolates are retained.

Screening for Colonization With Resistant Enterobacterales in Neutropenic Patients With Hematologic Malignancies

Screening for Colonization With Resistant Enterobacterales in Neutropenic Patients With Hematologic Malignancies (SCENE)

Acquisition of FQRE and ESBL-E in patients not initially colonized with these organisms

Gram-negative BSI during the episode of neutropenia

Colonization with fluoroquinolone-resistant Enterobacterales (FQRE) and Extended-spectrum-beta-lactamase-producing Enterobacterales (ESBL-E) upon initiation of chemotherapy

Occurrence (Yes/No) of fever (≥38.0°C) during the episode of neutropenia.

Any BSI during the episode of neutropenia

Intensive care unit admission prior to recovery from neutropenia

90-day mortality from the collection of the first swab

Weill Medical College of Cornell University

National Institute of Allergy and Infectious Diseases (NIAID)

Duke University

Cysts

Echinococcosis

Parovarian Cyst

Pathological Conditions, Anatomical

Helminthiasis

Parasitic Diseases

Hydatidosis

Alveolar Echinococcosis

Hematinics

Liver Extracts

patients who underwent surgery for liver hydatid cyst from 2004 to 2018 in two major university-affiliated hospitals in Fars Province, southern Iran

The current study aimed to evaluate the therapeutic features and complications of liver hydatid cyst in patients who underwent surgery for CE in Fars province, southern Iran.

A total of 293 patients who underwent surgery for liver hydatid cyst from 2004 to 2018 in Fars Province, southern Iran, were retrospectively evaluated. The clinical records of patients were reviewed and the demographic and clinical characteristics of each patient were assessed.

Fars province with the capital of Shiraz in one of the thirty-one provinces of Iran located in the southwest part of the country with a population of more than 4.6 million people of which 67.6% living in urban areas, 32.2% in rural areas and 0.3% live as nomad tribes. The average temperature of Fars province is 17.8 °C, ranging between 4.7 °C and 29.2 °C and the annual rainfall is 261mm. Animal farming and agriculture are of great importance as they are considered as two main economic bases of this province. This type of livelihood has facilitated the presence of some of the zoonotic diseases such as CE and toxocariasis and leishmaniasis.

Data Collection Hospital records of a total of 293 patients who underwent surgery for liver hydatid cyst from 2004 to 2018 in two major university-affiliated hospitals in Fars Province, southern Iran, were retrospectively evaluated. In all cases, the preliminary diagnosis of hydatid cyst has been confirmed by postoperative pathological findings. So, the inclusion criterion of operation with the diagnosis of CE was considered while reviewing the records.

Information such as age, sex, presenting signs and symptoms of hydatid cyst, number and the specific location of cystic structures, history of relapse, reoperation, characteristics of the cyst (calcification, puss discharge, multicystic, multiloculated, daughter cyst, rupture, inflammation, superimposed infection, and septation), early postoperative complications, diagnostic procedures such as ultrasound scanning, computed tomography, X-rays, pathology reports, lab data, operation information and, drug therapy were extracted from the hospital records of each patient. The surgical procedure used for the patients, radical or conservative, was noted.

The Current Study Aimed to Evaluate the Therapeutic Features and Complications of Liver Hydatid Cyst in Patients Who Underwent Surgery for CE in Fars Province, Southern Iran.

Management of Liver Hydatid Cysts: A Retrospective Analysis of 293 Cases From Southern Iran

The individuals' data will not be shared with other researchers, as there is no need to do so.

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Study on Classification Method of Indocyanine Green Lymphography Based on Deep Learning	NCT04824378	Breast Cancer R... Deep Learning	No Intervention...	-	Peking University People's Hospital
A Retrospective Analysis of Magnetic Resonance Imaging Data for Breast Cancer Screening in the Open Consortium for Decentralized Medical Artificial Intelligence	NCT05698056	Breast Cancer	No intervention...	18 Years - 90 Years	Technische Universität Dresden
EVEREST-HN 1: EVolution of a patiEnt-REported Symptom-based Risk Stratification sySTem	NCT05909020	Head and Neck C...	No intervention...	18 Years -	Royal Marsden NHS Foundation Trust
Screening for Colonization With Resistant Enterobacterales in Neutropenic Patients With Hematologic Malignancies	NCT04710212	Hematologic Mal... Leukemia, Acute Neutropenia Bloodstream Inf...	No intervention...	18 Years -	Duke University
The Current Study Aimed to Evaluate the Therapeutic Features and Complications of Liver Hydatid Cyst in Patients Who Underwent Surgery for CE in Fars Province, Southern Iran.	NCT04363151	Patients Who Un...	No intervention...	-	Shiraz University of Medical Sciences

Spots Global Cancer Trial Database for no intervention.