LN-RADS, RECIST 1.1 and Node-RADS Classification in the Assessment of Lymph Nodes
NCT ID: NCT06527027
Last Updated: 2025-12-30
Study Results
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Basic Information
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RECRUITING
NA
1000 participants
INTERVENTIONAL
2023-12-01
2028-12-31
Brief Summary
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The main tested system in the study is LN-RADS, the comparators are RECIST 1.1 and Node-RADS criteria.
Lymph nodes are a key diagnostic and therapeutic element in oncology. Despite the technological progress, the detection of neoplastic changes in the lymph nodes is of low effectiveness, which results from the imperfection of the criteria used. Currently, the most widely used criterion is the RECIST 1.1 guideline developed in the 1990s, according to which the lymph node dimension in the short axis with a cut-off point of 10 mm is decisive. Lymph nodes smaller than 10 mm across are considered normal. It is a criterion with a high error rate, both due to the false-negative diagnoses (with small metastases below 10 mm) and false-positive diagnoses (in the case of inflammatory lymphadenopathy).
A particular disadvantageous situation is when the metastatic nodes and their transverse dimension is less than 10 mm, because they are treated as healthy nodes and the degree of the disease advancement is underestimated. As a result, the patient is not treated properly - no complete lymphadenectomy, no radiotherapy to the area of these nodes or insufficient systemic treatment. In all cases, underestimating the stage of the neoplastic diseases increases the risk of the recurrence.
LN-RADS accounts small metastases in nodes about 3 mm in size, thus about 20% more metastatic nodes may be detected compared to RECIST 1.1 method. This means that currently, according to RECIST 1.1 rules, approx. 20% of patients have missed nodal metastases and consequently receive insufficient treatment resulting in relapse. Previous studies have shown that RECIST 1.1 shows a high level of underestimation of metastatic nodes. The Node-RADS system, as the second comparator next to RECIT 1.1, is a fairly new system moving towards the structural assessment of lymph nodes, but proposed arbitrarily, without hard evidence for its effectiveness. Despite the publication of the Node-RADS system in a medical journal, it is not validated. The Node-RADS has numerous limitations and weaknesses that reduce its value.
Detailed Description
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Conditions
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Keywords
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Study Design
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RANDOMIZED
PARALLEL
DIAGNOSTIC
DOUBLE
Study Groups
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Lymph node assessment according to RECIST 1.1
Lymph node assessment according to RECIST 1.1 in CT
RECIST 1.1 classifies lymph nodes as healthy when they have a short axis dimension (SAD) of \<10 mm; Nodes with a SAD dimension \>=10 mm are considered to be involved in the cancer process.
Lymph node assessment according to RECIST 1.1 in MRI
RECIST 1.1 classifies lymph nodes as healthy when they have a short axis dimension (SAD) of \<10 mm; Nodes with a SAD dimension \>=10 mm are considered to be involved in the cancer process.
Lymph node assessment according to LN-RADS
Lymph node assessment according to LN-RADS in CT
LN-RADS (Lymph Node Reporting and Data System) categorizes nodes according to a scale that reflects the radiological and clinical forms of the nodes and the level of probability of a malignant process:
LN-RADS 1 - normal lymph node LN-RADS 2 - enlarged and fatty lymph node, not suspected from an oncological point of view LN-RADS 3 - lymph node with features suggesting reactive changes. LN-RADS 4a - lymph node with slight oncological suspicion LN-RADS 4b - lymph node with strong oncological suspicion LN-RADS 5 - definitely cancerous node
Lymph node assessment according to LN-RADS in MRI
LN-RADS (Lymph Node Reporting and Data System) categorizes nodes according to a scale that reflects the radiological and clinical forms of the nodes and the level of probability of a malignant process:
LN-RADS 1 - normal lymph node LN-RADS 2 - enlarged and fatty lymph node, not suspected from an oncological point of view LN-RADS 3 - lymph node with features suggesting reactive changes. LN-RADS 4a - lymph node with slight oncological suspicion LN-RADS 4b - lymph node with strong oncological suspicion LN-RADS 5 - definitely cancerous node
Lymph node assessment according to Node-RADS
Lymph node assessment according to Node-RADS in CT
Node-RADS classifies lymph nodes taking into account parameters such as: size, degree of homogeneity, boundaries and shape of the node. Depending on the degree of change in a given parameter, an appropriate number of points are awarded in each category, and the sum of the points determines the final classification of the node into one of five categories of probability of being affected by a cancer process: 1-very low, 2-low, 3-medium, 4 -high, 5-very high.
Lymph node assessment according to Node-RADS in MRI
Node-RADS classifies lymph nodes taking into account parameters such as: size, degree of homogeneity, boundaries and shape of the node. Depending on the degree of change in a given parameter, an appropriate number of points are awarded in each category, and the sum of the points determines the final classification of the node into one of five categories of probability of being affected by a cancer process: 1-very low, 2-low, 3-medium, 4 -high, 5-very high.
Interventions
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Lymph node assessment according to RECIST 1.1 in CT
RECIST 1.1 classifies lymph nodes as healthy when they have a short axis dimension (SAD) of \<10 mm; Nodes with a SAD dimension \>=10 mm are considered to be involved in the cancer process.
Lymph node assessment according to Node-RADS in CT
Node-RADS classifies lymph nodes taking into account parameters such as: size, degree of homogeneity, boundaries and shape of the node. Depending on the degree of change in a given parameter, an appropriate number of points are awarded in each category, and the sum of the points determines the final classification of the node into one of five categories of probability of being affected by a cancer process: 1-very low, 2-low, 3-medium, 4 -high, 5-very high.
Lymph node assessment according to LN-RADS in CT
LN-RADS (Lymph Node Reporting and Data System) categorizes nodes according to a scale that reflects the radiological and clinical forms of the nodes and the level of probability of a malignant process:
LN-RADS 1 - normal lymph node LN-RADS 2 - enlarged and fatty lymph node, not suspected from an oncological point of view LN-RADS 3 - lymph node with features suggesting reactive changes. LN-RADS 4a - lymph node with slight oncological suspicion LN-RADS 4b - lymph node with strong oncological suspicion LN-RADS 5 - definitely cancerous node
Lymph node assessment according to RECIST 1.1 in MRI
RECIST 1.1 classifies lymph nodes as healthy when they have a short axis dimension (SAD) of \<10 mm; Nodes with a SAD dimension \>=10 mm are considered to be involved in the cancer process.
Lymph node assessment according to Node-RADS in MRI
Node-RADS classifies lymph nodes taking into account parameters such as: size, degree of homogeneity, boundaries and shape of the node. Depending on the degree of change in a given parameter, an appropriate number of points are awarded in each category, and the sum of the points determines the final classification of the node into one of five categories of probability of being affected by a cancer process: 1-very low, 2-low, 3-medium, 4 -high, 5-very high.
Lymph node assessment according to LN-RADS in MRI
LN-RADS (Lymph Node Reporting and Data System) categorizes nodes according to a scale that reflects the radiological and clinical forms of the nodes and the level of probability of a malignant process:
LN-RADS 1 - normal lymph node LN-RADS 2 - enlarged and fatty lymph node, not suspected from an oncological point of view LN-RADS 3 - lymph node with features suggesting reactive changes. LN-RADS 4a - lymph node with slight oncological suspicion LN-RADS 4b - lymph node with strong oncological suspicion LN-RADS 5 - definitely cancerous node
Eligibility Criteria
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Inclusion Criteria
* planned lymph node biopsy or lymphadenectomy,
* planned or performed CT/MRI covering an area of the body with lymph nodes, - verified histopathologically or cytologically,
* informed consent to participate in the study.
Exclusion Criteria
* inconclusive histopathological or cytological results, which do not allow the nodes to be classified into one of two groups - benign or malignant.
18 Years
ALL
No
Sponsors
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Medical Research Agency, Poland
OTHER_GOV
Copernicus Memorial Hospital
OTHER
Responsible Party
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Cezary Chudoniński
Principal Investigator
Principal Investigators
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Cezary Chudobiński, PhD
Role: PRINCIPAL_INVESTIGATOR
Copernicus Memoriał Hospital
Locations
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Maria Skłodowska-Curie National Research Institute of Oncology - National Research Institute
Krakow, , Poland
Copernicus Memorial Hospital
Lodz, , Poland
Independent Public Healthcare Centre (SPZOZ) , University Clinical Hospital No. 2 of the Medical University of Łódź
Lodz, , Poland
Doradztwo i Zarządzanie w Opiece Zdrowotnej A.K. Sp.z o.o
Warsaw, , Poland
Maria Skłodowska-Curie National Research Institute of Oncology - National Research Institute
Warsaw, , Poland
Professor Orłowski Hospital in Warsaw , Independent Public Healthcare Centre
Warsaw, , Poland
Countries
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Central Contacts
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Facility Contacts
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Cezary Chudobiński, PhD
Role: primary
References
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Woolgar JA, Rogers SN, Lowe D, Brown JS, Vaughan ED. Cervical lymph node metastasis in oral cancer: the importance of even microscopic extracapsular spread. Oral Oncol. 2003 Feb;39(2):130-7. doi: 10.1016/s1368-8375(02)00030-1.
Rubaltelli L, Proto E, Salmaso R, Bortoletto P, Candiani F, Cagol P. Sonography of abnormal lymph nodes in vitro: correlation of sonographic and histologic findings. AJR Am J Roentgenol. 1990 Dec;155(6):1241-4. doi: 10.2214/ajr.155.6.2122673.
Elsholtz FHJ, Asbach P, Haas M, Becker M, Beets-Tan RGH, Thoeny HC, Padhani AR, Hamm B. Introducing the Node Reporting and Data System 1.0 (Node-RADS): a concept for standardized assessment of lymph nodes in cancer. Eur Radiol. 2021 Aug;31(8):6116-6124. doi: 10.1007/s00330-020-07572-4. Epub 2021 Feb 14.
Prenzel KL, Monig SP, Sinning JM, Baldus SE, Brochhagen HG, Schneider PM, Holscher AH. Lymph node size and metastatic infiltration in non-small cell lung cancer. Chest. 2003 Feb;123(2):463-7. doi: 10.1378/chest.123.2.463.
Yoshimura G, Sakurai T, Oura S, Suzuma T, Tamaki T, Umemura T, Kokawa Y, Yang Q. Evaluation of Axillary Lymph Node Status in Breast Cancer with MRI. Breast Cancer. 1999 Jul 25;6(3):249-258. doi: 10.1007/BF02967179.
Choi YJ, Ko EY, Han BK, Shin JH, Kang SS, Hahn SY. High-resolution ultrasonographic features of axillary lymph node metastasis in patients with breast cancer. Breast. 2009 Apr;18(2):119-22. doi: 10.1016/j.breast.2009.02.004. Epub 2009 Mar 17.
Huvos AG, Hutter RV, Berg JW. Significance of axillary macrometastases and micrometastases in mammary cancer. Ann Surg. 1971 Jan;173(1):44-6. doi: 10.1097/00000658-197101000-00006. No abstract available.
LEBORGNE R, LEBORGNE F Jr, LEBORGNE JH. SOFT-TISSUE RADIOGRAPHY OF AXILLARY NODES WITH FATTY INFILTRATION. Radiology. 1965 Mar;84:513-5. doi: 10.1148/84.3.513. No abstract available.
Ahuja A, Ying M. An overview of neck node sonography. Invest Radiol. 2002 Jun;37(6):333-42. doi: 10.1097/00004424-200206000-00005.
Chikui T, Yonetsu K, Nakamura T. Multivariate feature analysis of sonographic findings of metastatic cervical lymph nodes: contribution of blood flow features revealed by power Doppler sonography for predicting metastasis. AJNR Am J Neuroradiol. 2000 Mar;21(3):561-7.
Chudobinski C, Swiderski B, Antoniuk I, Kurek J. Enhancements in Radiological Detection of Metastatic Lymph Nodes Utilizing AI-Assisted Ultrasound Imaging Data and the Lymph Node Reporting and Data System Scale. Cancers (Basel). 2024 Apr 19;16(8):1564. doi: 10.3390/cancers16081564.
Provided Documents
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Document Type: Informed Consent Form
Related Links
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Related Info
Other Identifiers
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2022/ABM/03/00027
Identifier Type: -
Identifier Source: org_study_id