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

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

RECRUITING

Clinical Phase

NA

Total Enrollment

1000 participants

Study Classification

INTERVENTIONAL

Study Start Date

2023-12-01

Study Completion Date

2028-12-31

Brief Summary

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The project aims to evaluate the value of the new LN-RADS scales for lymph node classification in CT and MR and to compare this method with two other methods RECIST 1.1 and Node-RADS.

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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Lymph Node Neoplasm Lymph Node Metastasis

Keywords

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Lymph Nodes Lymph Node Excision Tomography, X-ray computed Lymphadenopathy Recurrence Magnetic Resonance Imaging

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

DIAGNOSTIC

Blinding Strategy

DOUBLE

Participants Investigators

Study Groups

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Lymph node assessment according to RECIST 1.1

Group Type SHAM_COMPARATOR

Lymph node assessment according to RECIST 1.1 in CT

Intervention Type OTHER

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

Intervention Type OTHER

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

Group Type EXPERIMENTAL

Lymph node assessment according to LN-RADS in CT

Intervention Type OTHER

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

Intervention Type OTHER

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

Group Type EXPERIMENTAL

Lymph node assessment according to Node-RADS in CT

Intervention Type OTHER

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

Intervention Type OTHER

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.

Intervention Type OTHER

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.

Intervention Type OTHER

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

Intervention Type OTHER

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.

Intervention Type OTHER

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.

Intervention Type OTHER

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

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

* diagnosed or suspected cancer,
* 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

* non-diagnostic CT/MRI images of lymph nodes due to reasons such as movement artifacts, artifacts from metal elements and any other factors that do not allow for proper assessment of the nodes,
* inconclusive histopathological or cytological results, which do not allow the nodes to be classified into one of two groups - benign or malignant.
Minimum Eligible Age

18 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Medical Research Agency, Poland

OTHER_GOV

Sponsor Role collaborator

Copernicus Memorial Hospital

OTHER

Sponsor Role lead

Responsible Party

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Cezary Chudoniński

Principal Investigator

Responsibility Role 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

Site Status ACTIVE_NOT_RECRUITING

Copernicus Memorial Hospital

Lodz, , Poland

Site Status RECRUITING

Independent Public Healthcare Centre (SPZOZ) , University Clinical Hospital No. 2 of the Medical University of Łódź

Lodz, , Poland

Site Status ACTIVE_NOT_RECRUITING

Doradztwo i Zarządzanie w Opiece Zdrowotnej A.K. Sp.z o.o

Warsaw, , Poland

Site Status ACTIVE_NOT_RECRUITING

Maria Skłodowska-Curie National Research Institute of Oncology - National Research Institute

Warsaw, , Poland

Site Status ACTIVE_NOT_RECRUITING

Professor Orłowski Hospital in Warsaw , Independent Public Healthcare Centre

Warsaw, , Poland

Site Status ACTIVE_NOT_RECRUITING

Countries

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Poland

Central Contacts

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Cezary Chudobiński, PhD

Role: CONTACT

Phone: +4842 689 58 99

Email: [email protected]

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.

Reference Type BACKGROUND
PMID: 12509965 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 2122673 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 33585994 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 12576367 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 11091725 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 19297159 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 5543548 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 14280727 (View on PubMed)

Ahuja A, Ying M. An overview of neck node sonography. Invest Radiol. 2002 Jun;37(6):333-42. doi: 10.1097/00004424-200206000-00005.

Reference Type BACKGROUND
PMID: 12021590 (View on PubMed)

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.

Reference Type BACKGROUND
PMID: 10730652 (View on PubMed)

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.

Reference Type RESULT
PMID: 38672646 (View on PubMed)

Provided Documents

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Document Type: Informed Consent Form

View Document

Related Links

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Other Identifiers

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2022/ABM/03/00027

Identifier Type: -

Identifier Source: org_study_id