LN-RADS, RECIST 1.1 and Node-RADS Classification in the Assessment of Lymph Nodes

NCT06527027 | Recruiting

• 1 other identifier: 2022/ABM/03/00027
• Study Type: interventional
• Target: 1,000
• Locations: 1 country
• Sites: 6

Brief Summary

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.

Conditions

Lymph Node Neoplasm; Lymph Node Metastasis

Keywords

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

Outcome Measures

Primary Outcomes (1)

• The effectiveness of assessment of LN-RADS, Node-RADS and RECIST 1.1

  Comparative assessment of the effectiveness of each of the three tested diagnostic methods (LN-RADS, RECIST 1.1, Node-RADS) in the form of an assessment of sensitivity, specificity and predictive value (positive/negative).

  After accomplished lymph node assessment according to classification system (up to 1 year)

Secondary Outcomes (2)

• Quantification of the agreement between raters assessing according to the specific classification system

  After accomplished lymph node assessment according to classification system (up to 1 year)

• The predictive value of various morphological parameters of lymph nodes regarding in context of clinical characteristics

  After accomplished lymph node assessment according to classification system (up to 1 year)

Study Arms (3)

Lymph node assessment according to RECIST 1.1

SHAM COMPARATOR

Other: Lymph node assessment according to RECIST 1.1 in CT; Other: Lymph node assessment according to RECIST 1.1 in MRI

Lymph node assessment according to LN-RADS

EXPERIMENTAL

Other: Lymph node assessment according to LN-RADS in CT; Other: Lymph node assessment according to LN-RADS in MRI

Lymph node assessment according to Node-RADS

EXPERIMENTAL

Other: Lymph node assessment according to Node-RADS in CT; Other: Lymph node assessment according to Node-RADS in MRI

Interventions

Lymph node assessment according to RECIST 1.1 in CT 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

Lymph node assessment according to Node-RADS in CT 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

Lymph node assessment according to LN-RADS in CT 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

Lymph node assessment according to RECIST 1.1 in MRI 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

Lymph node assessment according to Node-RADS in MRI 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

Lymph node assessment according to LN-RADS in MRI 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

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• 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.

You may not qualify if:

• 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.

Sponsors & Collaborators

• Copernicus Memorial Hospital: lead
• Medical Research Agency, Poland: collaborator

Study Sites (6)

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

Krakow, Poland

ACTIVE NOT RECRUITING

Copernicus Memorial Hospital

Lodz, 93-513, Poland

RECRUITING

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

Lodz, Poland

ACTIVE NOT RECRUITING

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

Warsaw, Poland

ACTIVE NOT RECRUITING

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

Warsaw, Poland

ACTIVE NOT RECRUITING

Professor Orłowski Hospital in Warsaw , Independent Public Healthcare Centre

Warsaw, Poland

ACTIVE NOT RECRUITING

Related Publications (11)

• 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.

  PMID: 33585994 BACKGROUND

• 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.

  PMID: 12576367 BACKGROUND

• 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.

  PMID: 11091725 BACKGROUND

• 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.

  PMID: 19297159 BACKGROUND

• 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.

  PMID: 5543548 BACKGROUND

• 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.

  PMID: 14280727 BACKGROUND

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

  PMID: 12021590 BACKGROUND

• 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.

  PMID: 10730652 BACKGROUND

• 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.

  PMID: 2122673 BACKGROUND

• 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.

  PMID: 12509965 BACKGROUND

• 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.

  PMID: 38672646 RESULT

Related Links

• Related Info

MeSH Terms

Conditions

Lymphatic Metastasis; Lymphadenopathy; Recurrence

Interventions

Magnetic Resonance Spectroscopy

Condition Hierarchy (Ancestors)

Neoplasm Metastasis; Neoplastic Processes; Neoplasms; Pathologic Processes; Pathological Conditions, Signs and Symptoms; Lymphatic Diseases; Hemic and Lymphatic Diseases; Disease Attributes

Intervention Hierarchy (Ancestors)

Spectrum Analysis; Chemistry Techniques, Analytical; Investigative Techniques

Study Officials

• Cezary Chudobiński, PhD

  Copernicus Memoriał Hospital

  PRINCIPAL INVESTIGATOR

Central Study Contacts

Cezary Chudobiński, PhD

CONTACT

+4842 689 58 99; cezary.chudobinski@wp.pl

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: RANDOMIZED
• Masking: DOUBLE
• Who Masked: PARTICIPANT, INVESTIGATOR
• Purpose: DIAGNOSTIC
• Intervention Model: PARALLEL
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Principal Investigator

Study Record Dates

• First Submitted: July 21, 2024
• First Posted: July 30, 2024
• Study Start: December 1, 2023
• Primary Completion (Estimated): December 31, 2028
• Study Completion (Estimated): December 31, 2028
• Last Updated: December 30, 2025

Record last verified: 2025-11

Data Sharing

• IPD Sharing: Will not share

Locations

PL (6)