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| Name | Class |
|---|---|
| Medical Research Agency, Poland | OTHER_GOV |
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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.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| Lymph node assessment according to RECIST 1.1 | Sham Comparator |
| |
| Lymph node assessment according to LN-RADS | Experimental |
| |
| Lymph node assessment according to Node-RADS | Experimental |
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| Name | Type | Description | Arm Group Labels | Other Names |
|---|---|---|---|---|
| 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. |
| Measure | Description | Time Frame |
|---|---|---|
| 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) |
| Measure | Description | Time Frame |
|---|---|---|
| Quantification of the agreement between raters assessing according to the specific classification system | Estimation of the level of agreement between investigators in individual lymph node staging systems. | 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 |
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Inclusion Criteria:
Exclusion Criteria:
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| Name | Role | Phone | Extension | |
|---|---|---|---|---|
| Cezary Chudobiński, PhD | Contact | +4842 689 58 99 | cezary.chudobinski@wp.pl |
| Name | Affiliation | Role |
|---|---|---|
| Cezary Chudobiński, PhD | Copernicus Memoriał Hospital | Principal Investigator |
| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Maria Skłodowska-Curie National Research Institute of Oncology - National Research Institute | Active, not recruiting | Krakow | Poland |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 33585994 | Background | 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. | |
| 12576367 | Background |
| Label | URL |
|---|---|
| Related Info | View source |
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| ICF | No | No | Yes | Informed Consent Form | May 12, 2025 | Dec 8, 2025 |
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| 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 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 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 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 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 |
|
Assessment of the predictive value of various morphological parameters of lymph nodes and clinical information in the context of differentiating benign and cancerous nodes. |
| After accomplished lymph node assessment according to classification system (up to 1 year) |
| Copernicus Memorial Hospital | Recruiting | Lodz | 93-513 | Poland |
|
| Independent Public Healthcare Centre (SPZOZ) , University Clinical Hospital No. 2 of the Medical University of Łódź | Active, not recruiting | Lodz | Poland |
| Doradztwo i Zarządzanie w Opiece Zdrowotnej A.K. Sp.z o.o | Active, not recruiting | Warsaw | Poland |
| Maria Skłodowska-Curie National Research Institute of Oncology - National Research Institute | Active, not recruiting | Warsaw | Poland |
| Professor Orłowski Hospital in Warsaw , Independent Public Healthcare Centre | Active, not recruiting | Warsaw | Poland |
| 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. |
| 11091725 | 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. |
| 19297159 | 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. |
| 5543548 | 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. |
| 14280727 | 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. |
| 12021590 | 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. |
| 10730652 | 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. |
| 2122673 | 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. |
| 12509965 | 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. |
| 38672646 | Result | 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. |
| ICF_002.pdf |
| ID | Term |
|---|---|
| D008207 | Lymphatic Metastasis |
| D000072281 | Lymphadenopathy |
| D012008 | Recurrence |
| ID | Term |
|---|---|
| D009362 | Neoplasm Metastasis |
| D009385 | Neoplastic Processes |
| D009369 | Neoplasms |
| D010335 | Pathologic Processes |
| D013568 | Pathological Conditions, Signs and Symptoms |
| D008206 | Lymphatic Diseases |
| D006425 | Hemic and Lymphatic Diseases |
| D020969 | Disease Attributes |
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| ID | Term |
|---|---|
| D009682 | Magnetic Resonance Spectroscopy |
| ID | Term |
|---|---|
| D013057 | Spectrum Analysis |
| D002623 | Chemistry Techniques, Analytical |
| D008919 | Investigative Techniques |
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