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System, model and kit for evaluating thyroid nodule malignancy degree or probability

A technology for thyroid nodules and malignancy, applied in the field of medical testing, can solve problems such as the inability to accurately determine whether there is a suspicion of malignancy, and no obvious improvement after overtreatment

Active Publication Date: 2022-04-29
西湖欧米(杭州)生物科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In other words, these two methods can only classify some benign nodules very well, and cannot accurately determine whether they are suspected of being malignant, so these two methods do not significantly improve the possible overtreatment

Method used

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  • System, model and kit for evaluating thyroid nodule malignancy degree or probability
  • System, model and kit for evaluating thyroid nodule malignancy degree or probability
  • System, model and kit for evaluating thyroid nodule malignancy degree or probability

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0069] Example 1—Establishment of a clinical multicenter prospective cohort.

[0070] First, establish a national multi-center clinical trial for sample collection.

[0071] Inclusion criteria:

[0072] (1) Age ≥ 18 years old, ≤ 70 years old;

[0073] (2) Treatment-naïve patients with thyroid nodules without drug treatment;

[0074] (3) Thyroid nodules ≥ 5 mm, thyroid fine needle aspiration, Bethesda III / IV;

[0075] (4) Total / partial thyroidectomy with histological report of corresponding cytopathological puncture nodules;

[0076] (5) Patients voluntarily participate in the research after informed consent.

[0077] Exclusion criteria:

[0078] (1) Patients without surgery;

[0079] (2) Insufficient sample size;

[0080] A total of 3120 samples were collected in this study. After excluding the samples that did not meet the standards, the remaining 2450 samples were used for sample pre-processing and data collection.

Embodiment 2

[0081] Example 2—FNA sample processing method assisted by pressure circulation system.

[0082] FNA puncture samples were obtained by ultrasound guidance or intraoperative repeated aspiration and puncture using a 19-27 g syringe needle. The puncture samples were first lysed by 0.5 mL red blood cell lysate at a low temperature of 4 °C, reacted for 5 min, put into a centrifuge, and centrifuged at 300 g for 10 min. After centrifugation, discard the solution and retain the cells remaining after centrifugation.

[0083] Subsequently, PCT technology samples were used for pretreatment.

[0084] PCT is an emerging semi-automated sample preparation technology for tissue lysis and protein and peptide extraction, in a small volume (150 microliters) container, through ultra-high pressure (up to 45k psi) and standard atmospheric pressure circulation to promote tissue and cells. Dissolves, accelerates proteolysis and enzymatic hydrolysis. The main feature of PCT is the semi-automatic p...

Embodiment 3

[0087] Example 3 - Selection of candidate proteins.

[0088] In this embodiment, candidate peptides and corresponding parent and child ions that are beneficial to the determination of benign and malignant thyroid nodules are screened out.

[0089] i) 14 protein combinations and 20 protein combinations discovered in previous studies;

[0090] ii) The model in the previous study selected 49 proteins for the diagnosis of follicular carcinoma and follicular adenoma;

[0091] iii) Differential proteins between follicular carcinoma and follicular adenoma obtained from the data in previous studies;

[0092] iv) 47 proteins stained by immunohistochemistry in clinic;

[0093] v) 76 proteins related to thyroid cancer reported in the literature;

[0094] After the inventors combined the proteins obtained through the above channels, the initial candidate pool covered a total of 212 proteins.

[0095] Next, the inventors screened 121 proteins and 537 parent-child ion pairs as the par...

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Abstract

The invention relates to a system, a model and a kit for evaluating the malignancy degree or probability of thyroid nodules. The method comprises the following steps: processing a fine needle puncture tissue biopsy sample by adopting a pressure circulation technology, detecting proteomics data of target protein or polypeptide in the obtained sample by adopting a high performance liquid chromatography method and a mass spectrometry method, processing peptide fragment peak area information of the mass spectrometry data, and carrying out AI modeling, the method obtains a final evaluation result (malignant probability), can provide a reference for the thyroid nodule malignant degree for clinic, and also can provide a second evaluation result (malignant probability) for doctors for thyroid nodules which cannot be clinically identified in the prior art. The invention also provides a corresponding kit, a system, an evaluation model and related uses.

Description

technical field [0001] The invention relates to the field of medical detection, and in particular to a method for evaluating the malignancy of thyroid nodules based on targeted detection of proteins or polypeptides and machine learning. Background technique [0002] Thyroid nodules (Thyroid Nodules) is a common clinical disease, according to the autopsy report, the incidence of thyroid nodules in the general population is about 50% to 60%, mostly in women. The vast majority of patients with thyroid nodules have no clinical symptoms and are often found through physical examination or self-touch. Among the thyroid nodules found by pathological examination, only 5% to 15% of the nodules are malignant nodules, that is, thyroid cancer. [0003] The evaluation of thyroid nodules recommended by current clinical guidelines is mainly based on the following three points: first, high-resolution ultrasound, second, blood biochemical indicators, and third, fine needle aspiration biopsy ...

Claims

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Application Information

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IPC IPC(8): G01N30/02G01N30/72G01N30/86G01N33/68G06N20/00G16B5/00G16B40/00
CPCG01N30/02G01N30/72G01N30/8675G01N33/6848G16B5/00G16B40/00G06N20/00
Inventor 郭天南朱怡孙耀庭陈晨葛伟刚胡一凡许路昂
Owner 西湖欧米(杭州)生物科技有限公司
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