(1123 days)
Ventana Medical Systems, Inc. developed the Ventana Anti-S100 antibody for use on the Ventana ES automated immunohistochemistry system. Ventana Anti-S100 is substantially equivalent to other marketed immunohistochemical stains used in the identification of cells of normal and abnormal lineage as an aid in diagnosis of anaplastic tumors.
Ventana Medical Systems' Anti-S100 (rabbit polyclonal) contains rabbit antiserum directed against an epitope found on S100 protein. S100 used for immunization was purified by ammonium sulphate fractionation, DEAE-Sephadex chromatography and gel filtration on Sephadex G100. The antiserum was obtained from rabbits after repeated injections of S100 protein complexed to methylated bovine serum albumin in complete Freund's adjuvant.
Here's an analysis of the provided text regarding the acceptance criteria and study to prove device performance:
Acceptance Criteria and Device Performance
1. Table of Acceptance Criteria and Reported Device Performance
| Acceptance Criteria | Reported Device Performance |
|---|---|
| Sensitivity | Appropriate staining of nerve cells in normal tissues tested; staining of 80% of melanoma tissues tested. |
| Inter-run Reproducibility | Staining intensity and pattern of staining was similar in all tissue slides evaluated across 16 different instrument runs. |
| Intra-run Reproducibility | Staining intensity and pattern of staining was similar in all 10 slides from the same tissue within one run. |
| Specificity | Pre-absorption of antiserum with S100 protein resulted in complete loss of staining of tissue sections, indicating S100-specific binding. |
| Clinical Equivalence (Implicit) | Compares favorably to published literature (for sensitivity). Substantially equivalent to other marketed immunohistochemical stains (e.g., EMA) for identification of cells of normal and abnormal lineage as an aid in diagnosis of anaplastic tumors. |
2. Sample size used for the test set and the data provenance
- Sample Size: The exact number of individual samples (patients or tissue blocks) tested is not specified. The text mentions "Paraffin embedded preparations from normal and pathologic samples" and later "80% of the melanoma tissues tested". For reproducibility, it mentions "samples of the same tissue on 16 different instrument runs" and "ten samples of the same tissue within one run." This indicates a testing strategy but not the total number of unique cases.
- Data Provenance: "Samples were obtained from excess tissues obtained for reasons other than the present study." This indicates the data is retrospective and likely from a single institution or source (though the country of origin is not specified).
3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts
- The document does not specify the number of experts or their qualifications used to establish ground truth for the test set.
4. Adjudication method for the test set
- The document does not specify any adjudication method for the test set. The evaluation seems to have been based on "specific staining intensity and background staining" without detail on who performed this evaluation or how discrepancies were resolved.
5. If a multi-reader multi-case (MRMC) comparative effectiveness study was done
- No, an MRMC comparative effectiveness study was not done. The study focuses on the performance of the device itself (staining characteristics and reproducibility) and compares its sensitivity favorably to published literature, rather than comparing human reader performance with and without AI assistance.
6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done
- Yes, in a sense, a standalone study was done. This device is a diagnostic reagent (antibody) used in an automated system, not an AI algorithm. The study directly evaluates the performance of the reagent system (Ventana Anti-S100 on the Ventana ES Automated Slide Stainer) in terms of staining characteristics, sensitivity, and reproducibility. It assesses the output of the automated staining process itself, which is then interpreted by a human. The "algorithm" here is the chemical process and automation, and its output is what's being evaluated.
7. The type of ground truth used
- The ground truth appears to be based on clinical diagnosis/pathological classification of the "normal and pathologic samples" (e.g., normal tissues, leiomyosarcomas, squamous cell carcinomas, breast carcinomas, carcinoid tumors, and melanomas). The "appropriate staining of nerve cells in normal tissues" and "staining of 80% of the melanoma tissues" implies that the underlying histological classification of these tissues served as the ground truth against which the S100 staining was evaluated.
8. The sample size for the training set
- This is a diagnostic reagent, not a machine learning algorithm, so there is no concept of a "training set" in the conventional AI sense. The antibody is developed based on its immunological properties against S100 protein.
9. How the ground truth for the training set was established
- As there is no training set for an AI algorithm, this question is not applicable. The "ground truth" for the antibody's development would be the known structure and presence of the S100 protein, and the antibody's specificity relies on the antigen-antibody binding mechanism confirmed by pre-absorption studies.
§ 866.5550 Immunoglobulin (light chain specific) immunological test system.
(a)
Identification. An immunoglobulin (light chain specific) immunological test system is a device that consists of the reagents used to measure by immunochemical techniques both kappa and lambda types of light chain portions of immunoglobulin molecules in serum, other body fluids, and tissues. In some disease states, an excess of light chains are produced by the antibody-forming cells. These free light chains, unassociated with gamma globulin molecules, can be found in a patient's body fluids and tissues. Measurement of the various amounts of the different types of light chains aids in the diagnosis of multiple myeloma (cancer of antibody-forming cells), lymphocytic neoplasms (cancer of lymphoid tissue), Waldenstrom's macroglobulinemia (increased production of large immunoglobulins), and connective tissue diseases such as rheumatoid arthritis or systemic lupus erythematosus.(b)
Classification. Class II (performance standards).