(281 days)
Unknown
The device description mentions "automated intelligent cell assessment software" and "pixel area detection algorithms," which could potentially involve AI/ML, but the summary does not explicitly state the use of AI, ML, or DNN, nor does it provide details about training sets or model types typically associated with AI/ML. The focus is on image processing and algorithms, which can exist independently of AI/ML.
No.
The device is intended to aid in diagnosis and prognosis by quantifying biomarkers, not to provide therapy or directly influence therapy outcomes through intervention.
Yes
The device aids in the management, prognosis, and prediction of therapy outcomes for breast cancer by quantifying estrogen receptors in tissue specimens, which directly supports medical decision-making for patient care.
Yes
The device description explicitly states "QCA is a standalone, automated intelligent cell assessment software device". While it utilizes existing hardware (personal computer, microscope, camera, printer, Internet connection), the device itself is the software application that performs the analysis.
Yes, this device is an IVD (In Vitro Diagnostic).
Here's why:
- Intended Use: The intended use explicitly states that the device is "intended to detect and classify cells of clinical interest" and "intended to measure and quantitate the percentage and intensity of positively stained nuclei in formalin-fixed, paraffin-embedded tissue specimens immunohistochemically stained for estrogen receptors." This involves analyzing biological specimens (tissue) to provide information about a patient's health status (ER expression in breast cancer).
- Indications for Use: The indications for use state that it is "indicated for use as an aid in the management, prognosis and prediction of therapy outcomes of breast cancer." This clearly links the device's output to clinical decision-making regarding a patient's condition.
- Specimen Type: The device analyzes "formalin-fixed, paraffin-embedded tissue specimens," which are biological specimens derived from the human body.
- Clinical Context: The device is used in the context of breast cancer diagnosis and management, which is a clinical application.
- Adjunctive Tool for Pathologists: While it's an "adjunctive computer-assisted methodology," it's designed to assist qualified pathologists in interpreting results from immunohistochemical staining, which is a standard IVD procedure.
The definition of an IVD generally includes devices intended for use in the examination of specimens derived from the human body to provide information for diagnostic, monitoring, or compatibility purposes. This device fits that description by analyzing tissue specimens to provide quantitative data on ER expression, which is used in the diagnosis, prognosis, and prediction of therapy outcomes for breast cancer.
N/A
Intended Use / Indications for Use
The QCA device is intended to detect and classify cells of clinical interest based on recognition of cellular areas of particular color and chromatic intensity. In this software application, the QCA device is intended to measure and quantitate the percentage and intensity of positively stained nuclei in formalin-fixed, paraffin-embedded tissue specimens immunohistochemically stained for estrogen receptors.
It is indicated for use as an aid in the management, prognosis and prediction of therapy outcomes of breast cancer when used with reagents validated for those indications.
The QCA system is an adjunctive computer-assisted methodology to assist the reproducibility of a qualified pathologist in the acquisition and measurement of images from microscopic slides of breast cancer specimens stained for the presence of estrogen (ER) nuclear receptor protein. The accuracy of the test result depends upon the quality of immunohistochemical staining. It is the responsibility of a qualified pathologist to employ appropriate morphological studies and controls to assure the validity of the QCA ER scores.
Product codes
NQN
Device Description
QCA is a standalone, automated intelligent cell assessment software device that analyzes digital images of cells of interest by pixel color attributes and pixel area detection algorithms. The software system utilizes a pathologist's own personal computer, light microscope, digital camera, printer, and Internet connection.
Mentions image processing
QCA is a standalone, automated intelligent cell assessment software device that analyzes digital images of cells of interest by pixel color attributes and pixel area detection algorithms.
Mentions AI, DNN, or ML
Not Found.
Input Imaging Modality
Microscopic images captured by a digital camera.
Anatomical Site
Breast tissue specimens.
Indicated Patient Age Range
Not Found.
Intended User / Care Setting
Qualified pathologist.
Description of the training set, sample size, data source, and annotation protocol
Not Found.
Description of the test set, sample size, data source, and annotation protocol
A non-clinical study was outlined using 32 invasive breast carcinoma tissue specimens with a range of ER positivity/negativity. Tissue blocks were sent to an outside CLIA-approved lab that performed IHC for ER on all 32 cases following predicate device’s specifications. Predicate device results were kept blind. The outside lab returned all 32 IHC slides to Cell Analysis. Based on professional judgment, two pathologists captured 3 representative images from each case (2 * 3 * 32 = 192). Three different pathologists performed independent manual inspection and derived scores for 192 randomly mixed images. Manual inspection results were kept blind. One of the three above-mentioned pathologists used the candidate device (QCA) to analyze the same 192 images without manually overriding the program’s scores. All results were un-blinded and data from predicate device, manual inspections, and QCA were compared.
For the qualitative percent positivity comparison study, the data included the original 32 invasive breast carcinomas (6 images taken per case/slide) and an additional 120 cases (to optimize the number of images to consider per case study). These cases included both invasive and in-situ breast cancers that were processed and stained according to the protocol listed in the Appendix.
Summary of Performance Studies (study type, sample size, AUC, MRMC, standalone performance, key results)
QCA ER Percent Positivity vs. Manual Percent Positivity Evaluation
Study Type: Regression analysis comparing QCA's nuclear pixel-based ER percent positivity against individual pathologist's manually assessed positively stained nuclei.
Sample Size: 192 images (3 images x 2 pathologists capturing images x 32 cases).
Key Results:
- Pathologist #1: Corr Coef (R) = 0.957, Slope = 0.92, Intercept = 6.18, SE of regression line = 7.09, N=192
- Pathologist #2: Corr Coef (R) = 0.934, Slope = 0.97, Intercept = 0.15, SE of regression line = 8.81, N=192
- Pathologist #3: Corr Coef (R) = 0.925, Slope = 0.92, Intercept = 4.62, SE of regression line = 7.36, N=192
QCA ER Score vs. Manual Score Evaluation
Study Type: Comparison of QCA generated intensity scores against manually generated intensity scores.
Sample Size: 192 images.
Key Results:
- Pathologist #1: R = 0.849, slope = 0.98, intercept = -0.01, standard error of regression line = 0.37, sample size = 192.
- Pathologist #2: R = 0.854, slope = 0.92, intercept = -0.02, standard error of regression line = 0.36, sample size = 192.
- Pathologist #3: (No specific R, slope, intercept, SE values provided in the text for Pathologist #3's Intensity Score, only a scatter plot is referenced).
QCA ER Percent Positivity vs. Predicate Device ER Percent Positivity Evaluation
Study Type: Regression analysis comparing the predicate device results to those of QCA for percent positivity.
Sample Size: 32 cases.
Key Results: Corr Coef (R) is 0.897, the slope is 0.88, the intercept is 21.3, the standard error of the regression line is 11.8, and the sample size (n) is 32.
Qualitative Percent Positivity Comparison Study
Study Type: Agreement tables comparing manual against QCA methods using example cut-off values of ≥5.0% and ≥1.0% positivity.
Sample Size: 152 (32 + 120) cases/slides.
Key Results (for ≥1.0% Positive):
| Positive | Negative | ||
|---|---|---|---|
| QCA | Positive | 149 | 0 |
| Negative | 0 | 3 |
Inter-microscope Variability Study
Study Type: Regression results of QCA ER score and QCA percent positivity against those of the manual results across different microscopes.
Sample Size: 32 breast cancers (4 images per case analyzed on each of five systems).
Key Results: (Mean values across different microscopes for %Pos and Score studies)
- n: 32 for all tests
- Corr Coef: Ranged from 0.964 to 0.999 for %Pos and 0.962 to 0.989 for Score.
- Slope (m): Ranged from 0.930 to 1.081 for %Pos and 0.952 to 1.065 for Score.
- Intercept (b): Ranged from -6.125 to 3.481 for %Pos and -0.027 to 0.058 for Score.
- SE: Ranged from 4.814 to 7.868 for %Pos and 0.113 to 0.209 for Score.
QCA Within-Image Reproducibility Study
Study Type: Repeated capture of an individual microscopic field.
Sample Size: Ten different breast cancer cases/slides; each field was repeatedly captured 10 times.
Key Results: Every result within each set of 10 images was absolutely identical with respect to QCA ER score and percentage positivity (data not shown).
Key Metrics (Sensitivity, Specificity, PPV, NPV, etc.)
Not Found.
Predicate Device(s)
Reference Device(s)
Not Found.
Predetermined Change Control Plan (PCCP) - All Relevant Information
Not Found.
§ 864.1860 Immunohistochemistry reagents and kits.
(a)
Identification. Immunohistochemistry test systems (IHC's) are in vitro diagnostic devices consisting of polyclonal or monoclonal antibodies labeled with directions for use and performance claims, which may be packaged with ancillary reagents in kits. Their intended use is to identify, by immunological techniques, antigens in tissues or cytologic specimens. Similar devices intended for use with flow cytometry devices are not considered IHC's.(b)
Classification of immunohistochemistry devices. (1) Class I (general controls). Except as described in paragraphs (b)(2) and (b)(3) of this section, these devices are exempt from the premarket notification requirements in part 807, subpart E of this chapter. This exemption applies to IHC's that provide the pathologist with adjunctive diagnostic information that may be incorporated into the pathologist's report, but that is not ordinarily reported to the clinician as an independent finding. These IHC's are used after the primary diagnosis of tumor (neoplasm) has been made by conventional histopathology using nonimmunologic histochemical stains, such as hematoxylin and eosin. Examples of class I IHC's are differentiation markers that are used as adjunctive tests to subclassify tumors, such as keratin.(2) Class II (special control, guidance document: “FDA Guidance for Submission of Immunohistochemistry Applications to the FDA,” Center for Devices and Radiologic Health, 1998). These IHC's are intended for the detection and/or measurement of certain target analytes in order to provide prognostic or predictive data that are not directly confirmed by routine histopathologic internal and external control specimens. These IHC's provide the pathologist with information that is ordinarily reported as independent diagnostic information to the ordering clinician, and the claims associated with these data are widely accepted and supported by valid scientific evidence. Examples of class II IHC's are those intended for semiquantitative measurement of an analyte, such as hormone receptors in breast cancer.
(3) Class III (premarket approval). IHC's intended for any use not described in paragraphs (b)(1) or (b)(2) of this section.
(c)
Date of PMA or notice of completion of a PDP is required. As of May 28, 1976, an approval under section 515 of the Federal Food, Drug, and Cosmetic Act is required for any device described in paragraph (b)(3) of this section before this device may be commercially distributed. See § 864.3.
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Image /page/0/Picture/2 description: The image shows a semi-circle made of eight black dots. The dots are arranged in a curved pattern, resembling an incomplete circle. The dots are evenly spaced and of the same size. The semi-circle is oriented with the open end facing upwards.
This summary of 510(k) safety and effectiveness information is being submitted in accordance with the requirements of SMDA 1990 and 21 CFR 807.92.
Device Name
QCA (Version 3.1)
A videomicroscopy software system for quantitative estrogen receptor immunohistochemistry
Common Digital analyzer
Name
510(k) Number K031363
- Classification A new class II in vitro medical device MYA Hematology: Immunohistochemistry Antibody Assay, Estrogen Receptor 21 CFR 864.1860 Applicant Cell Analysis, Inc 1801 Maple Avenue
- Evanston, II 60201 United States of America
- Applicant Joel Herm Contact President 866-235-5442 joel.herm@cellanalysis.com
- Manufacturer Cell Analysis, Inc. 1801 Maple Avenue (single site) Evanston, II 60201 United States of America
Device Establishment Registration Number: 9052602
- Predicate Modification to ACIS (Automated Cellular Imaging System) K012138, September 30, 2002 Device ChromaVision Medical Systems, Inc. Capestrano, CA
Submission May 29, 2003 Date
1
Summary narrative
Immunohistochemistry special stains are often used by pathologists for many purposes. However, there is a need for objectivity in the assessment of such stains, as manual observation by individual pathologists suffers from subjectivity and inter-observer variability. With this need in mind, Cell Analysis, Inc. was founded to develop a quantitative cellular image analysis system entitled QCA. It is specifically designed to help pathologists make objective measurements of the estrogen receptor nuclear antigens visualized by immunohistochemistry (IHC). The system is essentially software that analyzes images captured by a pathologist through a video camera using the pathologist's own microscope and desktop computer. The system requires competent human intervention at all steps in the analysis process. After the pathologist chooses appropriate fields for analysis, enters necessary settings, and masks areas of non-tumor if desired, the system will automatically derive an overall score of the field of interest. Should the pathologist disagree with the score, s/he can adjust QCA settings so that the system derives a score that matches their professional assessment.
To determine substantial equivalence of the system to a predicate, QCA was compared against the stand-alone ChromaVision imaging system (ACIS) and against manual assessment by highly trained pathologists. The ChromaVision ACIS system constitutes an FDA-cleared Class II medical device with an almost identical intended use as Cell Analysis' QCA system. However, it should be understood that manual inspection of immunohistochemistry special stains remains the method of choice for this analysis in the vast majority of all pathology laboratories, and must therefore be considered the standard to which other systems should be compared.
The Cell Analysis QCA system is designed to analyze the estrogen receptor (ER) antigen, and for test purposes 32 breast cancers were chosen from archival material at Lake Forest Hospital and stained immunohistochemically for ER. Each of these 32 slides (and appropriate control slides) was analyzed by the Cell Analysis QCA system, the ChromaVision ACIS system, and manually by three highly trained pathologists. All assessments and analyses were made in blinded fashion. The correlations between the individual pathologists' manual results and the QCA results were all excellent.
Legally marketed predicate device and method to which substantial equivalence is claimed -807.92(a)(3)
Digital analyzer: ChromaVision Medical Systems, Inc's ACIS (Automated Cellular Imaging System) for detection of ER/PR found to be substantially equivalent on September 30, 2002 (KO12138)
Description of the device - 807.92(a)(4)
QCA is a standalone, automated intelligent cell assessment software device that analyzes digital images of cells of interest by pixel color attributes and pixel area detection algorithms. The software system utilizes a pathologist's own personal computer, light microscope, digital camera, printer, and Internet connection.
Image /page/1/Figure/10 description: The image shows a diagram of a pathologist's workflow using QCA software. The workflow starts with a pathologist's microscope with a camera, which is connected to a pathologist's PC with QCA software. The PC is connected to a monitor and printer, and it is also connected to the internet via a 128-bit SSL connection. The internet is connected to a firewall, which protects a web server running QCA software and a QCA database server.
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Image /page/2/Picture/21 description: The image shows a circular arrangement of eight black dots. The dots are evenly spaced and form an incomplete circle, with a small gap between the first and last dot. The dots are solid black and have a uniform size and shape. The overall impression is a simple, geometric design.
Intended Use - 807.92(a)(5)
The QCA device is intended to detect and classify cells of clinical interest based on recognition of cellular areas of particular color and chromatic intensity. In this software application, the QCA device is intended to measure and quantitate the percentage and intensity of positively stained nuclei in formalinfixed, paraffin-embedded tissue specimens immunohistochemically stained for estrogen receptors.
It is indicated for use as an aid in the management, prognosis and prediction of therapy outcomes of breast cancer when used with reagents validated for those indications.
The QCA system is an adjunctive computer-assisted methodology to assist the reproducibility of a qualified pathologist in the acquisition and measurement of images from microscopic slides of breast cancer specimens stained for the presence of estrogen (ER) nuclear receptor protein. The accuracy of the test result depends upon the quality of immunohistochemical staining. It is the responsibility of a qualified pathologist to employ appropriate morphological studies and controls to assure the validity of the QCA ER scores.
Technological characteristics - 807.92(a)(6)
The method of cell assessment is similar to the predicate device, i.e., colorimetric pattern recognition by microscopic examination of digital images of prepared cells by chroma (hue and intensity), and histologic area as observed by a pathologist-controlled microscope/digital camera combination. Assessment algorithms have been designed to mimic visual observations by highly trained health care professionals.
Non-clinical Study Outline
- 32 invasive breast carcinoma tissue specimens with a range of ER positivity/negativity were .. selected from different patients.
- Tissue blocks were sent to an outside CLIA-approved lab
- Outside lab performed IHC for ER on all 32 cases following predicate device's specifications
- . Outside lab pathologists used predicate device to derive percent positivity.
- . Predicate device results were kept blind
- Outside lab returns all 32 IHC slides to Cell Analysis.
- . Based on professional judgment acquired through pathology training and experience, two pathologists captured 3 representative images from each case (2 * 3 * 32 = 192)
- . Three different pathologists performed independent manual inspection and derived scores for 192 randomly mixed images
- . Manual inspection results were kept blind
- . One of the three above-mentioned pathologists used the candidate device (QCA) to analyze the same 192 images without manually overriding the program's scores
- All results were un-blinded and data from predicate device, manual inspections, and QCA were compared
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Image /page/3/Picture/14 description: The image shows a circular arrangement of eight black dots. The dots are evenly spaced and form an incomplete circle, with a small gap between the last and first dot. The dots are solid and have a uniform size and shape.
Performance Characteristics
For all comparison studies the primary estrogen receptor antibody used was the DakoCytomation 1D5 clone (FDA 510(K) cleared). The detection system was the labeled Streptavidin-Biotin peroxidase system (LSAB2), also purchased from DakoCytomation Corporation. Please see Appendix on page 9 of this Summary for the immunohistochemistry staining protocol used in all studies of this submission.
QCA ER Percent Positivity vs. Manual Percent Positivity Evaluation
Manual evaluation: As manual inspection of IHC slides remains the most widely utilized method by a wide margin*, therefore this must be considered the standard of current pathology practice. However, it is also recognized that manual inspection suffers from considerable inter-observer variability.
QCA chose tissue specimens from 32 consecutive invasive breast cancers received in a pathology practice over a three and a half month period. Based on professional judgment, three representative images of each ER slide were digitally captured by each of two pathologists. These 192 different images (3 images x 2 pathologists x 32 cases = 192 images) were then first randomly mixed and then screened by each of three different pathologists to ensure blinding of results. The three then manually assessed the percentage of tumor cell nuclei with weak positive ER IHC staining (% weak positivity), the percentage of turnor cell nuclerate positive staining (% moderate positivity), and the percentage of tumor cell nuclei with strong staining (% strong positivity) for each slide. From these determinations, a total percentage of tumor cell nuclei with any degree of positivity (% total positivity) was calculated for each slide.
(% total positivity) = (% weak positivity) + (% moderate positivity) + (% strong positivity)
A completely ER-negative tumor was scored as 0%, and a tumor showing any degree of positive ER staining of all tumor cells (regardless whether the staining is weak, moderate, or strong) was scored as 100%.
QCA evaluation: The same 192 images were then assessed with the QCA software by one pathologist without any manual adjustments of the nuclear thresholds. The pathologist did mask nine of the images to exclude areas of non-tumorous cells.
Different from the manual study, instead of counting the percent of positively stained nuclei, QCA software evaluates individual "nuclear pixels" and automatically assigns a staining intensity score 0. 1. 2, or 3 to each pixel. Each pixel's individual score is automatically determined based on the negative control and positive control provided by the pathologist at the beginning of the testing. Any degree of staining above the negative control will be assigned by QCA as a "positive" pixel. QCA will calculate the "% weak positivity" (as the number of weakly stained pixels against the total number of nuclear pixels), % moderate positivity, and % strong positivity. Using the same formula, the total percent of positively stained pixels (% total positivity) can be calculated as follows: (% total positivity) = (% weak positivity) + (% moderate positivity) + (% strong positivity).
Regression analysis was performed by using individual pathologist's (manually assessed positively stained nuclei) manual ER percent positivity aqainst QCA's (nuclear pixel) ER percent positivity. The results of three pathologists are shown on the next page.
- Layfield LJ, Gupta D, Mooney EE. Assessment of Tissue Estrogen and Progesterone Receptor Levels: A Survey of Current Practice, Techniques, and Quantitation Methods. Breast J. 2000; 6:189-196.
4
QCA 510(k) Submission 510(k) Summary
Image /page/4/Figure/1 description: This image is a scatter plot comparing QCA ER % Positivity and Pathologist #1 ER % Positivity. The x-axis represents Pathologist #1 ER % Positivity, ranging from 0 to 100. The y-axis represents QCA ER % Positivity, also ranging from 0 to 100. There are several data points scattered across the plot, with a few trend lines running through the data.
Image /page/4/Figure/2 description: This image shows a legend for a plot. The legend indicates that a solid black line represents the regression line. The area between two dashed black lines represents the 95% confidence level. The solid black square represents the line X=Y.
Pathologist #1
Corr Coef (R) =0.957 Slope = 0.92 Intercept = 6.18 SE of regression line = 7.09 N=192
Image /page/4/Figure/5 description: The image is a scatter plot comparing QCA ER % Pos on the y-axis and Pathologist #2 ER % Pos on the x-axis. The x and y axis range from 0 to 100. There is a strong positive correlation between the two variables, as indicated by the points clustering around the regression line. The regression line and confidence intervals are also plotted on the scatter plot.
Pathologist #2
Corr Coef (R) =0.934 Slope = 0.97 Intercept = 0.15 SE of regression line = 8.81 N=192
Image /page/4/Figure/8 description: The image is a scatter plot comparing QCA ER % Pos on the y-axis and Pathologist #3 ER % Pos on the x-axis. The x and y axis both range from 0 to 100. There is a strong positive correlation between the two variables, with most of the data points clustered around a straight line. There are also three lines of best fit shown on the scatter plot.
Pathologist #3
Corr Coef (R) =0.925 Slope = 0.92 Intercept = 4.62 SE of regression line = 7.36 N=192
5
QCA 510(k) Submission
510(k) Summary
QCA ER Score vs. Manual Score Evaluation
Using the same 32 consecutive invasive breast cancer slides mentioned in the outline, a different Osing the same of tonodoulve incorporates the intensity of the ER staining, the intensity score, was scornig system that additionally intorperation method (Manual ER Score) and by QCA software (QCA also generated by the same management monulated using the same formula: Intensity Score EN SCOC). Doth manad and QCP orsele positivity x 2) + (% strong positivity x 3)} / 100%. As =( // weak positivity x 1) · ( x modelate plei based and QCA is pixel based. This Intensity Score is montoned above, the manual soncept of HSCORE*, which is currently used in many pathology laboratories for ER scoring.
Image /page/5/Figure/4 description: The image contains two scatter plots comparing QCA ER scores with pathologist ER scores. The first plot, labeled "Pathologist #1", shows a correlation coefficient of 0.849, a slope of 0.98, an intercept of -0.01, a standard error of regression line of 0.37, and a sample size of 192. The second plot, labeled "Pathologist #2", shows a correlation coefficient of 0.854, a slope of 0.92, an intercept of -0.02, a standard error of regression line of 0.36, and a sample size of 192.
- HSCORE = Σ (l + 1) × PC, where I and PC represent the intensity and the percentage of cells that stained at each positive intensity category, respectively. (McCarty KS Jr., et al. Cancer Res. 1986;46(8 Suppl):4244s-4248s.)
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QCA 510(k) Submission 510(k) Summary
Image /page/6/Figure/1 description: This image is a scatter plot comparing QCA ER scores to Pathologist #3 ER scores. The x-axis represents the Pathologist #3 ER Score, ranging from 0.0 to 3.0, while the y-axis represents the QCA ER Score, also ranging from 0.0 to 3.0. The plot shows a positive correlation between the two scores, with data points scattered around a regression line. There are also two lines above and below the regression line.
QCA ER Percent Positivity vs. Predicate Device ER Percent Positivity Evaluation
We performed regression analysis comparing the predicate device results to those of QCA for percent positivity. The predicate device's percent positivity values on 32 cases were provided by a CLIApositive. The productions as case (slide-by-slide) basis only. The values were provided in 10% increments on 31 cases, one case was reported at 5%. The QCA percent positivity was the cumulative inoremont by QCA of all 6 images taken of each of the same 32 cases. The following figure shows the regression results of the predicate device's ER percent positivity against QCA's ER percent positivity. The regression statistics are shown in the legend.
Image /page/6/Figure/4 description: This image is a scatter plot that compares the QCA ER % Pos to the Predicate Device's ER % Pos. The plot includes a regression line, 95% confidence level lines, and a line where X=Y. The correlation coefficient (R) is 0.897, the slope is 0.88, the intercept is 21.3, the standard error of the regression line is 11.8, and the sample size (n) is 32.
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Image /page/7/Picture/1 description: The image shows a circular arrangement of eight black dots. The dots are evenly spaced and form an incomplete circle, with a small gap between the first and last dot. The dots are solid and have a uniform size and shape. The overall impression is a simple, geometric design.
Qualitative Percent Positivity Comparison Study
The following agreement tables include the data from the original 32 invasive breast carcinomas (as The rollowing agreement (abled more, 6 images taken per case/slide) and an additional 120 described in the Outline, page of the our determination of the optimum number of images to consider per case study). These cases include both invasive and in-situ breast cancers that were orocessed and stained according to the protocol listed in the Appendix. The QCA final percent positivity for each of the 152 (32 + 120) cases/slides was calculated based on the cumulative poolthity of all tumor cell nuclear pixels taken from each case (see QCA Evaluation, page 4 above). The manual percent positivity for each of the 152 total cases was calculated based on the same f rro nambal peroom position). Interpretations of positive breast tumor ER status vary from 1% to 10% of percent positivity in different pathology laboratories (see reference by Layfield LJ. page 4). We used ≥5.0% and ≥1.0% positivity as example cut-off values, and derived the following qualitative agreement tables to compare the manual against the QCA methods.
| 1.0%>Positive | Manual | ||
|---|---|---|---|
| Positive | Negative | ||
| QCA | Positive | 149 | 0 |
| Negative | 0 | 3 |
Inter-microscope Variability Study
The QCA system was installed in 5 different pathologists' offices, one with an Olympus BX50 microscope, another with an Olympus BH-2 microscope, another with a Nikon Labophot-2 microscope, another with a Reichert Micro Star IV microscope, and the last with a Zeiss Axiostar Plus microscope. Having previously shown that four images per case yield results within one standard deviation of the true mean for QCA score and percent positivity, four images of each of the 32 breast cancers were captured and analyzed on each of the five systems. For each case, appropriate negative and positive controls were also captured. As described on page 4 (QCA evaluation), the final QCA score and percent positivity for each case/slide is the cumulative average of 4 images taken for each case. The next two figures show the regression results of QCA ER score and QCA percent positivity against those of the manual results.
Image /page/7/Figure/7 description: The image contains two scatter plots comparing QCA ER scores and QCA % ER positivity across different microscopes. The left plot shows QCA ER score versus manual ER score, with data points clustered around a diagonal line, indicating a positive correlation. The right plot shows QCA % ER positivity versus manual % ER positivity, with a similar positive correlation and data points ranging from 0 to 100 on both axes. Both plots include regression lines for different microscope models, such as Olympus BX50 and Nikon Labophot-2.
8
QCA 510(k) Submission 510(k) Summary
| BX50 | BH2 | Labophot | Microstar | Axiostar | ||||||
|---|---|---|---|---|---|---|---|---|---|---|
| %Pos | Score | %Pos | Score | %Pos | Score | %Pos | Score | %Pos | Score | |
| n | 32 | 32 | 32 | 32 | 32 | 32 | 32 | 32 | 32 | 32 |
| Corr Coef | 0.976 | 0.980 | 0.988 | 0.989 | 0.982 | 0.980 | 0.964 | 0.962 | 0.980 | 0.977 |
| Slope (m) | 1.081 | 1.065 | 1.018 | 0.984 | 0.999 | 0.963 | 0.930 | 0.952 | 0.972 | 1.037 |
| m low 95% | 0.991 | 0.983 | 0.959 | 0.929 | 0.927 | 0.891 | 0.834 | 0.852 | 0.899 | 0.953 |
| m high 95% | 1.171 | 1.146 | 1.077 | 1.038 | 1.071 | 1.035 | 1.026 | 1.053 | 1.046 | 1.121 |
| Intercept (b) | -6.125 | -0.015 | 1.634 | -0.016 | 1.831 | 0.058 | 3.481 | -0.027 | -0.822 | 0.001 |
| b low 95% | -13.134 | -0.142 | -2.969 | -0.101 | -3.830 | -0.054 | -4.042 | -0.183 | -6.553 | -0.129 |
| b high 95% | 0.884 | 0.111 | 6.237 | 0.068 | 7.492 | 0.170 | 11.005 | 0.128 | 4.910 | 0.131 |
| SE | 7.331 | 0.169 | 4.814 | 0.113 | 5.920 | 0.150 | 7.868 | 0.209 | 5.994 | 0.174 |
QCA Within-Image Reproducibility Study
To document the within-image reproducibility of the QCA system, ten different breast cancer cases/slides that had been subjected to the same ER antibody staining protocol (as mentioned below in the Appendix) were chosen to perform the following reproducibility study.
An individual microscopic field from each of ten different slides was repeatedly captured 10 times using the QCA system. Every result within each set of 10 images was absolutely identical with respect to QCA ER score and percentage positivity (data not shown). This experimental design tested the reproducibility of the microscope/camera systems as well as that of the software itself.
Performance Data Conclusions
The QCA system provided an objective measure at least equal to the manual inspection of the individual pathologists and was substantially equivalent to the predicate device.
Appendix:
The immunohistochemistry staining procedure used in all studies for this submission.
- Formalin-fixed, paraffin-embedded breast tumor tissue blocks were sectioned at 5 microns in 1. thickness.
- These tissue sections were affixed onto glass slides by baking in a dry oven at 60°C for 30 2. minutes.
- The slides were de-paraffinized through xylene and hydrated through 100%, 95% and 70% 3. ethyl alcohol then finally in distilled water.
- Antigen retrieval was achieved by immersing slides in a jar with 1mM EDTA pH7.5 solution. 4. This jar was placed in a steamer and steamed for 30 minutes. It was then allowed to cool for 20 minutes.
- Slides were immersed in 3% hydrogen peroxide and protein blocking solution 5. (DakoCytomation) for 10 minutes each to block the non-specific antigen binding sites and to neutralize the endogenous peroxidase activity.
- The slides were incubated with DakoCytomation 1D5 ER monoclonal antibody (1/25 dilution) at ം. room temperature for 30 minutes.
- These slides were then incubated with biotinylated secondary antibody for 30 minutes 7.
- The slides were then incubated with streptavidin-horseradish peroxidase conjugate for 30 8. mintures
- 3.3' diamino-benzidine (DAB) Chromogen was added and allowed to develop color for 5 ത mintutes.
-
- The slides were counter-stained with Gill 3 hematoxylin for 5 minutes.
-
- Slides were dehydrated and coverslipped.
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Image /page/9/Picture/1 description: The image shows the logo for the Department of Health & Human Services USA. The logo features a stylized eagle with its wings spread, symbolizing protection and care. The text "DEPARTMENT OF HEALTH & HUMAN SERVICES USA" is arranged in a circular pattern around the eagle, emphasizing the department's role and affiliation with the United States.
Food and Drug Administration 2098 Gaither Road Rockville MD 20850
Mr. Joel Herm President Cell Analysis, Inc. 1801 Maple Avenue Suite 2319 Evanston, Illinois 60201-3135
FEB - 5 2004
Re: K031363 Trade/Device Name: OCA (Quantitative Cellular Assessment) Regulation Number: 21 CFR § 864.1860 Regulation Name: Immunohistochemistry reagents and Kits Regulatory Class: II Product Code: NQN Dated: November 6, 2003 Received: November 10, 2003
Dear Mr. Herm:
We have reviewed your Section 510(k) premarket notification of intent to market the device referenced above and have determined the device is substantially equivalent (for the indications for use stated in the enclosure) to legally marketed predicate devices marketed in interstate commerce prior to May 28, 1976, the enactment date of the Medical Device Amendments, or to devices that have been reclassified in accordance with the provisions of the Fedcral Food, Drug, and Cosmetic Act (Act) that do not require approval of a premarket approval application (PMA). You may, therefore, market the device, subject to the general controls provisions of the Act. The general controls provisions of the Act include requirements for annual registration, listing of devices, good manufacturing practice, labeling, and prohibitions against misbranding and adulteration.
If your device is classified (see above) into either class II (Special Controls) or class III (PMA), it may be subject to such additional controls. Existing major regulations affecting your device can be found in Title 21, Code of Federal Regulations (CFR), Parts 800 to 895. In addition, FDA may publish further announcements concerning your device in the Federal Register.
Please be advised that FDA's issuance of a substantial equivalence determination does not mean that FDA has made a determination that your device complies with other requirements of the Act or any Federal statutes and regulations administered by other Federal agencies. You must comply with all the Act's requirements, including, but not limited to: registration and listing (21 CFR Part 807); labeling (21 CFR Parts 801 and 809); and good manufacturing practice requirements as set forth in the quality systems (QS) regulation (21 CFR Part 820). This letter will allow you to begin marketing your device as described in your Section 510(k) premarket notification. The I'DA finding of substantial equivalence of your device to a legally marketed predicate device results in a classification for your device and thus, permits your device to procced to the market.
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If you desire specific information about the application of labeling requirements to your device, or questions on the promotion and advertising of your device, please contact the Office of In Vitro Diagnostic Device Evaluation and Safety at (301) 594-3084. Also, please note the regulation entitled, "Misbranding by reference to premarket notification" (21CFR Part 807.97). You may obtain other general information on your responsibilities under the Act from the Division of Small Manufacturers, International and Consumer Assistance at its toll-free number (800) 638-2041 or (301) 443-6597 or at its Internet address http://www.fda.gov/cdrh/dsma/dsmamain.html.
Sincerely yours,
Joseph L. Archet
Joseph L. Hackett, Ph.D. Acting Director Division of Immunology and Hematology Devices Office of In Vitro Diagnostic Device Evaluation and Safety Center for Devices and Radiological Health
Enclosure
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QCA 510(k) Submission Intended Use
510(k) Number: K031363
Device Name: QCA
Indications for Use
The QCA device is intended to detect and classify cells of clinical interest based on recognition of cellular areas of particular color and chromatic intensity. In this software application, the QCA device is intended to measure and quantitate the percentage and intensity of positively stained nuclei in formalin-fixed, paraffin-embedded tissue specimens immunohistochemically stained for estrogen receptors.
It is indicated for use as an aid in the management, prognosis and prediction of therapy outcomes of breast cancer when used with reagents validated for those indications.
The QCA system is an adjunctive computer-assisted methodology to assist the reproducibility of a qualified pathologist in the acquisition and measurement of images from microscopic slides of breast cancer specimens stained for the presence of estrogen (ER) nuclear receptor protein. The accuracy of the test result depends upon the quality of immunohistochemical staining. It is the responsibility of a qualified pathologist to employ appropriate morphological studies and controls to assure the validity of the QCA ER scores.
im Chan
Division Sign-Off
Office of In Vitro Diagnostic Device Evaluation and Safety
510(k)________________________________________________________________________________________________________________________________________________________________________
(Please do not write below this line - Continue on another page if necessary)
Concurrence of CDRH, Office of Device Evaluation (ODE)
Prescription Use
(Per 21 CFR 801.109) ✓
Or
Over-the-Counter Use