Method comparison study: 1200 PBS slides analyzed by 6 investigators
6 (investigators)
Indications for Use
The X100/X100HT with Full Field Peripheral Blood Smear Application is intended to locate and display images of white cells, red cells, and platelets acquired from fixed and stained peripheral blood smears and assists a qualified technologist in conducting a WBC differential, RBC morphology evaluation, and platelet estimate using those images. For in-vitro diagnostic use only. For professional use only.
Device Story
Digital cell morphology solution; captures high-resolution images of fixed/stained peripheral blood smears without immersion oil. System automatically locates/presents images of WBCs, RBCs, and platelets. Workflow includes full field review, WBC differential, RBC morphology evaluation, and platelet estimate. New Decision Support System (DSS) provides suggested RBC morphological pre-gradings and platelet clump indications via dotted-line overlays. User must review, confirm, or adjust all system suggestions; final grading/reporting remains manual. Used in clinical laboratories by trained technologists. Benefits include streamlined review process and standardized cell visualization; assists in clinical decision-making by providing pre-classified/pre-graded data for final verification.
Clinical Evidence
Performance evaluated via multi-center method comparison study (1200 slides) across three sites. Compared results of trained examiners using the device with and without DSS. Metrics included PPA, NPA, and overall agreement for 23 RBC morphological features and platelet clumping. Overall agreement for categories ranged from 87.08% (PLT Clumping) to 97.90% (RBC Inclusions). Supplemental study (75 slides) compared DSS schistocyte detection against manual light microscopy, showing 82.67% overall agreement. Precision/reproducibility studies (2160 scans) met 80% acceptance criteria.
Technological Characteristics
Hardware: Digital scanner (X100/X100HT) and processing unit. Imaging: Automated scan, multi-illumination, 100X magnification reconstruction without immersion oil. Analysis: Automated cell-locating device (21 CFR 864.5260). Software: Includes DSS for RBC morphology and platelet clump detection. Calibration: Mechanical/optical calibration verified by technician. Standards: Complies with CLSI EP05-A3, EP12-A2, EP17-A2, IEC 62471, ISO 14971, UL 61010-1, IEC 62304, and IEC 62366-1.
Indications for Use
Indicated for professional use by qualified technologists to assist in WBC differential, RBC morphology evaluation, and platelet estimation from fixed and stained peripheral blood smears.
Regulatory Classification
Identification
An automated cell-locating device is a device used to locate blood cells on a peripheral blood smear, allowing the operator to identify and classify each cell according to type. (Peripheral blood is blood circulating in one of the body's extremities, such as the arm.)
Predicate Devices
X100 with Full Field Peripheral Blood Smear (PBS) Application (K201301)
X100HT with Slide Loader with Full Field Peripheral Blood Smear (PBS) Application (K220013)
Submission Summary (Full Text)
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FDA
U.S. FOOD & DRUG
ADMINISTRATION
# 510(k) SUBSTANTIAL EQUIVALENCE DETERMINATION DECISION SUMMARY
INSTRUMENT ONLY
## I Background Information:
A 510(k) Number
K243144
B Applicant
Scopio Labs Ltd.
C Proprietary and Established Names
X100 with Full Field Peripheral Blood Smear (PBS) Application
X100HT with Full Field Peripheral Blood Smear (PBS) Application
D Regulatory Information
| Product Code(s) | Classification | Regulation Section | Panel |
| --- | --- | --- | --- |
| JOY | Class II | 21 CFR 864.5260 - Automated Cell-Locating Device | HE - Hematology |
## II Submission/Device Overview:
A Purpose for Submission:
This submission is for the addition of a Decision Support System (DSS) to support the user's review of red blood cell (RBC) morphology and platelet clumps.
B Type of Test:
White blood cell (WBC) differential, red blood cell (RBC) morphology evaluation and platelet estimation
## III Intended Use/Indications for Use:
A Intended Use(s):
See Indications for Use below.
Food and Drug Administration
10903 New Hampshire Avenue
Silver Spring, MD 20993-0002
www.fda.gov
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B Indication(s) for Use:
The X100/X100HT with Full Field Peripheral Blood Smear Application is intended to locate and display images of white cells, red cells, and platelets acquired from fixed and stained peripheral blood smears and assists a qualified technologist in conducting a WBC differential, RBC morphology evaluation, and platelet estimate using those images. For in-vitro diagnostic use only. For professional use only.
C Special Conditions for Use Statement(s):
Rx - For Prescription Use Only
IV Device/System Characteristics:
A Device Description:
The X100/X100HT with Full Field Peripheral Blood Smear (PBS) Application (“Full Field PBS”) automatically locates and presents images of blood cells on peripheral blood smears. The user browses through the imaged smear to gain a high-level general impression. The user reviews the suggested classification of each white cell according to type and may manually change the suggested classification of any cell. The user reviews and may manually change the suggested platelet estimation as well. In this modified version, a decision support system (DSS) has been added to support the user’s review of red blood cell (RBC) morphology and platelet clumps. The DSS’s recommendations are presented to the user by means of a dotted line around the grade or parameter suggested by the DSS. The user is instructed to review the DSS’s suggestions and must actively mark the appropriate selection.
The device consists of two main hardware components: the digital scanner (X100/X100HT) and the processing unit.
The RBC analysis starts from the center of the monolayer, detecting non-overlapping RBCs at a single region at a time, moving outward in a spiral to analyze additional regions. The analysis process includes two steps – the first step keeps analyzing regions until 10,000 non-overlapping RBCs are detected. These cells are then assigned morphological labels. The final grading is set by converting the morphology percentages of the analyzed cells into grades using the default thresholds recommended by the International Council for Standardization in Hematology (ICSH), that can be modified by the lab director.
The platelet clumps detection analyzes the entire monolayer and feathered edge regions of the scan to identify platelet clumps.
B Instrument Description Information:
1. Instrument Name(s):
X100 with Full Field Peripheral Blood Smear (PBS) Application
X100HT with Full Field Peripheral Blood Smear (PBS) Application
2. Specimen Identification:
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The slide's barcode is captured automatically and assigned to each case. The device also supports typing the barcode manually.
3. Specimen Sampling and Handling:
A peripheral blood sample collected in K₂EDTA or K₃EDTA tubes is mixed manually or automatically. A thin blood film is wedged on a clean dry glass slide (a blood smear) and stained with Romanowsky stain. After the staining process is completed, the slide is covered using any standard cover slipping method.
4. Calibration:
The Full Field PBS system requires initial calibration for its mechanical and optical performances. An initial calibration process is performed on a standard blood smear slide as part of the manufacturing process of the device. The calibration is verified after installation by a technician or a qualified operator. Calibration can also be performed if a problem arises in the daily QC testing.
5. Quality Control:
The daily QC involves testing a standard blood smear slide to verify image quality. During the daily QC the user reviews the images received from the Full Field PBS and verifies that at least 95% of the WBCs in the scanned image were identified and located correctly by the system.
V Substantial Equivalence Information:
A Predicate Device Name(s):
X100 with Full Field Peripheral Blood Smear (PBS) Application, X100HT with Slide Loader with Full Field Peripheral Blood Smear (PBS) Application
B Predicate 510(k) Number(s):
K201301, K220013
C Comparison with Predicate(s):
| Device & Predicate Device(s): | K243144 | K201301 | K220013 |
| --- | --- | --- | --- |
| Device Trade Name | X100/X100HT with Full Field Peripheral Blood Smear Application | X100 with Full Field Peripheral Blood Smear (PBS) Application | X100HT with Full Field Peripheral Blood Smear (PBS) Application |
| General Device Characteristic Similarities | | | |
| Intended Use/Indications For Use | The X100/X100HT with Full Field Peripheral Blood Smear Application is intended | Same | Same |
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| | to locate and display images of white cells, red cells, and platelets acquired from fixed and stained peripheral blood smears and assists a qualified technologist in conducting a WBC differential, RBC morphology evaluation, and platelet estimate using those images. For in vitro diagnostic use only. For professional use only. | | |
| --- | --- | --- | --- |
| Intended User | Skilled users, trained in the use of the device and in the identification of blood cells. | Same | Same |
| Sample Type | Stained blood film glass slides of peripheral whole blood | Same | Same |
| Sample Preparation | Romanowsky stain | Same | Same |
| Analysis Technique: White Blood Cells | WBCs are located/counted by moving according to the battlement pattern (ensuring that each cell is counted only once). Cell images are analyzed using standard mathematical methods, including deterministic artificial neural networks (ANN's) trained to distinguish between classes of white blood cells. The cell images are pre-classified, and the user reviews the suggested classification, and accepts or reclassifies the images. | Same | Same |
| Analysis Technique: Platelets estimation | Platelets are located/counted by moving according to the | Same | Same |
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| | battlement pattern (ensuring that each cell is counted only once). Cell images are analyzed using standard mathematical methods, including deterministic artificial neural networks (ANN's) trained to detect platelets. The user reviews the suggested estimate of the platelet concentration and accepts or modifies the result. | | |
| --- | --- | --- | --- |
| Quality Control | The daily QC involves testing a standard blood smear slide. During the daily QC the user reviews the images received from the Full Field PBS and verifies that at least 95% of the WBCs in the scanned image were identified and located correctly by the system. | Same | Same |
| High-Resolution Image Acquisition | Fully automated scan and image acquisition. Captures multiple images under plurality of illumination conditions and reconstructs a 100X magnification image of the viewed area, without the need for immersion oil. | Same | Same |
| General Device Characteristic Differences | | | |
| Analysis Technique: Red Blood Cells | The device presents an overview image to be reviewed by the user. The system presents to the user a dotted line around RBC | The device presents an overview image to be reviewed by the user. The examiner manually grades RBC morphology from the | The device presents an overview image to be reviewed by the user. The examiner manually grades RBC morphology from the |
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| | morphology grading suggestions. The examiner manually grades RBC morphology from the image. | image. | image. |
| --- | --- | --- | --- |
| Analysis Technique: Platelets Clump presence | The device presents an overview image to be reviewed by the user. The system presents to the user a dotted line around a suggestion whether platelet clump was detected. The examiner manually marks if platelet clumps are present in the smear. | The device presents an overview image to be reviewed by the user. The examiner manually marks if platelet clumps are present in the smear. | The device presents an overview image to be reviewed by the user. The examiner manually marks if platelet clumps are present in the smear. |
VI Standards/Guidance Documents Referenced:
- CLSI EP05-A3: Evaluation of Precision of Quantitative Measurement Procedures; Approved Guideline - Third Edition
- CLSI EP12-A2: User Protocol for Evaluation of Qualitative Test Performance; Approved Guideline - Second Edition
- CLSI EP17-A2: Evaluation of Detection Capability for Clinical Laboratory Measurement Procedures; Approved Guideline - Second Edition
- IEC 62471 First edition 2006-07 Photobiological safety of lamps and lamp systems
- ANSI AAMI ISO 14971:2019 Medical Devices – Applications of risk management to medical devices
- ANSI UL 61010-1 3rd Ed 2012-05-12 Standard for Safety for Electrical Equipment for Measurement Control and Laboratory Use
- ANSI AAMI IEC 62304:2006/A1:2016 Medical device software – Software life cycle processes
- ANSI AAMI IEC 62366-1:2015+AMDI:2020 Medical devices Part 1: Application of usability engineering to medical devices
VII Performance Characteristics (if/when applicable):
A Analytical Performance:
1. Precision/Reproducibility:
**Repeatability**
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Repeatability was conducted at three (3) clinical sites – two (2) US sites and one (1) OUS site, using 27 test samples representing different RBC morphological features as well as platelet clumping. Over the course of 20 testing days, two (2) daily runs were performed using two (2) replicates. The selected samples represented 23 morphological features in different grading levels. In total, 2160 scans were performed. The DSS suggestions from the scans were compared to the assigned reference grades as performed by laboratory professionals. The rate of agreement was calculated for each sample and each morphological feature separately, and each of the rate of agreement results was compared separately to a predefined acceptance criterion of 80%. All results met the pre-defined acceptance criteria.
| Morphological Feature | Mean Agreement |
| --- | --- |
| Acanthocytes | 99% |
| Anisocytosis | 99% |
| Basophilic stippling | 98% |
| Bite cells | 98% |
| Blister cells | 98% |
| Echinocytes | 98% |
| Elliptocytes | 100% |
| Helmet cells | 99% |
| Howell-Jolly bodies | 98% |
| Hypochromia | 96% |
| Macrocytes | 100% |
| Micro-organisms | 100% |
| Microcytes | 100% |
| Ovalocytes | 99% |
| Pappenheimer bodies | 98% |
| Poikilocytosis | 97% |
| Polychromasia | 97% |
| Schistocytes | 99% |
| Sickle cells | 100% |
| Spherocytes | 98% |
| Stomatocytes | 100% |
| Target cells | 99% |
| Teardrop cells | 99% |
| Platelet clumps | 95% |
## Reproducibility
Reproducibility was performed using 16 test samples across three (3) clinical sites, two (2) US sites and one (1) OUS site, with the test samples representing different RBC morphological features as well as platelet clumping. The study was conducted over five (5) testing days with five (5) replicates per day on three (3) devices. All results met the predefined acceptance criteria of 80%.
| Morphological Feature | Mean Agreement |
| --- | --- |
| Acanthocytes | 99% |
| Anisocytosis | 99% |
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| Morphological Feature | Mean Agreement |
| --- | --- |
| Basophilic stippling | 97% |
| Bite cells | 97% |
| Blister cells | 100% |
| Echinocytes | 97% |
| Elliptocytes | 99% |
| Helmet cells | 99% |
| Howell-Jolly bodies | 97% |
| Hypochromia | 95% |
| Macrocytes | 99% |
| Micro-organisms | 99% |
| Microcytes | 100% |
| Ovalocytes | 98% |
| Pappenheimer bodies | 97% |
| Poikilocytosis | 97% |
| Polychromasia | 96% |
| Schistocytes | 99% |
| Sickle cells | 99% |
| Spherocytes | 99% |
| Stomatocytes | 100% |
| Target cells | 99% |
| Teardrop cells | 99% |
| Platelet clumps | 96% |
2. Linearity:
Not applicable.
3. Analytical Specificity/Interference:
Not applicable.
4. Accuracy (Instrument):
## Method Comparison
A method comparison study was conducted to compare the results achieved by trained examiners using the X100 with Full Field Peripheral Blood Smear (PBS) Application with the RBC and Platelet Clump Decision Support System (DSS) and without the RBC and Platelet Clump Decision Support System (DSS). A total of 1200 PBS slides were prepared, each from a different blood sample, from three (3) clinical sites – two (2) US sites and one (1) OUS site, representing RBC morphological features in different grading levels as well as platelet clumping. These samples were collected during routine laboratory workflow of the three sites, represented the range of clinical conditions expected in the target population, and were randomly assigned to the investigators at each site. The samples were split between six (6) investigators (200 samples per investigator) and analyzed in two (2) methods (reference
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and test arms). First, in the reference arm, the samples were assessed using the previously cleared version of the application without DSS assistance. After a three-week washout period, sample anonymization and randomization, the investigators analyzed the same samples in the test arm, using the modified version of the Full Field PBS Application, with DSS suggestions presented to investigators for RBC morphology and platelet clumping. In both arms of the study, the qualified users were provided with a full field scan of their assigned samples, graded the same 23 RBC morphological features according to a predefined 4-graded scale, and evaluated the presence of platelet clumps in each sample. The same images were reviewed with and without the newly introduced DSS for RBC morphological features and indications concerning platelet clump presence. A washout period of three (3) weeks took place between finishing one study arm and starting the second.
The results were evaluated according to the categories of morphological features (RBC color, RBC inclusions, RBC shape, RBC size, PLT Clumping) with acceptance criteria applied for each category and each predictive value separately, including 95% confidence intervals measured using 1000 bootstrap iterations. All RBC categories and platelet clumping met the pre-defined acceptance criteria of 80% for overall agreement, PPA and NPA.
## Multi-Center Performance by Morphological Features – All Sites Combined:
| Category | PPA (95% CI) | NPA (95% CI) | Overall Agreement (95% CI) |
| --- | --- | --- | --- |
| RBC Color | 98.33% (97.48%, 99.10%) | 97.61% (96.81%, 98.33%) | 97.88% (97.29%, 98.42%) |
| RBC Inclusions | 86.73% (81.66%, 91.23%) | 98.41% (98.06%, 98.78%) | 97.90% (97.50%, 98.27%) |
| RBC Shape | 95.35% (94.50%, 96.12%) | 96.40% (96.06%, 96.71%) | 96.22% (95.92%, 96.50%) |
| RBC Size | 99.42% (99.03%, 99.75%) | 92.72% (91.82%, 93.70%) | 95.58% (95.06%, 96.13%) |
| PLT Clumping | 86.11% (82.13%, 89.91%) | 87.39% (85.39%, 89.3) | 87.08% (85.25%, 88.92%) |
## Results evaluated for each morphological feature separately:
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| Morphological Feature | PPA
(95% CI) | NPA
(95% CI) | Overall Agreement
(95% CI) |
| --- | --- | --- | --- |
| Hypochromia | 99.31%
(98.43%, 100.00%) | 96.86%
(95.58%, 97.99%) | 97.75%
(96.92%, 98.50%) |
| Polychromasia | 97.40%
(95.92%, 98.72%) | 98.38%
(97.48%, 99.20%) | 98.00%
(97.17%, 98.75%) |
| Basophilic stippling | 96.55%
(88.89%, 100.00%) | 99.91%
(99.74%, 100.00%) | 99.83%
(99.58%, 100.00%) |
| Howell-Jolly bodies | 81.56%
(74.82%, 87.82%) | 93.96%
(92.51%, 95.45%) | 92.50%
(91.00%, 93.96%) |
| Micro-organisms | 85.71%
(50.00%, 100.00%) | 99.92%
(99.75%, 100.00%) | 99.83%
(99.58%, 100.00%) |
| Pappenheimer bodies | 100.00%
(100.00%, 100.00%) | 99.40%
(98.89%, 99.83%) | 99.42%
(98.92%, 99.83%) |
| Platelet clumps | 86.11%
(82.13%, 89.91%) | 87.39%
(85.39%, 89.39%) | 87.08%
(85.25%, 88.92%) |
| Acanthocytes | 100.00%
(100.00%, 100.00%) | 98.82%
(98.10%, 99.37%) | 98.91%
(98.25%, 99.42%) |
| Bite cells | 100.00%
(100.00%, 100.00%) | 99.91%
(99.74%, 100.00%) | 99.92%
(99.75%, 100.00%) |
| Blister cells | 88.89%
(63.64%, 100.00%) | 99.83%
(99.58%, 100.00%) | 99.75%
(99.42%, 100.00%) |
| Echinocytes | 99.48%
(98.70%, 100.00%) | 99.13%
(98.37%, 99.64%) | 99.24%
(98.65%, 99.66%) |
| Elliptocytes | 97.80%
(94.19%, 100.00%) | 99.64%
(99.27%, 99.91%) | 99.50%
(99.08%, 99.83%) |
| Helmet cells | 82.46%
(72.22%, 92.23%) | 94.23%
(93.12%, 95.33%) | 93.67%
(92.50%, 94.75%) |
| Ovalocytes | 100.00%
(100.00%, 100.00%) | 98.52%
(97.47%, 99.35%) | 99.24%
(98.74%, 99.66%) |
| Poikilocytosis | 98.61%
(97.39%, 99.55%) | 96.27%
(94.99%, 97.46%) | 97.13%
(96.19%, 98.05%) |
| Schistocytes | 77.17%
(71.63%, 82.27%) | 74.51%
(71.44%, 77.40%) | 75.17%
(72.59%, 77.63%) |
| Sickle cells | 98.00%
(93.10%, 100.00%) | 99.47%
(99.03%, 99.83%) | 99.41%
(98.95%, 99.83%) |
| Spherocytes | 97.59%
(93.72%, 100.00%) | 99.55%
(99.11%, 99.91%) | 99.42%
(98.92%, 99.83%) |
| Stomatocytes | 100.00%
(100.00%, 100.00%) | 99.30%
(98.77%, 99.74%) | 99.33%
(98.83%, 99.75%) |
| Target cells | 99.07%
(97.84%, 100.00%) | 99.17%
(98.48%, 99.71%) | 99.15%
(98.55%, 99.57%) |
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| Morphological Feature | PPA
(95% CI) | NPA
(95% CI) | Overall Agreement
(95% CI) |
| --- | --- | --- | --- |
| Teardrop cells | 84.78%
(80.00%, 88.89%) | 82.24%
(79.68%, 84.85%) | 82.89%
(80.57%, 85.11%) |
| Anisocytosis | 99.34%
(98.66%, 100.00%) | 97.98%
(96.81%, 99.00%) | 98.67%
(98.00%, 99.33%) |
| Macrocytes | 99.36%
(98.59%, 100.00%) | 88.49%
(86.58%, 90.50%) | 92.75%
(91.58%, 94.00%) |
| Microcytes | 99.57%
(98.91%, 100.00%) | 92.66%
(90.82%, 94.43%) | 95.33%
(94.17%, 96.42%) |
RBC Color
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 881 | 36 | 917 |
| Test Method Negative | 15 | 1468 | 1483 |
| Total | 896 | 1504 | 2400 |
RBC Inclusions
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 183 | 73 | 256 |
| Test Method Negative | 28 | 4516 | 4544 |
| Total | 211 | 4589 | 4800 |
RBC Shape
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 2606 | 493 | 3099 |
| Test Method Negative | 127 | 13184 | 13311 |
| Total | 2733 | 13677 | 16410 |
RBC Size
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 1531 | 150 | 1681 |
| Test Method Negative | 9 | 1910 | 1919 |
| Total | 1540 | 2060 | 3600 |
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Hypochromia
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 432 | 24 | 456 |
| Test Method Negative | 3 | 741 | 744 |
| Total | 435 | 765 | 1200 |
Polychromasia
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 449 | 12 | 461 |
| Test Method Negative | 12 | 727 | 739 |
| Total | 461 | 739 | 1200 |
Basophilic Stippling
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 28 | 1 | 29 |
| Test Method Negative | 1 | 1170 | 1171 |
| Total | 29 | 1171 | 1200 |
Howell-Jolly Bodies
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 115 | 64 | 179 |
| Test Method Negative | 26 | 995 | 1021 |
| Total | 141 | 1059 | 1200 |
Micro-organisms
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 6 | 1 | 7 |
| Test Method Negative | 1 | 1192 | 1193 |
| Total | 7 | 1193 | 1200 |
Pappenheimer Bodies
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 34 | 7 | 41 |
| Test Method Negative | 0 | 1159 | 1159 |
| Total | 34 | 1166 | 1200 |
Acanthocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 97 | 13 | 110 |
| Test Method Negative | 0 | 1086 | 1086 |
| Total | 97 | 1099 | 1196 |
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Bite cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 41 | 1 | 42 |
| Test Method Negative | 0 | 1158 | 1158 |
| Total | 41 | 1159 | 1200 |
Blister cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 8 | 2 | 10 |
| Test Method Negative | 1 | 1189 | 1190 |
| Total | 9 | 1191 | 1200 |
Echinocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 380 | 7 | 387 |
| Test Method Negative | 2 | 800 | 802 |
| Total | 382 | 807 | 1189 |
Elliptocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 89 | 4 | 93 |
| Test Method Negative | 2 | 1105 | 1107 |
| Total | 91 | 1109 | 1200 |
Helmet Cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 47 | 66 | 113 |
| Test Method Negative | 10 | 1077 | 1087 |
| Total | 57 | 1143 | 1200 |
Ovalocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 583 | 9 | 592 |
| Test Method Negative | 0 | 598 | 598 |
| Total | 583 | 607 | 1190 |
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Poikilocytosis
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 426 | 28 | 454 |
| Test Method Negative | 6 | 723 | 729 |
| Total | 432 | 751 | 1183 |
Schistocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 196 | 194 | 390 |
| Test Method Negative | 58 | 567 | 625 |
| Total | 254 | 761 | 1015 |
Sickle cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 49 | 6 | 55 |
| Test Method Negative | 1 | 1136 | 1137 |
| Total | 50 | 1142 | 1192 |
Spherocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 81 | 5 | 86 |
| Test Method Negative | 2 | 1112 | 1114 |
| Total | 83 | 1117 | 1200 |
Stomatocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 56 | 8 | 64 |
| Test Method Negative | 0 | 1130 | 1130 |
| Total | 56 | 1138 | 1194 |
Target cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 319 | 7 | 326 |
| Test Method Negative | 3 | 841 | 844 |
| Total | 322 | 848 | 1170 |
Teardrop cells
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 234 | 143 | 377 |
| Test Method Negative | 42 | 662 | 704 |
| Total | 276 | 805 | 1081 |
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Anisocytosis
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 602 | 12 | 614 |
| Test Method Negative | 4 | 582 | 586 |
| Total | 606 | 594 | 1200 |
Macrocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 467 | 84 | 551 |
| Test Method Negative | 3 | 646 | 649 |
| Total | 470 | 730 | 1200 |
Microcytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 462 | 54 | 516 |
| Test Method Negative | 2 | 682 | 684 |
| Total | 464 | 736 | 1200 |
Platelet clumps
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 248 | 115 | 363 |
| Test Method Negative | 40 | 797 | 837 |
| Total | 288 | 912 | 1200 |
Schistocyte Supplemental Study: RBC-DSS vs. manual light microscope
To supplement the results for schistocytes, the sponsor conducted a study in which the results for schistocytes using the DSS were compared to the results from manual light microscope. Two experienced operators analyzed 75 slides with a mixture of normal PBS samples without schistocytes and slides containing schistocytes in different grade levels. The slides were reviewed on both the DSS and the manual light microscope with a wash-out period between the two devices. The results are summarized below.
Schistocytes
| | Reference Method Positive | Reference Method Negative | Total |
| --- | --- | --- | --- |
| Test Method Positive | 29 | 7 | 36 |
| Test Method Negative | 6 | 33 | 39 |
| Total | 35 | 40 | 75 |
{15}
| Morphological Feature | PPA (95% CI) | NPA (95% CI) | Overall Agreement (95% CI) |
| --- | --- | --- | --- |
| Schistocytes | 82.86% (73.33%, 90.67%) | 82.50% (69.57%, 94.44%) | 82.67% (70.00%, 93.75%) |
5. Carry-Over:
Not applicable.
B Other Supportive Instrument Performance Characteristics Data:
Not applicable.
VIII Proposed Labeling:
The labeling supports the finding of substantial equivalence for this device.
IX Conclusion:
The submitted information in this premarket notification is complete and supports a substantial equivalence decision.
K243144 - Page 16 of 16
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Learn the FDA Browser
Two short videos show you everything — or skip straight to the written tutorial if you'd rather read. You can reopen this any time from the Tutorial button in the top bar.
Part 1 — Search, results, and everyday workflows 16 min
Part 2 — Embeddings: the galaxy map 3 min
1. Search: exact and fuzzy
Type a phrase like "coronary artery calcification" into the search box. You get two kinds of results. Exact results match the literal phrase — prefix searches work ("coronary artery calcificati") but suffix searches do not. Fuzzy results match on the meaning and intent of your phrase rather than the exact words, and are sorted by relevance score. Hover over the Exact or Fuzzy badge on any row to see exactly why it matched.
Use the checkboxes above the results to narrow: SaMD keeps only software-only devices, AI / ML keeps only devices with AI.
Exact vs. fuzzy search: what's the difference?
Exact matches on the literal phrase (prefix search works, suffix does not). Fuzzy matches on the meaning and intent of the phrase rather than the exact words. Hover over the badge on any row to see why it matched.
You search "coronary artery calcification" and want only software devices with AI. What two filters do you apply?
Narrow by SaMD (software-only devices), then narrow by AI/ML (devices with AI).
2. The results table
Scroll right in the results table. The intended use is extracted for you — no need to open the PDF. The device story gives a high-level snapshot of what the device does and how it's used. The AI Performance sub-table shows each output name, acceptance criteria, observed values, and development/test dataset descriptions — the same format Innolitics uses for regulatory strategy outputs, and the fastest high-level fingerprint of an AI device. It is AI-generated but has been very reliable in practice.
Where do you find a device's intended use without opening the PDF?
Scroll right in the search results table. The intended use column is extracted for you; no need to dig into the 510(k) summary PDF.
What does the AI Performance sub-table show, and why is it useful?
Output name, acceptance criteria, observed values, development dataset description, and test dataset description. It's the same format we use for regulatory strategy output and Fast 510(k) input, and the fastest high-level fingerprint of an AI device. AI-generated but reliable in practice.
3. Judging fuzzy relevance
Fuzzy results trail off in relevance as you scroll. Use three signals to decide how far down to go: the fuzzy badge explanations, the intended use column, and whether your target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, you're past the relevant zone. A top hit with a low score (~0.4) and a stretched explanation is a hint the closest predicates are far away — the project may be headed for De Novo. Note the fuzzy search is a pattern match: it doesn't handle negation ("not") well, and hardware devices can appear — filter by SaMD/AI ML to cut them.
How do you judge how far down fuzzy search results to go?
Use the relevancy signals: the fuzzy badge explanations, the intended use column, and whether the target output (e.g., Cobb angle) still appears in the AI Performance sub-table. Once it stops appearing, results are trailing off in relevancy.
4. Device detail page: chat and citations
Click a device name to open its detail page: device facts on the left, a chat window on the right. Ask something like "Describe the training data". The answer carries little citation bubbles — click one to jump to the highlighted passage in the source PDF, so you can verify every AI answer against the document. There's also a Download PDF button for sharing.
How do you verify an AI chat answer on the device detail page?
Click the citation bubbles to jump to the relevant highlight in the source document.
Reading rule for every project: how many summaries do you read in full?
At least the three most relevant 510(k) or De Novo summaries, in full. After that, use targeted chat questions to confirm your memory quickly. The tool supports this professional habit — it doesn't replace it.
5. Side-by-side comparison
Select multiple rows in the results table (aim for under ~10), then open the PDF Viewer tab. Ask one question — it goes to all selected devices in parallel, each with citations. This is the fastest way to compare and contrast devices: training data, PCCP scope, how they handled adding new scanners, and so on.
What does the side-by-side PDF viewer mode do?
Select multiple devices, open the PDF viewer tab, and ask one question (e.g., "Describe the training data"). It queries all selected devices simultaneously with citations, so you can compare and contrast quickly.
6. Collections
With rows selected, go to the Collections tab and create a labeled collection (e.g., "Cobb Angle Project"). Reload that selection any time — before a client call, pull up the collection and ask questions across all of its devices at once.
How do you save a set of selected devices for later use?
Select the rows, go to the Collections tab, and create a labeled collection (e.g., "Cobb Angle Project"). You can reload the selection anytime and carry it into the PDF viewer and other tabs that support selections.
7. Product codes and the regulations tree
Click a product code in the results to jump to it in the regulations tree — identification text, sibling product codes, and devices you can open in a PDF viewer on the right. Click a regulation number to see its identification, special controls, and related product codes. You can also search by product code or regulation number at the top of the tree. Always read the special controls if any exist for your device — it broadens your search and sharpens pre-kickoff research.
What can you do from the regulations tree view?
Browse product codes and regulation numbers, read the identification text and special controls, browse sibling product codes, open device PDFs on the right, and search by product code or regulation number at the top of the tree.
8. Chart view
Click Show Chart and segment by regulation number (or product code) to see which regulations dominate your result set. Clicking a regulation takes you into the regulations tree. Great for spotting that most matches are, say, hardware laparoscopic devices — a cue to go back and filter.
How do you see which regulations dominate a search result set?
Click "Show Chart" and segment by Regulation Number. Clicking a regulation takes you to the regulations tree.
9. The predicate graph
Open the Predicates tab for a family-tree view of predicate relationships. Click a node to trace its parents and children; selections from search carry over pre-selected. Commonly predicated devices are worth reading — a lot of people predicated them for a reason. The visual lineage is also handy on client calls, e.g. to show how a predicate family evolved and justify why your predicate still holds.
In the predicate graph, why are commonly predicated devices worth reading?
A lot of people predicated them for a reason. Clicking a node traces parents and children, and selections from search carry over pre-selected.
10. Embeddings: the galaxy map
The Embeddings tab plots every matching document in a 2-D "galaxy map" where semantically similar devices cluster together. Hover or click clusters to explore, and let AI label the clusters for you. Embeddings beat product codes for grouping: two devices can carry different product codes (LLZ vs. QIH) yet do the same thing — the embedding captures the meaning of the intended use and device story. This is also exactly how retrieval-augmented generation (RAG) works under the hood, and it makes a great visual on client calls.
Try it yourself
Head to the search page and work through a few of these AI/ML fuzzy searches to build intuition: perivascular fat on CT · aortic valve calcification opportunistic screening on noncontrast CT · breast cancer prediction on digital pathology slides · autism detection · gestational age prediction · a hearing aid that can also detect a pulse · foundation model based analysis of ECG · large language models · penetration test. Watch how the relevance scores, intended use, and AI Performance tables tell you when results stop being meaningful.