DOI: 10.5061/dryad.5dv41nsfj
title: Image dataset of disk diffusion assay scanned with the SIRscan system

description: We present a comprehensive dataset deposited in the DRYAD repository,
 which includes high-resolution images and corresponding automated
 interpretations from the SIRscan system. This dataset is intended to
 support the development and validation of machine learning models and
 other analytical tools aimed at enhancing the accuracy of antimicrobial
 resistance detection, particularly in Gram-negative bacteria. The images
 in this dataset were generated using disk diffusion methods following the
 EUCAST guidelines and encompass a variety of phenotypic resistance
 patterns against beta-lactam antibiotics. The dataset includes 225
 Gram-negative bacterial isolates with a total of 862 unique phenotypic
 categories, reflecting various resistance mechanisms, including
 extended-spectrum beta-lactamase (ESBL), plasmid-mediated AmpC
 beta-lactamase, and carbapenemase production. Each image is paired with an
 automated reading provided by the SIRscan system, which includes
 measurements of inhibition zone diameters and preliminary resistance
 classification. This pairing of raw image data with machine-generated
 interpretations offers a valuable resource for the development of advanced
 algorithms for antimicrobial resistance prediction and other related
 applications. This dataset is part of an ongoing effort to provide
 open-access resources that can be used to benchmark and validate the
 performance of machine learning models in clinical microbiology. By
 sharing these data, we aim to facilitate the development of more accurate
 and efficient diagnostic tools, ultimately contributing to better clinical
 outcomes and more effective antimicrobial stewardship.
description: The dataset was collected as part of a larger study aimed at
 improving the detection of antimicrobial resistance in Gram-negative
 bacteria using disk diffusion methods. The data collection process
 involved the following steps: 
 <strong>Isolate Selection:</strong> A total of 225
 Gram-negative bacterial isolates were selected for the study. These
 isolates were chosen based on their clinical relevance and diversity in
 resistance mechanisms, including extended-spectrum beta-lactamase (ESBL),
 plasmid-mediated AmpC beta-lactamase, and carbapenemase production. The
 isolates represented a range of species commonly encountered in clinical
 microbiology. <strong>Disk
 Diffusion Testing:</strong> Disk diffusion tests were performed on
 each isolate following the standardized guidelines provided by the
 European Committee on Antimicrobial Susceptibility Testing (EUCAST). The
 tests involved placing antibiotic-impregnated disks on agar plates
 inoculated with the bacterial isolates. After incubation, the diameter of
 the inhibition zones around each disk was measured to assess the
 susceptibility of the bacteria to the antibiotics. 
 <strong>Image Acquisition:</strong>
 High-resolution images of the agar plates were captured using the SIRscan
 automated system. The SIRscan system is equipped with advanced imaging
 technology that allows for precise measurement of inhibition zones. Each
 image was stored with a unique identifier corresponding to the specific
 isolate and antibiotic combination tested. 
 <strong>Automated Interpretation:</strong>
 The SIRscan system also provided automated interpretations of the disk
 diffusion results. These interpretations included measurements of
 inhibition zone diameters and preliminary classifications of resistance
 mechanisms based on predefined algorithms aligned with EUCAST guidelines.
 The automated interpretations were recorded alongside the corresponding
 images. <strong>Data
 Annotation and Validation:</strong> The collected images and
 automated interpretations were reviewed and validated by clinical
 microbiologists to ensure accuracy and consistency. Any discrepancies
 between the automated readings and expert evaluations were noted, and the
 dataset was curated to include only high-quality data.
 <strong>Data
 Organization:</strong> The final dataset includes 862 unique
 phenotypic categories, each associated with a high-resolution image and
 its corresponding automated interpretation. The data is organized in a
 structured format, with metadata describing the isolate, antibiotic
 tested, inhibition zone measurements, and the interpreted resistance
 mechanism. This dataset, now
 available in the DRYAD repository, represents a robust resource for
 researchers developing and validating machine learning models and other
 tools for antimicrobial resistance detection. The collection process was
 designed to ensure the reliability and relevance of the data for clinical
 and research applications.
description: # README ## Title Image Dataset of Disk Diffusion Assay Scanned with the
 SIRscan System ## Citation Egli, Adrian et al. (2023). Image Dataset of
 Disk Diffusion Assay Scanned with the SIRscan System. Dryad Digital
 Repository.
 [https://doi.org/10.5061/dryad.5dv41nsfj](https://doi.org/10.5061/dryad.5dv41nsfj) ## Authors * **Prof. Adrian Egli** * Institute of Medical Microbiology * University of Zurich * Email: [aegli@imm.uzh.ch](mailto:aegli@imm.uzh.ch) ## Contact Information For any questions or further information regarding this dataset, please contact: * **Prof. Adrian Egli** * Email: [aegli@imm.uzh.ch](mailto:aegli@imm.uzh.ch) ## Date of Data Collection * January 2020 to December 2022 ## Geographic Location of Data Collection * Institute of Medical Microbiology * University of Zurich * Zurich, Switzerland ## Project Description This dataset comprises images and measurement data from routine microbiological diagnostics using the disk diffusion assay to assess antimicrobial resistance (AMR) in bacterial isolates. The images were generated using the **SIRscan** system, an automated device for scanning and interpreting disk diffusion plates. The disk diffusion assay was conducted according to the **European Committee on Antimicrobial Susceptibility Testing (EUCAST)** guidelines. The assay involves placing antibiotic-impregnated disks on agar plates inoculated with bacteria and measuring the inhibition zones to determine the susceptibility of bacteria to various antibiotics. Based on the measured inhibition zones, bacteria are categorized as **Sensitive (S)**, **Intermediate (I)**, or **Resistant (R)** to each antibiotic tested. The dataset also includes information on specific resistance mechanisms inferred from the resistance patterns: * **No Resistance Mechanism**: Bacteria are susceptible to tested antibiotics. * **Extended Spectrum Beta-Lactamases (ESBL)** * **AmpC Beta-Lactamases (AmpC)** * **Carbapenemases** * **Combination of Mechanisms**: Occurrence of multiple resistance mechanisms. These resistance mechanisms may occur individually or in combination. ## Description of Data Files The dataset is organized into three main compressed files: ### 1. `images_original.zip` * **Description**: Contains the original, unprocessed images of disk diffusion plates captured by the SIRscan system. * **File Format**: JPEG images (`.jpg`) * **Number of Files**: 225 images * **Folder Structure**: `images_original/ ├── Sample001_20200101_090000.jpg ├── Sample002_20200101_093000.jpg ├── ...` * **File Naming Convention**: * Each image file is named using the format: `SampleID_Date_Time.jpg`, where: * **SampleID**: Unique identifier for the bacterial isolate (e.g., Sample001). * **Date**: Date of image capture in `YYYYMMDD` format. * **Time**: Time of image capture in `HHMMSS` format. ### 2. `images_measured.zip` * **Description**: Contains images annotated with measured inhibition zones, where an AI system has recognized and measured the zones. * **File Format**: JPEG images (`.jpg`) with annotations. * **Number of Files**: 225 images * **Folder Structure**: `images_measured/ ├── Sample001_20200101_090000_measured.jpg ├── Sample002_20200101_093000_measured.jpg ├── ...` * **File Naming Convention**: * Each image file corresponds to the original image but with `_measured` appended to indicate the measurements. ### 3. `Tables.zip` * **Description**: Contains tabular data with detailed measurements and interpretations for each antibiotic tested against each bacterial isolate. * **File Format**: CSV files (`.csv`) * **Number of Files**: 1 file * **Folder Structure**: `Tables/ └── measurements.csv` * **File Contents**: The `measurements.csv` file includes the following columns: * **SampleID**: Unique identifier for each bacterial isolate. * **Date**: Date of the test (`YYYY-MM-DD` format). * **Antibiotic**: Name of the antibiotic tested. * **ZoneDiameter_mm**: Measured diameter of the inhibition zone in millimeters. * **Interpretation**: Categorical assessment based on EUCAST guidelines (`S`, `I`, `R`). * **ResistanceMechanism**: Identified resistance mechanism(s) (`None`, `ESBL`, `AmpC`, `Carbapenemase`, `Combination`). * **Comments**: Additional notes or observations. ## File Organization and Structure * The dataset is divided into three main directories, each compressed into a ZIP file for ease of distribution. * **`images_original.zip`** and **`images_measured.zip`** contain image files organized in a flat structure without subfolders. * **`Tables.zip`** contains the `measurements.csv` file with all measurement data. ## Variable Definitions ### Image Files * **SampleID**: A unique alphanumeric code assigned to each bacterial isolate (e.g., `Sample001`). * **Date**: Date when the image was captured (`YYYYMMDD` format). * **Time**: Time when the image was captured (`HHMMSS` format). ### Measurements CSV File (`measurements.csv`) * **SampleID**: Matches the `SampleID` in the image files; used to link measurement data with images. * **Date**: Date of the disk diffusion assay (`YYYY-MM-DD` format). * **Antibiotic**: The antibiotic agent tested (e.g., Amoxicillin, Ciprofloxacin). * **ZoneDiameter_mm**: The measured diameter of the inhibition zone, in millimeters. * **Interpretation**: * **S**: Sensitive * **I**: Intermediate * **R**: Resistant * **ResistanceMechanism**: * **None**: No specific resistance mechanism detected. * **ESBL**: Presence of Extended Spectrum Beta-Lactamase. * **AmpC**: Presence of AmpC beta-lactamase. * **Carbapenemase**: Presence of carbapenemase enzymes. * **Combination**: Multiple resistance mechanisms present. * **Comments**: Any additional information or observations noted during the assay. ## Methods ### Sample Collection * Bacterial isolates were collected from patient samples submitted for routine diagnostic testing at the Institute of Medical Microbiology, University of Zurich. * Isolates include a range of clinically relevant bacterial species. ### Disk Diffusion Assay * Conducted according to **EUCAST guidelines** (version 2022). * Mueller-Hinton agar plates were inoculated with bacterial suspensions adjusted to a 0.5 McFarland standard. * Antibiotic disks were placed on the agar surface using standardized protocols. * Plates were incubated at **35±1°C** for **16-20 hours**. ### Image Acquisition * After incubation, plates were scanned using the **SIRscan 2000** automated system. * Original images were saved in high-resolution JPEG format. ### Measurement and Interpretation * Inhibition zones were measured using AI software integrated with the SIRscan system. * The AI system automatically detects the edges of inhibition zones and calculates their diameters. * Measurements were reviewed and validated by trained microbiologists. * Interpretations (`S`, `I`, `R`) were assigned based on EUCAST breakpoint tables. ### Resistance Mechanism Identification * Based on specific inhibition zone patterns and confirmatory tests, resistance mechanisms were inferred. * For example, resistance to cephalosporins and susceptibility to carbapenems may indicate ESBL production. ## Software Requirements * **Image Viewing**: Any standard image viewer capable of opening JPEG files (e.g., Windows Photo Viewer, macOS Preview). * **Data Analysis**: Software capable of opening CSV files, such as Microsoft Excel, LibreOffice Calc, or statistical software like R or Python. ## Data Usage Notes * Data is anonymized and does not contain any patient-identifiable information. * Users should comply with data protection regulations when using the dataset. ## License and Access Restrictions * This dataset is licensed under the **Creative Commons Attribution 0 (CC0)**. However, if possible we would appreciate a proper citation of this dataset. * Users are free to share and adapt the material for any purpose, even commercially, provided appropriate credit is given. ## Acknowledgements * We thank the staff of the Institute of Medical Microbiology, University of Zurich, for their assistance in data collection and validation. * Special thanks to the technical team for their support with the SIRscan system. ## Funding Sources * This work was supported by the **the University of Zurich**. ## Data Source * The images and data were derived from routine diagnostic activities at the Institute of Medical Microbiology, University of Zurich. --- **In Case of Questions:** Please contact the main author, **Prof. Adrian Egli**, at **[aegli@uzh.ch](mailto:aegli@uzh.ch)** for any inquiries regarding the dataset. --- ## Summary This README file provides a comprehensive overview of the dataset titled "Image Dataset of Disk Diffusion Assay Scanned with the SIRscan System." It includes detailed descriptions of the data files, their organization, variables, and the methods used to generate the data. The dataset is valuable for researchers interested in antimicrobial resistance, microbiology diagnostics, image analysis, and the development of AI tools in medical applications. By providing this detailed README, we aim to ensure that anyone interested in reusing the data can easily understand and navigate the dataset, facilitating transparency and reproducibility in research.