The revolution in breast cancer diagnostics: from visual inspection of histopathology slides to using desktop tissue analysers for automated nanomechanical profiling of tumours
The revolution in breast cancer diagnostics: from visual inspection of histopathology slides to using desktop tissue analysers for automated nanomechanical profiling of tumours
We aim to develop new portable desktop tissue analysers (DTAs) to provide fast, low-cost, and precise test results for fast nanomechanical profiling of tumours. This paper will explain the reasoning for choosing indentation-type atomic force microscopy (IT-AFM) to reveal the functional details of cancer. Determining the subtype, cancer stage, and prognosis will be possible, which aids in choosing the best treatment. DTAs are based on fast IT-AFM at the size of a small box that can be made for a low budget compared to other clinical imaging tools. The DTAs can work in remote areas and all parts of the world. There are a number of direct benefits: First, it is no longer needed to wait a week for the pathology report as the test will only take 10 min. Second, it avoids the complicated steps of making histopathology slides and saves costs of labour. Third, computers and robots are more consistent, more reliable, and more economical than human workers which may result in fewer diagnostic errors. Fourth, the IT-AFM analysis is capable of distinguishing between various cancer subtypes. Fifth, the IT-AFM analysis could reveal new insights about why immunotherapy fails. Sixth, IT-AFM may provide new insights into the neoadjuvant treatment response. Seventh, the healthcare system saves money by reducing diagnostic backlogs. Eighth, the results are stored on a central server and can be accessed to develop strategies to prevent cancer. To bring the IT-AFM technology from the bench to the operation theatre, a fast IT-AFM sensor needs to be developed and integrated into the DTAs.
cancer; biomarker; atomic force microscope; artificial intelligence; mechanobiology; MEMS sensor; IT-AFM
Stolz, Martin
7bfa1d59-511d-471b-96ce-679b343b5d1d
28 February 2024
Stolz, Martin
7bfa1d59-511d-471b-96ce-679b343b5d1d
Stolz, Martin
(2024)
The revolution in breast cancer diagnostics: from visual inspection of histopathology slides to using desktop tissue analysers for automated nanomechanical profiling of tumours.
Bioengineering, 11 (3), [237].
Abstract
We aim to develop new portable desktop tissue analysers (DTAs) to provide fast, low-cost, and precise test results for fast nanomechanical profiling of tumours. This paper will explain the reasoning for choosing indentation-type atomic force microscopy (IT-AFM) to reveal the functional details of cancer. Determining the subtype, cancer stage, and prognosis will be possible, which aids in choosing the best treatment. DTAs are based on fast IT-AFM at the size of a small box that can be made for a low budget compared to other clinical imaging tools. The DTAs can work in remote areas and all parts of the world. There are a number of direct benefits: First, it is no longer needed to wait a week for the pathology report as the test will only take 10 min. Second, it avoids the complicated steps of making histopathology slides and saves costs of labour. Third, computers and robots are more consistent, more reliable, and more economical than human workers which may result in fewer diagnostic errors. Fourth, the IT-AFM analysis is capable of distinguishing between various cancer subtypes. Fifth, the IT-AFM analysis could reveal new insights about why immunotherapy fails. Sixth, IT-AFM may provide new insights into the neoadjuvant treatment response. Seventh, the healthcare system saves money by reducing diagnostic backlogs. Eighth, the results are stored on a central server and can be accessed to develop strategies to prevent cancer. To bring the IT-AFM technology from the bench to the operation theatre, a fast IT-AFM sensor needs to be developed and integrated into the DTAs.
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Accepted/In Press date: 27 February 2024
Published date: 28 February 2024
Keywords:
cancer; biomarker; atomic force microscope; artificial intelligence; mechanobiology; MEMS sensor; IT-AFM
Identifiers
Local EPrints ID: 502717
URI: http://eprints.soton.ac.uk/id/eprint/502717
ISSN: 2306-5354
PURE UUID: 9f6a8e17-b092-4eae-9848-338b680e835e
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Date deposited: 07 Jul 2025 16:39
Last modified: 08 Jul 2025 01:44
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