Recent advancements in medical imaging have opened new possibilities for cancer diagnosis. Researchers at Empa have developed a novel 3D tissue analysis method for thyroid tumours using X-ray phase-contrast micro-computed tomography (micro-CT). This technology, enhanced by artificial intelligence, enables faster and more precise diagnoses without altering or destroying tissue samples. As this technique gains recognition, it holds potential for broader applications across various cancer types, improving diagnostic accuracy while streamlining traditional histopathological procedures. By replacing complex diagnostic procedures with simpler imaging methods, it could significantly enhance efficiency in clinical settings.
Revolutionising Tissue Examination with 3D Imaging
Traditionally, pathologists examine tissue samples by slicing them into thin sections and analysing them under a microscope in two dimensions. The new non-invasive histopathological 3D imaging approach eliminates the need for such invasive processing. Instead, entire biopsy blocks can be visualised digitally, allowing specialists to rotate and inspect them from multiple angles. This technique provides a more comprehensive view of the tumour structure, aiding in more accurate assessments. By preserving the integrity of the sample, additional molecular biological examinations remain possible, further enhancing diagnostic precision.
Early trials with pathologists from the University of Bern have demonstrated the capability of this method to detect clinically significant tissue characteristics in thyroid tumours. X-ray phase-contrast micro-CT enhances the visibility of even the smallest differences in soft tissue, allowing a detailed analysis of the tumour microenvironment. The data collected from these images is then processed using machine learning algorithms, which help in refining diagnostic accuracy. This new approach offers a valuable tool for personalised treatment strategies, ensuring that patients receive the most appropriate level of care.
Enhancing Detection of Tumour Characteristics
One of the key advantages of this 3D analysis is its ability to uncover hidden tumour features in deeper tissue layers that might be missed using conventional methods. For instance, encapsulated thyroid tumours that exhibit aggressive growth often infiltrate surrounding healthy tissue or blood vessels—an indicator of malignancy. Traditional histological techniques may overlook these subtle but critical details, potentially leading to misdiagnoses or delayed treatment.
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A retrospective study, conducted with patient samples from across Europe, aims to validate the effectiveness of this approach in identifying early signs of tumour recurrence. In one case, a patient hospitalised in 2011 with a tumour initially classified as benign later developed a malignant recurrence. Conventional sectional analysis failed to detect capsular herniations deep in the tissue, but the new 3D imaging technique identified these abnormalities retrospectively. Based on these findings, researchers are now examining historical patient samples across Europe to assess whether early detection using this method could have improved clinical outcomes.
The study has received funding from multiple foundations, including the Mirto Foundation, the Bank Vontobel Donation Foundation and several others. These contributions are enabling further investigations into cases where initially harmless findings later progressed into serious malignancies. The ability to retrospectively analyse past cases with advanced imaging provides an opportunity to refine diagnostic protocols, reducing the likelihood of underdiagnosed malignancies in the future.
Seamless Integration into Clinical Practice
The adoption of 3D tissue analysis offers a significant enhancement to existing diagnostic workflows rather than replacing established histopathological methods. By integrating seamlessly into routine clinical procedures, this approach complements traditional two-dimensional sectioning techniques, providing additional insights without disrupting current medical practices. The ability to obtain comprehensive, non-destructive imaging ensures that clinicians can re-evaluate samples as needed, supporting more flexible and informed decision-making.
Furthermore, this technology has shown promise for applications beyond thyroid cancer, including prostate and lung cancers. Ongoing research, funded by the Swiss National Science Foundation, is exploring its potential in detecting metastases in colorectal cancer. If successful, this method could help replace some of the more complex molecular analyses currently used in oncology with simpler and more efficient imaging techniques. This could lead to the development of standardised imaging biomarkers that correlate with underlying genetic changes, enabling a more targeted and predictive approach to cancer treatment.
Future advancements could even enable the correlation of imaging findings with molecular tumour characteristics, paving the way for more refined genetic profiling through imaging alone. By linking imaging texture features at the micrometre scale to molecular alterations within the tumour, researchers aim to develop a more holistic understanding of cancer progression and therapeutic response.
The development of 3D computed tomography for cancer diagnosis represents a significant leap forward in medical imaging. By enabling a non-invasive, comprehensive examination of tumour structures, this method enhances diagnostic accuracy while preserving tissue integrity for further analysis. Retrospective analyses have already demonstrated its potential to uncover missed malignancies, reinforcing its importance in refining diagnostic strategies.
With continued research and clinical validation, this technology could play a transformative role in personalised medicine, improving early detection and treatment outcomes across various cancer types. By integrating into mainstream medical practice, it has the potential to refine cancer diagnostics and optimise patient care strategies globally. In the long term, the ability to link imaging findings with genetic changes could further enhance precision medicine, enabling tailored treatment plans based on a patient's unique tumour profile. As adoption of this technique increases, it may lead to significant improvements in cancer prognosis, making early and accurate detection more accessible and reliable than ever before.
Source: EMPA
Image Credit: iStock
