When suspicious findings are discovered during radiological examinations, the conventional course of action is the use of a sample biopsy. This procedure is often necessary due to lack of specificity inherent in radiological examinations. In breast imaging, standard x-ray mammography detect various lesions where biopsies are needed. Biopsies, however, consume significant amounts of time and resources. Additionally, the prolonged waiting period for the biopsy results places an additional emotional and practical burden on the patient.

Furthermore, it is important to emphasize that cancers, even when sharing common names such as "breast cancer" or "rectal cancer," exhibit substantial heterogeneity in terms of their clinical characteristics and prognoses. As a result, the optimal treatment strategies and prognostic outcomes might well be unknown at the beginning of treatment.

The Split Dynamic (SD) method extracts structural information, intensity curves and numerical biomarkers, which, based on our own research, have been shown to contain unique and valuable information related to tumor specificity and disease prognosis.

In practice, there are several distinct features in the Split Dynamics approach to MRI imaging when compared to the conventional methods used in standard MR exams. These differences become particularly noticeable when the primary objectives of the examination are cancer detection and prognosis. MRI has the potential to provide both structural and functional information about a suspicious lesion. However, due to the operating procedures of the scanner, there is often a need to strike a balance between structural and functional data.

An excellent illustration of this compromise can be seen in MR breast imaging. Several years ago, radiologists administering a single dose of contrast agent decided that, for the sake of diagnostic accuracy, it was best to track the contrast bolus over time using a high-resolution (structural) imaging sequence. Previous to this decision it was also recognized that functional information could better differentiate between the most common benign tumor, fibroadenomas, and the most prevalent cancerous tumours, invasive ductal carcinoma. However, no one was able to develop an MRI technique capable of capturing both types of information within a single dose of contrast agent, until researchers at Sunnmøre MR-klinikk demonstrated that the Split Dynamics method could achieve precisely that. In our Ph.D. research, we demonstrated that certain biomarkers, made possible by our method, exhibited a uniqueness that set them apart from biomarkers generated by alternative functional MRI approaches. Additionally, we found that some of these biomarkers were more precise when produced using our method compared to other existing solutions for functional MRI.

In the field of breast imaging, we assert that no other non-invasive imaging technique surpasses the precision of our SD (Split Dynamics) method. We believe that widespread adoption of the SD method has the potential to significantly accelerate and enhance the accuracy of breast tumor diagnosis compared to current methods in use today.

In the context of rectal cancer, the remarkable and ground-breaking discovery was that the SD dynamic method holds prognostic value. This means that when rectal cancer is detected using the SD method, it can provide an indication of the likelihood of surviving the next five years. If the indication provided by the SD dynamic method suggests a low likelihood of surviving, it may warrant consideration of alternative and potentially experimental treatment procedures.

The present Technology Readiness Level (TRL 5) has been achieved after several years of conducting scientific studies, which have been well-received and published in prestigious radiological journals. Additionally, we have developed an in-house software solution for comprehensive evaluation of the MR images generated by the SD method. This proprietary software is exceptional in that it can extract biomarkers and generate an extensive list of numerical values, which are valuable for diagnostics, prognostics, and research purposes.

The time to make the SD method available for global adoption is now, given the demonstrated potential of the method. To achieve this, it's crucial to establish multiple sites that can replicate our scientific findings, laying the groundwork for a CE marked software and method solution.