BackgroundIn the present work we compared the spatial uncertainties associated with a MR-based workflow for external radiotherapy of prostate cancer to a standard CT-based workflow. The MR-based workflow relies on target definition and patient positioning based on MR imaging. A solution for patient transport between the MR scanner and the treatment units has been developed. For the CT-based workflow, the target is defined on a MR series but then transferred to a CT study through image registration before treatment planning, and a patient positioning using portal imaging and fiducial markers.MethodsAn "open bore" 1.5T MRI scanner, Siemens Espree, has been installed in the radiotherapy department in near proximity to a treatment unit to enable patient transport between the two installations, and hence use the MRI for patient positioning. The spatial uncertainty caused by the transport was added to the uncertainty originating from the target definition process, estimated through a review of the scientific literature. The uncertainty in the CT-based workflow was estimated through a literature review.ResultsThe systematic uncertainties, affecting all treatment fractions, are reduced from 3-4 mm (1Sd) with a CT based workflow to 2-3 mm with a MR based workflow. The main contributing factor to this improvement is the exclusion of registration between MR and CT in the planning phase of the treatment.ConclusionTreatment planning directly on MR images reduce the spatial uncertainty for prostate treatments.

Prostate cancer is the most common cancer for men in the western world. For the first time, a dual-modality probe, combining Raman spectroscopy and tactile resonance technology, has been used for assessment of fresh human prostate tissue. The study investigates the potential of the dual-modality probe by testing its ability to differentiate prostate tissue types ex vivo. Measurements on four prostates show that the tactile resonance modality was able to discriminate soft epithelial tissue and stiff stroma (p < 0.05). The Raman spectra exhibited a strong fluorescent background at the current experimental settings. However, stroma could be discerned from epithelia by integrating the value of the spectral background. Combining both parameters by a stepwise analysis resulted in 100% sensitivity and 91% specificity. Although no cancer tissue was analysed, the results are promising for further development of the instrument and method for discriminating prostate tissues and cancer.

Tissue characterization is fundamental for identification of pathological conditions. Raman spectroscopy (RS) and tactile resonance measurement (TRM) are two promising techniques that measure biochemical content and stiffness, respectively. They have potential to complement the golden standard-–histological analysis. By combining RS and TRM, complementary information about tissue content can be obtained and specific drawbacks can be avoided. The aim of this study was to develop a multivariate approach to compare RS and TRM information. The approach was evaluated on measurements at the same points on porcine abdominal tissue. The measurement points were divided into five groups by multivariate analysis of the RS data. A regression analysis was performed and receiver operating characteristic (ROC) curves were used to compare the RS and TRM data. TRM identified one group efficiently (area under ROC curve 0.99). The RS data showed that the proportion of saturated fat was high in this group. The regression analysis showed that stiffness was mainly determined by the amount of fat and its composition. We concluded that RS provided additional, important information for tissue identification that was not provided by TRM alone. The results are promising for development of a method combining RS and TRM for intraoperative tissue characterization.

The tactile resonance method (TRM) and Raman spectroscopy (RS) are promising for tissue characterization in vivo. Our goal is to combine these techniques into one instrument, to use TRM for swift scanning, and RS for increasing the diagnostic power. The aim of this study was to determine the classification accuracy, using support vector machines, for measurements on porcine tissue and also produce preliminary data on human prostate tissue. This was done by developing a new experimental set-up combining micro-scale TRM-scanning haptic microscopy (SHM)-for assessing stiffness on a micro-scale, with fibre optic RS measurements for assessing biochemical content. We compared the accuracy using SHM alone versus SHM combined with RS, for different degrees of tissue homogeneity. The cross-validation classification accuracy for healthy porcine tissue types using SHM alone was 65-81%, and when RS was added it increased to 81-87%. The accuracy for healthy and cancerous human tissue was 67-70% when only SHM was used, and increased to 72-77% for the combined measurements. This shows that the potential for swift and accurate classification of healthy and cancerous prostate tissue is high. This is promising for developing a tool for probing the surgical margins during prostate cancer surgery.

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Measurement science and technology (ISSN: 0957-0233)Citation for the published paper: Nyberg, M. ; Candefjord, S. ; Jalkanen, V. (2012) AbstractHistopathology is the golden standard for cancer diagnosis and involves the characterization of tissue components. It is labor intensive and time consuming. We have earlier proposed a combined fibre-optic near-infrared Raman spectroscopy (NIR-RS) and tactile resonance method (TRM) probe for detecting positive surgical margins as a complement to interoperative histopathology. The aims of this study were to investigate the effects of attaching an RS probe inside a cylindrical TRM sensor, to investigate how laserinduced heat of the fibre-optic NIR-RS affected the temperature of the RS probe tip and an encasing TRM sensor. In addition, the possibility to perform fibre-optic NIR-RS in a well-lit environment was investigated.A small amount of rubber latex was preferable for attaching the thin RS probe inside the TRM sensor. The temperature rise of the TRM sensor due to a fibre-optic NIR-RS at 270 mW during 20 s was less than 2 °C. Fibre-optic NIR-RS was feasible in a dimmed bright environment using a small light shield and automatic subtraction of a pre-recorded contaminant spectrum. The results are promising for a combined probe for tissue characterization.

This is a published version of a paper published in The Analyst.Citation for the published paper: Nyberg, M., Ramser, K., Lindahl, O. (2013) "Optical fibre probe NIR Raman measurements in ambient light and in combination with a tactile resonance sensor for possible cancer detection" The Analyst, 138 (14): [4029][4030][4031][4032][4033][4034] Access to the published version may require subscription.Permanent link to this version:

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