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NIROT for imaging of hypoxia in cancer tumors (preclinical study) Alexander Kalyanov*, Juan Mata Pavia*, Catherine Germanier***, Markus Rudin***, Martin.

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Presentation on theme: "NIROT for imaging of hypoxia in cancer tumors (preclinical study) Alexander Kalyanov*, Juan Mata Pavia*, Catherine Germanier***, Markus Rudin***, Martin."— Presentation transcript:

1 NIROT for imaging of hypoxia in cancer tumors (preclinical study) Alexander Kalyanov*, Juan Mata Pavia*, Catherine Germanier***, Markus Rudin***, Martin Wolf*,** * University Hospital Zurich (USZ) ** University of Zurich (UZH) *** Swiss Federal Institute of Technology in Zurich (ETH) Switzerland

2 Motivation Oxygenation of tumor tissue is one of the most important indicators of how aggressive the tumor is. As shown on the plots, tumor hypoxia presents a significant risk for patients and can decrease survival probability by factor of 2. Information about tumor oxygenation could help in prognosis and in choosing a treatment strategy. Despite the high importance of in vivo measurement of oxygenation in tumors, there is currently no technique available. 2 Survival probability comparison between hypoxic tumors (pO 2 <10mm/Hg) and normoxic ones (pO 2 ≥10mm/Hg)

3 The goal of this study is To develop a continuous wave multispectral near-infrared optical tomography (mNIROT) technique for determining the oxygenation state of tissue in small animals. This would give information about the blood supply when studying the tumor microenvironment under hypoxic conditions. Such a setup for animals would be a step towards the development of NIROT for humans in the future. 3

4 State of the art Several different hypoxia imaging techniques are available at the moment for small animals, however they are either invasive and/or expensive. They measure different parameters that can be related to hypoxia, however they cannot provide a quantitative oxygenation value FMT: requires DNA modified cancer cells that produce fluorescence proteins in the presence of hypoxia inducible factors (HIF). Bioluminescence: require ODD-luciferase transgenic mice that spontaneously produce a protein consisting of HIF-1 α oxygen-dependent degradation domain (ODD) fused to luciferase. FMISO-PET: images pO2 in tissue, which can be correlated to StO2 with the oxygen dissociation curve (pH and temperature dependent) 4

5 Why near-infrared optical tomography? 5 Quantitative measurements of StO2 without contrast agents due to the combination of the multispectral approach and the finite elements method (FEM) it becomes possible to reconstruct the concentration of absorbers, such as oxy- and deoxyhemoglobin, in a highly scattering medium with arbitrary shape Non-invasive radiation light at 650-850 nm wavelengths range is used Scalable to humans being non-invasive and employing neither contrast agents nor DNA modification, the NIROT approach could be scaled to investigate tissue oxygenation in the human body in the future

6 How does it work? 6 Multispectral NIROT is a combination of diffuse optical tomography (DOT) and near-infrared spectroscopy (NIRS) – the intensity of diffused light at different wavelengths is measured and used for further reconstruction of the absorbers’ concentrations The main absorbers in tissue are: – oxyhemoglobin (O 2 Hb) and – deoxyhemoglobin (HHb) Hemoglobin is the main oxygen transporter in tissue. Therefore, tissue oxygen saturation StO 2 can be calculated by: StO 2 = O 2 Hb / (O 2 Hb + HHb) transparency window and typical wavelength range of NIRS 798 nm

7 7 Reconstruction algorithm Hypoxia Image adapted from: Ntziachristos V., Fluorescence Molecular Tomography, Annu. Rev. Eng. 2006.8:1-33. NIROT principle An object is illuminated by light at several points called sources and diffused light is registered by detectors. We used a CCD camera for detection of light. Each pixel of the camera is used as a separate detector for further reconstruction of the tissue’s optical properties.

8 The multispectral approach in NIROT is possible due to the different absorption curves of oxy- and deoxyhemoglobin. Measurements at different wavelengths make it possible to quantify oxygenation of tissue in the volume under investigation. As shown on the plot, the oxyhemoglobin HbO 2 absorbs less at wavelengths below 798nm while deoxyhemoglobin HHb absorbs less at wavelengths above 798nm. Multispectral NIROT 8

9 Self-calibrated mNIROT 9 680 nm / 760nm 830 nm / 760nm 830nm 760 nm 680 nm Absorption [1/(mM*mm)] : HbO 2 =0.10, HHb=0.61 Absorption [1/(mM*mm)] : HbO 2 =0.15, HHb=0.38 Absorption [1/(mM*mm)] : HbO 2 =0.23, HHb=0.18 We implemented a wavelength normalisation approach to avoid calibration of the setup which is a typical diffuse optical tomography problem. To the best of our knowledge this is the first time this approach has been used for in vivo measurements. By using the ratio between measurements at two different wavelengths (instead of absolute values) we made the system self-calibrated so no measurements of homogeneous mediums are needed. The approach also removes the influence of background tissue.

10 mNIROT system for animals 10 CCD wavelength tunable laser lens galvo scanner mirror 2 3D-scanning of surface anesthesia mirror 1 NIROT transmission mode reflection mode An animal was placed on a stage with a transparent glass window and anesthetized. The stage was equipped with a heating system to warm up the animal during the experiment. A laser beam scans the bottom surface through the glass window and diffused light is registered by CCD-camera. The CCD was focused on the animal’s surface by the lens.

11 mNIROT system for animals 11 Technical details cameraAndor DV434-BV laser source Fianium SC450 (8 W total output power) with AOTF NIR1 (650÷1100 nm, 2-5 nm bandwidth, ~20mW output) Measurement details 3D scanningNIROT wavelength, nm650700, 735, 760, 798, 820 measurement time10’20’ number of sources70024 typical exposure time, sec 0.050.5-1.5 illumination modereflectiontransmission Photo of the setup shielded from ambient light The mNIROT is based on FMT setup provided by Prof. M.Rudin (Institute for Biomedical Engineering, ETH and UZH) CCD illumination system anaesthesia suppler galvo scanner reflection mode mirror object positioner

12 3D-scanning of an object shape 12 Real animal In order to improve the reconstruction quality we implemented 3D-scanning of the object surface and used information of its geometry to calculate the weight matrix by FEM More than 700 laser spot positions were used for the 3D-surface scanning, captured one after another. A shift of each spot corresponds to surface altitude at this particular point

13 RAW data for 798nm 13 Here is an example of RAW experimental data imposed on the volume of a mouse. 24 source positions on the bottom surface of the animal for each of the wavelengths* were used. Diffused light was captured by a CCD camera (256x256 detectors), the field of view (FOV) was about 74x74 mm. white-light imageRAW data for 798 nm for all the sources * a set of 700, 735, 760, 798 and 820 nm wavelengths

14 Reconstruction 14 *NIRFAST is an open source software package for MATLAB® environment created by Dartmouth college http://www.dartmouth.edu/~nir/nirfast/ http://www.dartmouth.edu/~nir/nirfast/ We used an extensively modified NIRFAST* package for reconstructions. The software was adapted for the wavelength normalisation approach. Homemade software is employed for pre- processing, filtering and validation of RAW data. Tetrahedron size of mesh was set to 1mm for the forward problem resulting in ~9000 nodes. The size was increased up to 2mm for bulk tissue and was kept 1mm for the tumor region in case of inverse problem to improve computation time. This leads to ~2000 nodes in the same volume. The computation time reached 7 minutes for the whole reconstruction process (desktop PC, i7-4770 CPU @ 3.40 GHz, 16 GB RAM).

15 Reconstruction 15 hypoxic region in tumor hypoxic region in tumor spleen artefacts due to low resolution of mesh out of ROI (tumor) YZ-plane XZ-plane XY-plane 3D view StO 2 distribution over the mouse body on the 32 nd day after injection of tumor cells. reconstructed average StO 2 in body is 52%; average StO 2 in the tumor is 41%; minimum StO 2 in the tumor is 8%. spleen liver spleen

16 Validation of NIROT: histology of the tumor 16 The tumor tissue is stained to highlight hypoxic areas in red. These areas are characterized by extremely low partial oxygen pressure pO 2 <10 mmHg (which means that oxygen saturation is not higher than StO 2 <20%). red – hypoxia (pimonidazole staining on the top figure and HIF staining on the bottom figure) green – GFP contained in the cells blue – nuclei of the cells The histological sample was taken on the 37 th day after injection of tumor cells The pimonidazole staining shows presence of highly hypoxic tissue (StO 2 <20%), which agrees well with the NIROT data

17 Long-term study of tumors’ hypoxia 17 tumor cells: mice type: tumor cells injection: DLD-1 wt n°6 HRE-iRFP BALB/c nude, female right flank, subcutaneously The study was carried out in mice. Tumor cells were injected subcutaneously to a batch of 4 mice. NIROT measurements were performed during the next 37 days starting with the 4 th day. 9 datasets were obtained for each mouse except one which died on the 15 th day of the experiment* (#274534). 4 days after injection: 710 15 1823 29 32 37 * Nevertheless the data from the first 4 measurements of it was used in the following statistics

18 Long-term study of tumors’ hypoxia 18 Oxygen saturation of tissue was reconstructed for each measurement. The average values of StO 2 of all animals and its standard deviation (SD) are shown on the plot. Please go to the next slide for more details.

19 Long-term study of tumors’ hypoxia 19 Reconstructed StO 2 values have a similar dynamic for all animals. Average tumor oxygenation appears to be lower than bulk tissue all the time except the first measurement (the 4 th day after injection of tumor cells). At the first 15 days a decrement of StO 2 was observed in all three monitored parameters: bulk tissue StO 2 B, average tumor StO 2 AT and local spatial minimum in tumor area StO 2 min. Although the minimum StO 2 reached extremely low values of about 5%, which is 40% lower than the bulk tissue, the average StO 2 in tumors did not drop down below 28% and stayed 10-15% lower than the background during first 29 days of experiment. After the 15 th day StO 2 increased and almost reached initial values at day 29. The difference between StO 2 B and StO 2 AT reduced to 7%. StO 2 AT grew up to 44% and StO 2 min up to 34%, both shown maximum values since the first week of tumor growth. The last 2 measurements were performed after necrotic processes started in the tumors. The reconstruction algorithm was not adapted to handle necrotic tissue. Therefore the data could be misinterpreted in this time interval.

20 Conclusion The concept of multispectral NIROT with wavelength normalisation approach was proven for hypoxia imaging – geometry information was taken into account and NIRFAST software was employed – quantitative measurements of StO 2 concentration of highly heterogeneous mouse tissue were performed with high spatial resolution Long-term study of the dynamics of tumor hypoxia on a mice model was performed – hypoxia dynamic was measured during 37 days in a batch of 4 mice, the measured trends are in good correlation between animals – the data correlates with HIF-1α activity in hypoxic tumors [M.Rudin at all, 2009] 20

21 Thank you for your attention! 21 The work was supported by:


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