| 1. |
- Andersén, Christoffer, 1991-, et al.
(författare)
-
Presults for the aI-Brachy study : Utilizing deep learning for needle reconstruction in prostate brachytherapy
- 2019
-
Konferensbidrag (refereegranskat)abstract
- Purpose To develop a deep neural network for automatic reconstruction of needles in ultrasound images depicting the prostate during brachytherapy treatment of prostate cancer.Methods Ultrasound tomographies of the prostate from 907 treatments were used to train the artificial intelligent (AI) algorithm. The image matrices were downsampled to 128x128x128 and were used as in-data when training the AI, a 27 layer convolutional neural network. The needles were identified manually by medical physicists using conventional software. These reconstructions were used as gold standard when training the algorithm. An additional set of examinations were used for validation where the needle reconstructions by the AI were compared to the manual reconstructions. The root mean square deviation (RMSD) of needle position, including the central part (70 slices) of the needle was measured in order to avoid influence from artefacts around the needle tip. The result was also evaluated through visual inspection (see image). The times spent for manual vs. AI reconstruction were compared.Results RMSD for manual vs. AI reconstruction is on average (n=170) 1.18±1.0mm, whereas the difference between two manual operators is 0.02±0.06mm, which suggests that the AI is inferior to manual operators. The visual inspection, however, shows AI to be very accurate in positioning the needles. Manual reconstruction took approximately 11.0 minutes, whereas the time for the trained AI is negligible in comparison. Worth noticing regarding RMSD calculations is that, due to limited image resolution, small values may be under-estimated, hence overestimating the difference between the reconstruction methods.Conclusions The study implies that an AI may reconstruct needles for brachytherapy treatments of prostate cancer. The larger deviations between AI algorithm and manual operators, compared to between human operators appears to disagree with the high accuracy of the visual evaluation. However, visually, manual needle reconstructions appear to deviate more from the ultrasound image than do the AI reconstructions. This discrepancy is mainly caused by manual reconstruction software assuming straight needles, unlike the AI. We conclude that AI gives the opportunity to save a substantial amount of treatment planning time, when the patient is anesthetised. Further studies are needed to determine whether different reconstruction methods impact treatment plans.
|
|
| 2. |
- Bernhardt, Peter, 1966, et al.
(författare)
-
A novel quantitative image-based method for evaluating cranial symmetry and its usefulness in patients undergoing surgery for unicoronal synostosis.
- 2013
-
Ingår i: The Journal of craniofacial surgery. - 1536-3732. ; 24:1, s. 166-9
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Unicoronal synostosis presents with cranial asymmetry. Fixed points are difficult to identify; surgical results are therefore difficult to evaluate. The aim of this study was to develop a computer-based method for evaluation of forehead symmetry to enable evaluation of surgical results in unicoronal synostosis. Methods: The MATLAB tool was programmed to segment computed tomographic images, leaving the outermost contour. Cephalometric images were segmented manually due to lower contrast. A center-point (O) and an end-point were manually defined in the midline of the forehead and at the nonfused coronal suture, respectively. The program then found a point (p) on the fused side, at the same distance from the O as the end-point. The contours of the left and right side of the forehead were thereafter superimposed, and the position of minimal area mismatch of the sides was identified. To correct for growth between preoperative images and follow-up, the number of mismatching pixels was related to the area outlined by the contour of the forehead, the end-point and p. Two quantities, the relative symmetry change and the absolute symmetry change, were defined and evaluated by repeated measurements on spherical and elliptical phantoms and 15 patients. Results: Measurements with the MATLAB program were reliable with an SD of 0.26% to 5.39% for the expected range of differences. The SD was lower for measurements on computed tomographic images than for measurements on cephalometric images. The SD was also lower in patients with large surgical improvement than in patients with little improvement. The results support the use of relative symmetry change to evaluate surgical results. Conclusions: Our new computer-based method is capable of measuring forehead symmetry with good precision. This method can be used for systematic evaluation of surgical outcome for unicoronal synostosis and other asymmetric skull deformities.
|
|
| 3. |
- Högberg, Jonas, et al.
(författare)
-
Comparison of Otsu and an adapted Chan-Vese method to determine thyroid active volume using Monte Carlo generated SPECT images
- 2024
-
Ingår i: EJNMMI Physics. - : Springer Nature. - 2197-7364. ; 11:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: The Otsu method and the Chan-Vese model are two methods proven to perform well in determining volumes of different organs and specific tissue fractions. This study aimed to compare the performance of the two methods regarding segmentation of active thyroid gland volumes, reflecting different clinical settings by varying the parameters: gland size, gland activity concentration, background activity concentration and gland activity concentration heterogeneity.METHODS: A computed tomography was performed on three playdough thyroid phantoms with volumes 20, 35 and 50 ml. The image data were separated into playdough and water based on Hounsfield values. Sixty single photon emission computed tomography (SPECT) projections were simulated by Monte Carlo method with isotope Technetium-99 m ([Formula: see text]Tc). Linear combinations of SPECT images were made, generating 12 different combinations of volume and background: each with both homogeneous thyroid activity concentration and three hotspots of different relative activity concentrations (48 SPECT images in total). The relative background levels chosen were 5 %, 10 %, 15 % and 20 % of the phantom activity concentration and the hotspot activities were 100 % (homogeneous case) 150 %, 200 % and 250 %. Poisson noise, (coefficient of variation of 0.8 at a 20 % background level, scattering excluded), was added before reconstruction was done with the Monte Carlo-based SPECT reconstruction algorithm Sahlgrenska Academy reconstruction code (SARec). Two different segmentation algorithms were applied: Otsu's threshold selection method and an adaptation of the Chan-Vese model for active contours without edges; the results were evaluated concerning relative volume, mean absolute error and standard deviation per thyroid volume, as well as dice similarity coefficient.RESULTS: Both methods segment the images well and deviate similarly from the true volumes. They seem to slightly overestimate small volumes and underestimate large ones. Different background levels affect the two methods similarly as well. However, the Chan-Vese model deviates less and paired t-testing showed significant difference between distributions of dice similarity coefficients (p-value [Formula: see text]).CONCLUSIONS: The investigations indicate that the Chan-Vese model performs better and is slightly more robust, while being more challenging to implement and use clinically. There is a trade-off between performance and user-friendliness.
|
|
| 4. |
- Krauss, Wolfgang, 1973-, et al.
(författare)
-
Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer
- 2024
-
Ingår i: Acta Radiologica. - : Sage Publications. - 0284-1851 .- 1600-0455. ; 23:1
-
Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Magnetic resonance imaging (MRI) is useful in the diagnosis of clinically significant prostate cancer (csPCa). MRI-derived radiomics may support the diagnosis of csPCa. PURPOSE: To investigate whether adding radiomics from biparametric MRI to predictive models based on clinical and MRI parameters improves the prediction of csPCa in a multisite-multivendor setting.MATERIAL AND METHODS: Clinical information (PSA, PSA density, prostate volume, and age), MRI reviews (PI-RADS 2.1), and radiomics (histogram and texture features) were retrieved from prospectively included patients examined at different radiology departments and with different MRI systems, followed by MRI-ultrasound fusion guided biopsies of lesions PI-RADS 3-5. Predictive logistic regression models of csPCa (Gleason score ≥7) for the peripheral (PZ) and transition zone (TZ), including clinical data and PI-RADS only, and combined with radiomics, were built and compared using receiver operating characteristic (ROC) curves.RESULTS: In total, 456 lesions in 350 patients were analyzed. In PZ and TZ, PI-RADS 4-5 and PSA density, and age in PZ, were independent predictors of csPCa in models without radiomics. In models including radiomics, PI-RADS 4-5, PSA density, age, and ADC energy were independent predictors in PZ, and PI-RADS 5, PSA density and ADC mean in TZ. Comparison of areas under the ROC curve (AUC) for the models without radiomics (PZ: AUC = 0.82, TZ: AUC = 0.80) versus with radiomics (PZ: AUC = 0.82, TZ: AUC = 0.82) showed no significant differences (PZ: P = 0.366; TZ: P = 0.171).CONCLUSION: PSA density and PI-RADS are potent predictors of csPCa. Radiomics do not add significant information to our multisite-multivendor dataset.
|
|
| 5. |
- Lagerlöf, Jakob Heydorn, 1978, et al.
(författare)
-
3D modeling of effects of increased oxygenation and activity concentration in tumors treated with radionuclides and antiangiogenic drugs.
- 2011
-
Ingår i: Medical physics. - : Wiley. - 0094-2405. ; 38:8, s. 4888-93
-
Tidskriftsartikel (refereegranskat)abstract
- Formation of new blood vessels (angiogenesis) in response to hypoxia is a fundamental event in the process of tumor growth and metastatic dissemination. However, abnormalities in tumor neovasculature often induce increased interstitial pressure (IP) and further reduce oxygenation (pO2) of tumor cells. In radiotherapy, well-oxygenated tumors favor treatment. Antiangiogenic drugs may lower IP in the tumor, improving perfusion, pO2 and drug uptake, by reducing the number of malfunctioning vessels in the tissue. This study aims to create a model for quantifying the effects of altered pO2-distribution due to antiangiogenic treatment in combination with radionuclide therapy.
|
|
| 6. |
- Lagerlöf, Jakob Heydorn, 1978, et al.
(författare)
-
A Parallel Computation Approach to Detailed 3D Modelling of the Complete Oxygen Distribution in Large Tumours
- 2018
-
Ingår i: Cancer Studies and Therapeutics. - 2002-7184. ; 3:4, s. 1-4
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose To develop a general course of action for oxygen distribution calculations, in macroscopic tumours, using Graphics Processing Units (GPU) for parallel computation. Methods A vessel tree structure and an associated macroscopic (about 100 g) tumour were generated, using a stochastic method and Bresenham’s line algorithm. The vessel dimensions were adjusted to correspond to measured values and each vessel voxel was assigned an oxygen value, based on its distance from an incoming large vessel. Diffusion and consumption were modelled using a Green’s function approach together with Michaelis-Menten kinetics. The tumour was inscribed in a matrix of 1012 elements. The computations were performed using a parallel method (CUDA), where the tumour was sectioned into about 18000 sub-matrices, overlapping to avoid edge effects, which were processed individually by three GPU: s. The result matrices were cropped to original size to enable concatenation. Results The entire process took approximately 48 hours, corresponding to 20 seconds per sub-matrix, which is more than fifty times faster when compared to the equivalent CPU calculation. Sample images illustrate the oxygen distribution of our poorly vascularised example tumour. Conclusions Regardless of the model accuracy and performance, the improvement in computation time using GPU calculations is highly advantageous. The preferred, parallel calculation method lowers the computation time by over 98% in this example, while maintaining full quality of performance. This is a remarkable improvement, which makes it possible to test and develop relevant models significantly faster. This computation approach does not depend on how the tumour model was created, nor is it limited to the type of model used here, but may be applied to a variety of problems, involving element-wise operations on large matrices.
|
|
| 7. |
|
|
| 8. |
- Lagerlöf, Jakob Heydorn, 1978, et al.
(författare)
-
Oxygen distribution in tumors: A qualitative analysis and modeling study providing a novel Monte Carlo approach
- 2014
-
Ingår i: Medical Physics. - : Wiley. - 0094-2405. ; 41:9
-
Tidskriftsartikel (refereegranskat)abstract
- Purpose: To construct a Monte Carlo (MC)-based simulation model for analyzing the dependence of tumor oxygen distribution on different variables related to tumor vasculature [blood velocity, vessel-to-vessel proximity (vessel proximity), and inflowing oxygen partial pressure (pO2)]. Methods: A voxel-based tissue model containing parallel capillaries with square cross-sections (sides of 10 μm) was constructed. Green's function was used for diffusion calculations and Michaelis-Menten's kinetics to manage oxygen consumption. The model was tuned to approximately reproduce the oxygenational status of a renal carcinoma; the depth oxygenation curves (DOC) were fitted with an analytical expression to facilitate rapid MC simulations of tumor oxygen distribution. DOCs were simulated with three variables at three settings each (blood velocity, vessel proximity, and inflowing pO2), which resulted in 27 combinations of conditions. To create a model that simulated variable oxygen distributions, the oxygen tension at a specific point was randomly sampled with trilinear interpolation in the dataset from the first simulation. Six correlations between blood velocity, vessel proximity, and inflowing pO2 were hypothesized. Variable models with correlated parameters were compared to each other and to a nonvariable, DOC-based model to evaluate the differences in simulated oxygen distributions and tumor radiosensitivities for different tumor sizes. Results: For tumors with radii ranging from 5 to 30 mm, the nonvariable DOC model tended to generate normal or log-normal oxygen distributions, with a cut-off at zero. The pO2 distributions simulated with the six-variable DOC models were quite different from the distributions generated with the nonvariable DOC model; in the former case the variable models simulated oxygen distributions that were more similar to in vivo results found in the literature. For larger tumors, the oxygen distributions became truncated in the lower end, due to anoxia, but smaller tumors showed undisturbed oxygen distributions. The six different models with correlated parameters generated three classes of oxygen distributions. The first was a hypothetical, negative covariance between vessel proximity and pO2 (VPO-C scenario); the second was a hypothetical positive covariance between vessel proximity and pO2 (VPO+C scenario); and the third was the hypothesis of no correlation between vessel proximity and pO2 (UP scenario). The VPO-C scenario produced a distinctly different oxygen distribution than the two other scenarios. The shape of the VPO-C scenario was similar to that of the nonvariable DOC model, and the larger the tumor, the greater the similarity between the two models. For all simulations, the mean oxygen tension decreased and the hypoxic fraction increased with tumor size. The absorbed dose required for definitive tumor control was highest for the VPO+C scenario, followed by the UP and VPO-C scenarios. Conclusions: A novel MC algorithm was presented which simulated oxygen distributions and radiation response for various biological parameter values. The analysis showed that the VPO-C scenario generated a clearly different oxygen distribution from the VPO+C scenario; the former exhibited a lower hypoxic fraction and higher radiosensitivity. In future studies, this modeling approach might be valuable for qualitative analyses of factors that affect oxygen distribution as well as analyses of specific experimental and clinical situations.
|
|
| 9. |
- Lagerlöf, Jakob Heydorn, 1978, et al.
(författare)
-
Oxygen Distributions-Evaluation of Computational Methods, Using a Stochastic Model for Large Tumour Vasculature, to Elucidate the Importance of Considering a Complete Vascular Network.
- 2016
-
Ingår i: PloS one. - : Public Library of Science (PLoS). - 1932-6203. ; 11:11
-
Tidskriftsartikel (refereegranskat)abstract
- To develop a general model that utilises a stochastic method to generate a vessel tree based on experimental data, and an associated irregular, macroscopic tumour. These will be used to evaluate two different methods for computing oxygen distribution.A vessel tree structure, and an associated tumour of 127 cm3, were generated, using a stochastic method and Bresenham's line algorithm to develop trees on two different scales and fusing them together. The vessel dimensions were adjusted through convolution and thresholding and each vessel voxel was assigned an oxygen value. Diffusion and consumption were modelled using a Green's function approach together with Michaelis-Menten kinetics. The computations were performed using a combined tree method (CTM) and an individual tree method (ITM). Five tumour sub-sections were compared, to evaluate the methods.The oxygen distributions of the same tissue samples, using different methods of computation, were considerably less similar (root mean square deviation, RMSD≈0.02) than the distributions of different samples using CTM (0.001< RMSD<0.01). The deviations of ITM from CTM increase with lower oxygen values, resulting in ITM severely underestimating the level of hypoxia in the tumour. Kolmogorov Smirnov (KS) tests showed that millimetre-scale samples may not represent the whole.The stochastic model managed to capture the heterogeneous nature of hypoxic fractions and, even though the simplified computation did not considerably alter the oxygen distribution, it leads to an evident underestimation of tumour hypoxia, and thereby radioresistance. For a trustworthy computation of tumour oxygenation, the interaction between adjacent microvessel trees must not be neglected, why evaluation should be made using high resolution and the CTM, applied to the entire tumour.
|
|
| 10. |
- Lagerlöf, Jakob Heydorn, 1978, et al.
(författare)
-
Potential of reducing normal tissue complications, using anti-angiogenic drugs in combination with radiotherapy-Modelling effects of improved tumor oxygenation
- 2009
-
Ingår i: Society of Nuclear Medicine Annual Meeting Abstracts 2009. - 0161-5505 .- 2159-662X. ; 50:2
-
Konferensbidrag (övrigt vetenskapligt/konstnärligt)abstract
- Objectives: Tumors stimulate angiogenesis, leading to increased interstitial pressure (IP) and degraded oxygenation (pO2) of the cells. In radiotherapy, high oxygen level in the tumor cells is favourable for successful treatment. Anti-angiogenic drugs can lower the IP in the tumor and cause improved perfusion and increased radionuclide uptake and pO2. This study aims to create a model, describing the variation and effects of altered tumor pO2 distribution due to anti-angiogenic treatment, for use within the field of radiation and radionuclide therapy. Methods: Based on experimental data (Lee et al., 2000), describing the effects of anti-angiogenic agents on pO2 in a tumor, a model was developed, showing how the treatment response improves as the tumor oxygenation level approaches that of normal tissue, which would be the theoretical maximum. The major difference occurs in the poorly oxygenated parts of the tumor. This is also the region where the pO2-dependence of the oxygen enhancement ratio is maximal. The dose levels required to achieve a tumor control probability (TCP) of 0.99 are compared for different pO2 distributions. The normal tissue doses will, in turn, depend on this. Results: As the distribution of oxygen in the tumor approaches normal tissue levels, the therapeutic effect on the tumor is improved so that the doses to normal tissue can be significantly decreased while retaining a high TCP. Conclusions: This shows the potential of efficient anti-angiogenic drugs, a potential that is likely to be further improved by the synergetic effects of an increased radionuclide uptake, in the field of radioisotope therapy.
|
|
