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- Andersén, Christoffer, 1991-, et al.
(författare)
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Presults for the aI-Brachy study : Utilizing deep learning for needle reconstruction in prostate brachytherapy
- 2019
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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.
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| 2. |
- Heydorn, Per, et al.
(författare)
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Long-term rearing affects pheromone-mediated flight behaviour of the Indian meal moth, Plodia interpunctella
- 2019
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Ingår i: Journal of Applied Entomology. - : Wiley. - 0931-2048 .- 1439-0418. ; 143:10, s. 1193-1195
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Tidskriftsartikel (refereegranskat)abstract
- The pest Plodia interpunctella (Hübner) is reared in many research laboratories. In a culture established in 1996, attraction of males to the female-produced sex pheromone in flight tunnel assays gradually decreased after ≈15 years of rearing. A new culture was established to enable comparison with the old culture regarding traits associated with mate finding. Female calling activity, pheromone titre and male antennal response to pheromone components did not differ between cultures. In contrast, very few males from the old culture reached the pheromone source in flight tunnel assays compared with 61%–81% of males from the other culture. Our results highlight the importance of maintaining viable insect cultures for research purposes and suggest frequent evaluation of traits involved in chemical communication in such cultures to ensure reliable results in experiments.
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| 3. |
- Krauss, Wolfgang, 1973-, et al.
(författare)
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Radiomics from multisite MRI and clinical data to predict clinically significant prostate cancer
- 2024
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Ingår i: Acta Radiologica. - : Sage Publications. - 0284-1851 .- 1600-0455. ; 23:1
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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.
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