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- Astaraki, Mehdi, PhD Student, 1984-, et al.
(författare)
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Early survival prediction in non-small cell lung cancer from PET/CT images using an intra-tumor partitioning method
- 2019
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Ingår i: Physica medica (Testo stampato). - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 60, s. 58-65
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Tidskriftsartikel (refereegranskat)abstract
- PurposeTo explore prognostic and predictive values of a novel quantitative feature set describing intra-tumor heterogeneity in patients with lung cancer treated with concurrent and sequential chemoradiotherapy.MethodsLongitudinal PET-CT images of 30 patients with non-small cell lung cancer were analysed. To describe tumor cell heterogeneity, the tumors were partitioned into one to ten concentric regions depending on their sizes, and, for each region, the change in average intensity between the two scans was calculated for PET and CT images separately to form the proposed feature set. To validate the prognostic value of the proposed method, radiomics analysis was performed and a combination of the proposed novel feature set and the classic radiomic features was evaluated. A feature selection algorithm was utilized to identify the optimal features, and a linear support vector machine was trained for the task of overall survival prediction in terms of area under the receiver operating characteristic curve (AUROC).ResultsThe proposed novel feature set was found to be prognostic and even outperformed the radiomics approach with a significant difference (AUROCSALoP = 0.90 vs. AUROCradiomic = 0.71) when feature selection was not employed, whereas with feature selection, a combination of the novel feature set and radiomics led to the highest prognostic values.ConclusionA novel feature set designed for capturing intra-tumor heterogeneity was introduced. Judging by their prognostic power, the proposed features have a promising potential for early survival prediction.
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| 2. |
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| 3. |
- Buizza, Giulia, et al.
(författare)
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Early tumor response prediction for lung cancer patients using novel longitudinal pattern features from sequential PET/CT image scans
- 2018
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Ingår i: Physica medica (Testo stampato). - : ELSEVIER SCI LTD. - 1120-1797 .- 1724-191X. ; 54, s. 21-29
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: A new set of quantitative features that capture intensity changes in PET/CT images over time and space is proposed for assessing the tumor response early during chemoradiotherapy. The hypothesis whether the new features, combined with machine learning, improve outcome prediction is tested. Methods: The proposed method is based on dividing the tumor volume into successive zones depending on the distance to the tumor border. Mean intensity changes are computed within each zone, for CT and PET scans separately, and used as image features for tumor response assessment. Doing so, tumors are described by accounting for temporal and spatial changes at the same time. Using linear support vector machines, the new features were tested on 30 non-small cell lung cancer patients who underwent sequential or concurrent chemoradiotherapy. Prediction of 2-years overall survival was based on two PET-CT scans, acquired before the start and during the first 3 weeks of treatment. The predictive power of the newly proposed longitudinal pattern features was compared to that of previously proposed radiomics features and radiobiological parameters. Results: The highest areas under the receiver operating characteristic curves were 0.98 and 0.93 for patients treated with sequential and concurrent chemoradiotherapy, respectively. Results showed an overall comparable performance with respect to radiomics features and radiobiological parameters. Conclusions: A novel set of quantitative image features, based on underlying tumor physiology, was computed from PET/CT scans and successfully employed to distinguish between early responders and non-responders to chemoradiotherapy.
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| 4. |
- Lazzeroni, Marta, et al.
(författare)
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Evaluation of third treatment week as temporal window for assessing responsiveness on repeated FDG-PET scans in Non-Small Cell Lung Cancer patients
- 2018
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Ingår i: Physica medica (Testo stampato). - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 46, s. 45-51
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: Early assessment of tumour response to treatment with repeated FDG-PET-CT imaging has potential for treatment adaptation but it is unclear what the optimal time window for this evaluation is. Previous studies indicate that changes in SUVmean and the effective radiosensitivity (alpha(eff), accounting for uptake variations and accumulated dose until the second FDG-PET-CT scan) are predictive of 2-year overall survival (OS) when imaging is performed before radiotherapy and during the second week. This study aims to investigate if multiple FDG-PET-derived quantities determined during the third treatment week have stronger predictive power.Methods: Twenty-eight lung cancer patients were imaged with FDG-PET-CT before radiotherapy (PET1) and during the third week (PET2). SUVmean, SUVmax, SUVpeak, MTV41%-50% (Metabolic Tumour Volume), TLG41%-50% (Total Lesion Glycolysis) in PET1 and PET2 and their change (), as well as average alpha(eff) (<(alpha)over bar >(eff)) and the negative fraction of alpha(eff) values (f(alpha eff) (< 0)) were determined. Correlations were sought between FDG-PET-derived quantities and OS with ROC analysis.Results: Neither SUVmean, SUVmax, SUVpeak in PET1 and PET2 (AUC = 0.5-0.6), nor their changes (AUC = 0.5-0.6) were significant for outcome prediction purposes. Lack of correlation with OS was also found for (alpha) over bar (eff) (AUC = 0.5) and f(alpha eff) (<) 0 (AUC = 0.5). Threshold-based quantities (MTV41%-50%, TLG41%-50%) and their changes had AUC= 0.5-0.7. P-values were in all cases >> 0.05.Conclusions: The poor OS predictive power of the quantities determined from repeated FDG-PET-CT images indicates that the third week of treatment might not be suitable for treatment response assessment. Comparatively, the second week during the treatment appears to be a better time window.
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| 5. |
- Lazzeroni, Marta, et al.
(författare)
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Impact of Tumour Cell Infiltration on Treatment Outcome in Gamma Knife Radiosurgery : A Modelling Study
- 2019
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Ingår i: Anticancer Research. - : INT INST ANTICANCER RESEARCH. - 0250-7005 .- 1791-7530. ; 39:4, s. 1675-1687
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Tidskriftsartikel (refereegranskat)abstract
- Background: High-grade gliomas with a widespread infiltration beyond the lesion detectable on diagnostic images are increasingly treated with Gamma Knife (TM) Radiosurgery (GKRS). The aim of this study was to assess the cell infiltration impact on the GKRS outcome for invasive gliomas. Materials and Methods: Tumor cell distribution was predicted using a novel algorithm whose computations are iterated until they reach an agreement with histopathology results. Treatment plans with different combinations of dose prescription (20 Gy at 50%-20% isodose) and targets [Gross Tumour Volume (GTV), zone 1 with 100%-60% of the GTV cell density and zone 2 with 60%-0% of the GTV cell density] were evaluated using standard conformity indexes (CI) and radiobiological parameters. Results: Considerable differences in terms of tumor control probability were found between plans having similar CI but different targets. Conclusion: To account for tumor cell infiltration outside the target is of key importance in GKRS and a radiobiological evaluation should accompany well-established CI.
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| 7. |
- Toma-Dasu, Iuliana, et al.
(författare)
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Evaluating tumor response of non-small cell lung cancer patients with 18F-fludeoxyglucose positron emission tomography: potential for treatment individualization
- 2015
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Ingår i: International Journal of Radiation Oncology, Biology, Physics. - : Elsevier BV. - 0360-3016 .- 1879-355X. ; 91:2, s. 376-384
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Tidskriftsartikel (refereegranskat)abstract
- Objective: To assess early tumor responsiveness and the corresponding effective radiosensitivity for individual patients with non-small cell lung cancer (NSCLC) based on 2 successive 18F-fludeoxyglucose positron emission tomography (FDG-PET) scans.Methods and Materials: Twenty-six NSCLC patients treated in Maastricht were included in the study. Fifteen patients underwent sequential chemoradiation therapy, and 11 patients received concomitant chemoradiation therapy. All patients were imaged with FDG before the start and during the second week of radiation therapy. The sequential images were analyzed in relation to the dose delivered until the second image. An operational quantity, effective radiosensitivity, αeff, was determined at the voxel level. Correlations were sought between the average αeff or the fraction of negative αeff values and the overall survival at 2 years. Separate analyses were performed for the primary gross target volume (GTV), the lymph node GTV, and the clinical target volumes (CTVs).Results: Patients receiving sequential treatment could be divided into responders and nonresponders, using a threshold for the average αeff of 0.003 Gy-1 in the primary GTV, with a sensitivity of 75% and a specificity of 100% (P<.0001). Choosing the fraction of negative αeff as a criterion, the threshold 0.3 also had a sensitivity of 75% and a specificity of 100% (P<.0001). Good prognostic potential was maintained for patients receiving concurrent chemotherapy. For lymph node GTV, the correlation had low statistical significance. A cross-validation analysis confirmed the potential of the method.Conclusions: Evaluation of the early response in NSCLC patients showed that it is feasible to determine a threshold value for effective radiosensitivity corresponding to good response. It also showed that a threshold value for the fraction of negative αeff could also be correlated with poor response. The proposed method, therefore, has potential to identify candidates for more aggressive strategies to increase the rate of local control and also avoid exposing to unnecessary aggressive therapies the majority of patients responding to standard treatment.
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