| 1. |
- Abelev, Betty, et al.
(författare)
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Measurement of prompt J/psi and beauty hadron production cross sections at mid-rapidity in pp collisions at root s=7 TeV
- 2012
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Ingår i: Journal of High Energy Physics. - 1029-8479. ; :11
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Tidskriftsartikel (refereegranskat)abstract
- The ALICE experiment at the LHC has studied J/psi production at mid-rapidity in pp collisions at root s = 7 TeV through its electron pair decay on a data sample corresponding to an integrated luminosity L-int = 5.6 nb(-1). The fraction of J/psi from the decay of long-lived beauty hadrons was determined for J/psi candidates with transverse momentum p(t) > 1,3 GeV/c and rapidity vertical bar y vertical bar < 0.9. The cross section for prompt J/psi mesons, i.e. directly produced J/psi and prompt decays of heavier charmonium states such as the psi(2S) and chi(c) resonances, is sigma(prompt J/psi) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 8.3 +/- 0.8(stat.) +/- 1.1 (syst.)(-1.4)(+1.5) (syst. pol.) mu b. The cross section for the production of b-hadrons decaying to J/psi with p(t) > 1.3 GeV/c and vertical bar y vertical bar < 0.9 is a sigma(J/psi <- hB) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 1.46 +/- 0.38 (stat.)(-0.32)(+0.26) (syst.) mu b. The results are compared to QCD model predictions. The shape of the p(t) and y distributions of b-quarks predicted by perturbative QCD model calculations are used to extrapolate the measured cross section to derive the b (b) over bar pair total cross section and d sigma/dy at mid-rapidity.
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| 2. |
- Abelev, Betty, et al.
(författare)
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Underlying Event measurements in pp collisions at root s=0.9 and 7 TeV with the ALICE experiment at the LHC
- 2012
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Ingår i: Journal of High Energy Physics. - 1029-8479. ; :7
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Tidskriftsartikel (refereegranskat)abstract
- We present measurements of Underlying Event observables in pp collisions at root s = 0 : 9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum p(T),L-T in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different p(T) thresholds: 0.15, 0.5 and 1.0 GeV/c. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track p(T) threshold considered. Data are compared to PYTHIA 6.4, PYTHIA 8.1 and PHOJET. On average, all models considered underestimate the multiplicity and summed p(T) in the Transverse region by about 10-30%.
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| 3. |
- 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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| 4. |
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| 5. |
- 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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| 6. |
- Hultqvist, Martha, et al.
(författare)
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Evaluation of nuclear reaction cross-sections and fragment yields in carbon beams using the SHIELD-HIT Monte Carlo code. Comparison with experiments
- 2012
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Ingår i: Physics in Medicine and Biology. - : IOP Publishing. - 0031-9155 .- 1361-6560. ; 57:13, s. 4369-4385
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Tidskriftsartikel (refereegranskat)abstract
- In light ion therapy, the knowledge of the spectra of both primary and secondary particles in the target volume is needed in order to accurately describe the treatment. The transport of ions in matter is complex and comprises both atomic and nuclear processes involving primary and secondary ions produced in the cascade of events. One of the critical issues in the simulation of ion transport is the modeling of inelastic nuclear reaction processes, in which projectile nuclei interact with target nuclei and give rise to nuclear fragments. In the Monte Carlo code SHIELD-HIT, inelastic nuclear reactions are described by the Many Stage Dynamical Model (MSDM), which includes models for the different stages of the interaction process. In this work, the capability of SHIELD-HIT to simulate the nuclear fragmentation of carbon ions in tissue-like materials was studied. The value of the parameter., which determines the so-called freeze-out volume in the Fermi break-up stage of the nuclear interaction process, was adjusted in order to achieve better agreement with experimental data. In this paper, results are shown both with the default value k = 1 and the modified value k = 10 which resulted in the best overall agreement. Comparisons with published experimental data were made in terms of total and partial charge-changing cross-sections generated by the MSDM, as well as integral and differential fragment yields simulated by SHIELD-HIT in intermediate and thick water targets irradiated with a beam of 400 MeV u(-1) C-12 ions. Better agreement with the experimental data was in general obtained with the modified parameter value (k = 10), both on the level of partial charge-changing cross-sections and fragment yields.
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| 7. |
- Häger, Wille, 1990-
(författare)
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A Novel Approach for Radiotherapy and Radiosurgery Treatment Planning Accounting for High-Grade Glioma Invasiveness into Normal Tissue
- 2023
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Licentiatavhandling (övrigt vetenskapligt/konstnärligt)abstract
- High-grade gliomas (HGGs) are a type of malignant brain cancer, which include glioblastomas (GBMs). In adults, GBM is the most common malignant primary brain cancer. Attempts to treat patients with GBMs have been conducted for over a century, but the prognosis has only marginally improved. Current standard treatment involves surgical resection of the gross tumor volume (GTV), followed by radiotherapy and chemotherapy. Despite the efforts, the median survival for patients diagnosed with GBMs is less than 15 months. The inability to accurately determine the full extent of the tumor invaded regions in the brain is assumed to be the reason for the incurability of GBMs. In radiotherapy, the microscopic infiltration of normal tissue by tumor cells in the vicinity of the GTV is accounted for by extending the target into a clinical target volume (CTV). Current recommended margin widths for GBMs range from 15 to 30 mm. Despite a generous margin, the persistent recurrence of GBMs following treatment indicates that the CTV delineations currently used might fail to encompass the entirety of the tumor cell distribution, leaving clonogenic tumor cells untreated. To improve the CTV delineation and possibly treatment of GBMs, novel approaches in determining the tumor infiltrated regions have been suggested in the form of mathematical modeling. The aim of this project is to develop a mathematical model for the infiltration of glioma cells into normal brain tissue and implement it into a framework for predicting the full extent of tumor-invaded tissue for HGGs. This thesis is comprised of papers I–II, an overview of the methodology, results, and discussion of the work. The work herein is presented in order of: 1) model development; 2) model verification. Paper I explores the robustness and results of a mathematical model for tumor spread in terms of its input parameters. By applying the model to a large dataset, the behavior of the model could be investigated statistically, and optimal input parameters determined. The results of the tumor invasion simulations were compared in terms of volumes to the conventionally delineated CTVs, which were found not to adhere to the pathways of the simulated spread. Paper II used the resulting simulated invasions from paper I to predict the overall survival (OS) of the same cohort of cases. OS prediction was better predicted by the simulated volumes of the tumor spread than the size of the GTV. The results showed the potential of improving OS prediction and furthermore demonstrated a new methodology for indirect model verification that does not rely on histopathological data. Planned future work will revolve around dose prescription and plan optimization based on the simulated tumor spread, model investigation using artificial intelligence methods, and finally, practical implementation of the model into research versions of treatment planning systems.
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| 8. |
- Häger, Wille, et al.
(författare)
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CTV Delineation for High-Grade Gliomas : Is There Agreement With Tumor Cell Invasion Models?
- 2022
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Ingår i: ADVANCES IN RADIATION ONCOLOGY. - : Elsevier BV. - 2452-1094. ; 7:5, s. 100987-
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: High-grade glioma (HGG) is a common form of malignant primary brain cancer with poor prognosis. The diffusive nature of HGGs implies that tumor cell invasion of normal tissue extends several centimeters away from the visible gross tumor volume (GTV). The standard methodology for clinical volume target (CTV) delineation is to apply a 2-to 3-cm margin around the GTV. However, tumor recurrence is extremely frequent. The purpose of this paper was to introduce a framework and computational model for the prediction of normal tissue HGG cell invasion and to investigate the agreement of the conventional CTV delineation with respect to the predicted tumor invasion. Methods and Materials: A model for HGG cell diffusion and proliferation was implemented and used to assess the tumor invasion patterns for 112 cases of HGGs. Normal brain structures and tissues as well as the GTVs visible on diagnostic images were delineated using automated methods. The volumes encompassed by different tumor cell concentration isolines calculated using the model for invasion were compared with the conventionally delineated CTVs, and the differences were analyzed. The 3-dimensional-Hausdorff distance between the CTV and the volumes encompassed by various isolines was also calculated. Results: In 50% of cases, the CTV failed to encompass regions containing tumor cell concentrations of 614 cells/mm3 or greater. In 84% of cases, the lowest cell concentration completely encompassed by the CTV was & GE;1 cell/mm3. In the remaining 16%, the CTV overextended into normal tissue. The Hausdorff distance was on average comparable to the CTV margin. Conclusions: The standard methodology for CTV delineation appears to be inconsistent with HGG invasion patterns in terms of size and shape. Tumor invasion modeling could therefore be useful in assisting in the CTV delineation for HGGs.
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| 9. |
- Häger, Wille, et al.
(författare)
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Overall survival prediction for high-grade glioma patients using mathematical modeling of tumor cell infiltration
- 2023
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Ingår i: Physica medica (Testo stampato). - : Elsevier BV. - 1120-1797 .- 1724-191X. ; 113
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Tidskriftsartikel (refereegranskat)abstract
- Purpose: This study aimed at applying a mathematical framework for the prediction of high-grade gliomas (HGGs) cell invasion into normal tissues for guiding the clinical target delineation, and at investigating the possibility of using tumor infiltration maps for patient overall survival (OS) prediction. Material & methods: A model describing tumor infiltration into normal tissue was applied to 93 HGG cases. Tumor infiltration maps and corresponding isocontours with different cell densities were produced. ROC curves were used to seek correlations between the patient OS and the volume encompassed by a particular isocontour. Area-Under-the-Curve (AUC) values were used to determine the isocontour having the highest predictive ability. The optimal cut-off volume, having the highest sensitivity and specificity, for each isocontour was used to divide the patients in two groups for a Kaplan-Meier survival analysis. Results: The highest AUC value was obtained for the isocontour of cell densities 1000 cells/mm3 and 2000 cells/mm3, equal to 0.77 (p < 0.05). Correlation with the GTV yielded an AUC of 0.73 (p < 0.05). The Kaplan-Meier survival analysis using the 1000 cells/mm3 isocontour and the ROC optimal cut-off volume for patient group selection rendered a hazard ratio (HR) of 2.7 (p < 0.05), while the GTV rendered a HR = 1.6 (p < 0.05). Conclusion: The simulated tumor cell invasion is a stronger predictor of overall survival than the segmented GTV, indicating the importance of using mathematical models for cell invasion to assist in the definition of the target for HGG patients.
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| 10. |
- 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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