A Novel Radiomics-Based Tumor Volume Segmentation Algorithm for Lung Tumors in FDG-PET/CT after 3D Motion Correction-A Technical Feasibility and Stability Study

Positron emission tomography (PET) provides important additional information when applied in radiation therapy treatment planning. However, the optimal way to define tumors in PET images is still undetermined. As radiomics features are gaining more and more importance in PET image interpretation as well, we aimed to use textural features for an optimal differentiation between tumoral tissue and surrounding tissue to segment-target lesions based on three textural parameters found to be suitable in previous analysis (Kurtosis, Local Entropy and Long Zone Emphasis). Intended for use in radiation therapy planning, this algorithm was combined with a previously described motion-correction algorithm and validated in phantom data. In addition, feasibility was shown in five patients. The algorithms provided sufficient results for phantom and patient data. The stability of the results was analyzed in 20 consecutive measurements of phantom data. Results for textural feature-based algorithms were slightly worse than those of the threshold-based reference algorithm (mean standard deviation 1.2%-compared to 4.2% to 8.6%) However, the Entropy-based algorithm came the closest to the real volume of the phantom sphere of 6 ccm with a mean measured volume of 26.5 ccm. The threshold-based algorithm found a mean volume of 25.0 ccm. In conclusion, we showed a novel, radiomics-based tumor segmentation algorithm in FDG-PET with promising results in phantom studies concerning recovered lesion volume and reasonable results in stability in consecutive measurements. Segmentation based on Entropy was the most precise in comparison with sphere volume but showed the worst stability in consecutive measurements. Despite these promising results, further studies with larger patient cohorts and histopathological standards need to be performed for further validation of the presented algorithms and their applicability in clinical routines. In addition, their application in other tumor entities needs to be studied

Histological Evaluation of Direct Pulp Capping with Novel Nanostructural Materials Based on Active Silicate Cements and Biodentine (R) on Pulp Tissue

The aim of this study was to examine the effect of Biodentine (R) and two new nanostructured materials based on active silicate cements on exposed tooth pulp of Vietnamese pigs. The study comprised 40 teeth in two Vietnamese pigs (24 months old). After class V cavity preparation, the pulp on each tooth was exposed using a small round bur. The following materials were applied on pulp exposures: Biodentine (R) (10 teeth), ALBO MPCA-I (10 teeth), and ALBO MPCA-II (10 teeth). In the control group, exposed pulp was covered with ProRoot MTA (R) (10 teeth). After the observation period of 28 days, the animals were sacrificed and the teeth prepared for histological analysis. Light microscope was used for the analysis of dentin bridge formation, tissue reorganization and inflammation, and the presence of bacteria in the pulp. In the group of Biodentine (R), a complete dentin bridge was noted in 3 cases, while incomplete dentin bridge in the form of dental islets was detected in 4 cases. Nanostructured material ALBO-MPCA I provided complete dentin bridge formation in 5 teeth, in 3 teeth the formed dentin bridge was incomplete. ALBO MPCA-II showed complete closure of the pulp opening by dentin bridge in 4 samples, while in the same number of teeth it was incomplete. In the control group, 4 teeth showed a complete dentin bridge, whereas in 6 teeth it was incomplete. Histological analysis indicated favourable therapeutic effects of Biodentine (R) and the two materials ALBO-MPCA I and ALBO-MPCA II after teeth pulp capping in Vietnamese pigs. Pulp reaction was similar to that caused by ProRoot MTA (R)

4D-CT-based motion correction of PET images using 3D iterative deconvolution

Objectives: Positron emission tomography acquisition takes several minutes representing an image averaged over multiple breathing cycles. Therefore, in areas influenced by respiratory movement, PET-positive lesions occur larger, but less intensive than they actually are, resulting in false quantitative assessment. We developed a motion-correction algorithm based on 4D-CT without the need to adapt PET-acquisition. Methods: The algorithm is based on a full 3D iterative Richardson-Lucy-Deconvolution using a point-spread-function constructed using the motion information obtained from the 4D-CT. In a motion phantom study (3 different hot spheres in background activity), optimal parameters for the algorithm in terms of number of iterations and start image were estimated. Finally, the correction method was applied to 3 patient data sets. In phantom and patient data sets lesions were delineated and compared between motion corrected and uncorrected images for activity uptake and volume. Results: Phantom studies showed best results for motion correction after 6 deconvolution steps or higher. In phantom studies, lesion volume improved up to 23% for the largest, 43% for the medium and 49% for the smallest sphere due to the correction algorithm. In patient data the correction resulted in a significant reduction of the tumor volume up to 33.3 % and an increase of the maximum and mean uptake of the lesion up to 62.1 and 19.8 % respectively. Conclusion: In conclusion, the proposed motion correction method showed good results in phantom data and a promising reduction of detected lesion volume and a consequently increasing activity uptake in three patients with lung lesions

A Novel Radiomics-Based Tumor Volume Segmentation Algorithm for Lung Tumors in FDG-PET/CT after 3D Motion Correction—A Technical Feasibility and Stability Study

Positron emission tomography (PET) provides important additional information when applied in radiation therapy treatment planning. However, the optimal way to define tumors in PET images is still undetermined. As radiomics features are gaining more and more importance in PET image interpretation as well, we aimed to use textural features for an optimal differentiation between tumoral tissue and surrounding tissue to segment-target lesions based on three textural parameters found to be suitable in previous analysis (Kurtosis, Local Entropy and Long Zone Emphasis). Intended for use in radiation therapy planning, this algorithm was combined with a previously described motion-correction algorithm and validated in phantom data. In addition, feasibility was shown in five patients. The algorithms provided sufficient results for phantom and patient data. The stability of the results was analyzed in 20 consecutive measurements of phantom data. Results for textural feature-based algorithms were slightly worse than those of the threshold-based reference algorithm (mean standard deviation 1.2%—compared to 4.2% to 8.6%) However, the Entropy-based algorithm came the closest to the real volume of the phantom sphere of 6 ccm with a mean measured volume of 26.5 ccm. The threshold-based algorithm found a mean volume of 25.0 ccm. In conclusion, we showed a novel, radiomics-based tumor segmentation algorithm in FDG-PET with promising results in phantom studies concerning recovered lesion volume and reasonable results in stability in consecutive measurements. Segmentation based on Entropy was the most precise in comparison with sphere volume but showed the worst stability in consecutive measurements. Despite these promising results, further studies with larger patient cohorts and histopathological standards need to be performed for further validation of the presented algorithms and their applicability in clinical routines. In addition, their application in other tumor entities needs to be studied

Local Control and overall survival after frameless radiosurgery: A single center experience

Introduction Stereotactic radiosurgery (SRS) has been increasingly advocated for 1–3 small brain metastases. The goal of this study was to evaluate the clinical results in patients with brain metastases treated with LINAC-based SRS using a thermoplastic mask (non-invasive fixation system) and Image-Guided Radiotherapy (IGRT). Material and Methods In this single-institution study 48 patients with 77 brain metastases were treated between February 2012 and January 2014. The prescribed dose was 20 Gy or 18 Gy as a single fraction. SRS was performed with a True Beam STX Novalis Radiosurgery LINAC (Varian Medical Systems). The verification of positioning was done using the BrainLAB ExacTrac ® X-ray 6D system and cone-beam CT. Results In 69 of 77 treated brain metastases (90%) the follow-up was documented on MR imaging performed every 3 months. Mean follow-up time was 10.86 months. Estimated 1-year local control was 83%, using the Kaplan-Meier method. In 7/69 brain metastases (10%) local failure (LF) was diagnosed. Median progression free survival (PFS) was 3.73 months, largely due to distant brain relapse. A GTV of ≤2.0 cm3 was significantly associated with a better PFS than a GTV >2.0 cm3. Extracranial stable disease and GTV ≤2.5 cm³ were significant predictors of OS. We observed 2 cases of radiation necrosis diagnosed by histology after surgical resection. No other cases of severe side effects (CTACE ≥ 3) were observed. Conclusion LINAC-based frameless SRS with the BrainLAB Mask using the BrainLAB ExacTrac ® X-ray 6D system for patient positioning is well tolerated, safe and leads to favorable crude local control of 90%. In our experience, local control after frameless (ringless) SRS is as good as ring-based SRS reported in literature. Without invasive head fixation, radiotherapy is more comfortable for patients

Macrophages, the main marker in biocompatibility evaluation of new hydrogels after subcutaneous implantation in rats

Biocompatibility of materials is one of the most important conditions for their successful application in tissue regeneration and repair. Cell-surface interactions stimulate adhesion and activation of macrophages whose acquaintance can assist in designing novel biomaterials that promote favorable macrophage-biomaterial surface interactions for clinical application. This study is designed to determine the distribution and number of macrophages as a means of biocompatibility evaluation of two newly synthesized materials [silver/poly(vinyl alcohol) (Ag/PVA) and silver/poly(vinyl alcohol)/graphene (Ag/PVA/Gr) nanocomposite hydrogels] in vivo, with approval of the Ethics Committee of the Faculty of Veterinary Medicine, University of Belgrade. Macrophages and giant cells were analyzed in tissue sections stained by routine H&E and immunohistochemical methods (CD68(+)). Statistical relevance was determined in the statistical software package SPSS 20 (IBM corp). The results of the study in terms of the number of giant cells localized around the implant showed that their number was highest on the seventh postoperative day (p.o.d.) in the group implanted with Ag/PVA hydrogels, and on the 30th p.o.d. in the group implanted with Ag/PVA/Gr. Interestingly, the number of macrophages measured in the capsular and pericapsular space was highest in the group implanted with the commercial Suprasor