A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules.

Lung cancer (LC) is currently one of the main causes of cancer-related deaths worldwide. Low-dose computed tomography (LDCT) of the chest has been proven effective in secondary prevention (i.e., early detection) of LC by several trials. In this work, we investigated the potential impact of radiomics on indeterminate prevalent pulmonary nodule (PN) characterization and risk stratification in subjects undergoing LDCT-based LC screening. As a proof-of-concept for radiomic analyses, the first aim of our study was to assess whether indeterminate PNs could be automatically classified by an LDCT radiomic classifier as solid or sub-solid (first-level classification), and in particular for sub-solid lesions, as non-solid versus part-solid (second-level classification). The second aim of the study was to assess whether an LCDT radiomic classifier could automatically predict PN risk of malignancy, and thus optimize LDCT recall timing in screening programs. Model performance was evaluated using the area under the receiver operating characteristic curve (AUC), accuracy, positive predictive value, negative predictive value, sensitivity, and specificity. The experimental results showed that an LDCT radiomic machine learning classifier can achieve excellent performance for characterization of screen-detected PNs (mean AUC of 0.89 ± 0.02 and 0.80 ± 0.18 on the blinded test dataset for the first-level and second-level classifiers, respectively), providing quantitative information to support clinical management. Our study showed that a radiomic classifier could be used to optimize LDCT recall for indeterminate PNs. According to the performance of such a classifier on the blinded test dataset, within the first 6 months, 46% of the malignant PNs and 38% of the benign ones were identified, improving early detection of LC by doubling the current detection rate of malignant nodules from 23% to 46% at a low cost of false positives. In conclusion, we showed the high potential of LDCT-based radiomics for improving the characterization and optimizing screening recall intervals of indeterminate PNs.

Radiosynthesis and Preclinical Evaluation of 11C-VA426, a Cyclooxygenase-2 Selective Ligand.

Cyclooxygenase-2 (COX-2) is involved in the inflammatory response, and its recurrent overexpression in cancers as well as in neurodegenerative disorders has made it an important target for therapy. For this reason, noninvasive imaging of COX-2 expression may represent an important diagnostic tool. In this work, a COX-2 inhibitor analogue, VA426 [1-(4-fluorophenyl)-3-(2-methoxyethyl)-2-methyl-5-(4-(methylsulfonil)phenyl)-1H-pyrrole], was synthesized and radiolabelled with the 11C radioisotope. The ex vivo biodistribution profile of 11C-VA426 was evaluated in the brain and periphery of healthy rats and mice and in brain and periphery of inflammation models, based on the administration of LPS. 11C-VA426 synthesis with the tBuOK base showed optimal radiochemical yield (15 ± 2%) based on triflate activity, molar activity (range 37-148 GBq/µmol), and radiochemical purity (>95%). Ex vivo biodistribution studies showed a fast uptake of radioactivity but a rapid washout, except in regions expressing COX-2 (lungs, liver, and kidney) both in rats and in mice, with maximum values at 30 and 10 minutes p.i., respectively. LPS administration did not show significant effect on radioactivity accumulation. Celecoxib competition experiments performed in rats and mice treated with LPS produced a general target unrelated reduction of radioactivity concentration in all peripheral tissues and brain areas examined. Finally, in agreement with the negative results obtained from biodistribution experiments, radiometabolites analysis revealed that 11C-VA426 is highly unstable in vivo. This study indicates that the compound 11C-VA426 is not currently suitable to be used as radiopharmaceutical for PET imaging. This family of compounds needs further implementation in order to improve in vivo stability.

Radiosensitizing effect of curcumin-loaded lipid nanoparticles in breast cancer cells.

In breast cancer (BC) care, radiotherapy is considered an efficient treatment, prescribed both for controlling localized tumors or as a therapeutic option in case of inoperable, incompletely resected or recurrent tumors. However, approximately 90% of BC-related deaths are due to the metastatic tumor progression. Then, it is strongly desirable to improve tumor radiosensitivity using molecules with synergistic action. The main aim of this study is to develop curcumin-loaded solid nanoparticles (Cur-SLN) in order to increase curcumin bioavailability and to evaluate their radiosensitizing ability in comparison to free curcumin (free-Cur), by using an in vitro approach on BC cell lines. In addition, transcriptomic and metabolomic profiles, induced by Cur-SLN treatments, highlighted networks involved in this radiosensitization ability. The non tumorigenic MCF10A and the tumorigenic MCF7 and MDA-MB-231 BC cell lines were used. Curcumin-loaded solid nanoparticles were prepared using ethanolic precipitation and the loading capacity was evaluated by UV spectrophotometer analysis. Cell survival after treatments was evaluated by clonogenic assay. Dose-response curves were generated testing three concentrations of free-Cur and Cur-SLN in combination with increasing doses of IR (2-9 Gy). IC50 value and Dose Modifying Factor (DMF) was measured to quantify the sensitivity to curcumin and to combined treatments. A multi-"omic" approach was used to explain the Cur-SLN radiosensitizer effect by microarray and metobolomic analysis. We have shown the efficacy of the Cur-SLN formulation as radiosensitizer on three BC cell lines. The DMFs values, calculated at the isoeffect of SF = 50%, showed that the Luminal A MCF7 resulted sensitive to the combined treatments using increasing concentration of vehicled curcumin Cur-SLN (DMF: 1,78 with 10 µM Cur-SLN.) Instead, triple negative MDA-MB-231 cells were more sensitive to free-Cur, although these cells also receive a radiosensitization effect by combination with Cur-SLN (DMF: 1.38 with 10 µM Cur-SLN). The Cur-SLN radiosensitizing function, evaluated by transcriptomic and metabolomic approach, revealed anti-oxidant and anti-tumor effects. Curcumin loaded- SLN can be suggested in future preclinical and clinical studies to test its concomitant use during radiotherapy treatments with the double implications of being a radiosensitizing molecule against cancer cells, with a protective role against IR side effects.

A novel framework for MR image segmentation and quantification by using MedGA.

BACKGROUND AND OBJECTIVES: Image segmentation represents one of the most challenging issues in medical image analysis to distinguish among different adjacent tissues in a body part. In this context, appropriate image pre-processing tools can improve the result accuracy achieved by computer-assisted segmentation methods. Taking into consideration images with a bimodal intensity distribution, image binarization can be used to classify the input pictorial data into two classes, given a threshold intensity value. Unfortunately, adaptive thresholding techniques for two-class segmentation work properly only for images characterized by bimodal histograms. We aim at overcoming these limitations and automatically determining a suitable optimal threshold for bimodal Magnetic Resonance (MR) images, by designing an intelligent image analysis framework tailored to effectively assist the physicians during their decision-making tasks. METHODS: In this work, we present a novel evolutionary framework for image enhancement, automatic global thresholding, and segmentation, which is here applied to different clinical scenarios involving bimodal MR image analysis: (i) uterine fibroid segmentation in MR guided Focused Ultrasound Surgery, and (ii) brain metastatic cancer segmentation in neuro-radiosurgery therapy. Our framework exploits MedGA as a pre-processing stage. MedGA is an image enhancement method based on Genetic Algorithms that improves the threshold selection, obtained by the efficient Iterative Optimal Threshold Selection algorithm, between the underlying sub-distributions in a nearly bimodal histogram. RESULTS: The results achieved by the proposed evolutionary framework were quantitatively evaluated, showing that the use of MedGA as a pre-processing stage outperforms the conventional image enhancement methods (i.e., histogram equalization, bi-histogram equalization, Gamma transformation, and sigmoid transformation), in terms of both MR image enhancement and segmentation evaluation metrics. CONCLUSIONS: Thanks to this framework, MR image segmentation accuracy is considerably increased, allowing for measurement repeatability in clinical workflows. The proposed computational solution could be well-suited for other clinical contexts requiring MR image analysis and segmentation, aiming at providing useful insights for differential diagnosis and prognosis.

Gene expression profiling of breast cancer cell lines treated with proton and electron radiations.

OBJECTIVE: Technological advances in radiation therapy are evolving with the use of hadrons, such as protons, indicated for tumors where conventional radiotherapy does not give significant advantages or for tumors located in sensitive regions, which need the maximum of dose-saving of the surrounding healthy tissues. The genomic response to conventional and non-conventional linear energy transfer exposure is a poor investigated topic and became an issue of radiobiological interest. The aim of this work was to analyze and compare molecular responses in term of gene expression profiles, induced by electron and proton irradiation in breast cancer cell lines. METHODS: We studied the gene expression profiling differences by cDNA microarray activated in response to electron and proton irradiation with different linear energy transfer values, among three breast cell lines (the tumorigenic MCF7 and MDA-MB-231 and the non-tumorigenic MCF10A), exposed to the same sublethal dose of 9 Gy. RESULTS: Gene expression profiling pathway analyses showed the activation of different signaling and molecular networks in a cell line and radiation type-dependent manner. MCF10A and MDA-MB-231 cell lines were found to induce factors and pathways involved in the immunological process control. CONCLUSION: Here, we describe in a detailed way the gene expression profiling and pathways activated after electron and proton irradiation in breast cancer cells. Summarizing, although specific pathways are activated in a radiation type-dependent manner, each cell line activates overall similar molecular networks in response to both these two types of ionizing radiation. Advances in knowledge: In the era of personalized medicine and breast cancer target-directed intervention, we trust that this study could drive radiation therapy towards personalized treatments, evaluating possible combined treatments, based on the molecular characterization.

Radiation-Induced Gene Expression Changes in High and Low Grade Breast Cancer Cell Types.

BACKGROUND: There is extensive scientific evidence that radiation therapy (RT) is a crucial treatment, either alone or in combination with other treatment modalities, for many types of cancer, including breast cancer (BC). BC is a heterogeneous disease at both clinical and molecular levels, presenting distinct subtypes linked to the hormone receptor (HR) status and associated with different clinical outcomes. The aim of this study was to assess the molecular changes induced by high doses of ionizing radiation (IR) on immortalized and primary BC cell lines grouped according to Human epidermal growth factor receptor (HER2), estrogen, and progesterone receptors, to study how HR status influences the radiation response. Our genomic approach using in vitro and ex-vivo models (e.g., primary cells) is a necessary first step for a translational study to describe the common driven radio-resistance features associated with HR status. This information will eventually allow clinicians to prescribe more personalized total doses or associated targeted therapies for specific tumor subtypes, thus enhancing cancer radio-sensitivity. METHODS: Nontumorigenic (MCF10A) and BC (MCF7 and MDA-MB-231) immortalized cell lines, as well as healthy (HMEC) and BC (BCpc7 and BCpcEMT) primary cultures, were divided into low grade, high grade, and healthy groups according to their HR status. At 24 h post-treatment, the gene expression profiles induced by two doses of IR treatment with 9 and 23 Gy were analyzed by cDNA microarray technology to select and compare the differential gene and pathway expressions among the experimental groups. RESULTS: We present a descriptive report of the substantial alterations in gene expression levels and pathways after IR treatment in both immortalized and primary cell cultures. Overall, the IR-induced gene expression profiles and pathways appear to be cell-line dependent. The data suggest that some specific gene and pathway signatures seem to be linked to HR status. CONCLUSIONS: Genomic biomarkers and gene-signatures of specific tumor subtypes, selected according to their HR status and molecular features, could facilitate personalized biological-driven RT treatment planning alone and in combination with targeted therapies.

Area-based cell colony surviving fraction evaluation: A novel fully automatic approach using general-purpose acquisition hardware.

BACKGROUND: The current methodology for the Surviving Fraction (SF) measurement in clonogenic assay, which is a technique to study the anti-proliferative effect of treatments on cell cultures, involves manual counting of cell colony forming units. This procedure is operator-dependent and error-prone. Moreover, the identification of the exact colony number is often not feasible due to the high growth rate leading to the adjacent colony merging. As a matter of fact, conventional assessment does not deal with the colony size, which is generally correlated with the delivered radiation dose or the administered cytotoxic agent. METHOD: Considering that the Area Covered by Colony (ACC) is proportional to the colony number and size as well as to the growth rate, we propose a novel fully automatic approach exploiting Circle Hough Transform, to automatically detect the wells in the plate, and local adaptive thresholding, which calculates the percentage of ACC for the SF quantification. This measurement relies just on this covering percentage and does not consider the colony number, preventing inconsistencies due to intra- and inter-operator variability. RESULTS: To evaluate the accuracy of the proposed approach, we compared the SFs obtained by our automatic ACC-based method against the conventional counting procedure. The achieved results (r = 0.9791 and r = 0.9682 on MCF7 and MCF10A cells, respectively) showed values highly correlated with the measurements using the traditional approach based on colony number alone. CONCLUSIONS: The proposed computer-assisted methodology could be integrated in laboratory practice as an expert system for the SF evaluation in clonogenic assays.

Cytokine profile of breast cell lines after different radiation doses.

PURPOSE: Ionizing radiation (IR) treatment activates inflammatory processes causing the release of a great amount of molecules able to affect the cell survival. The aim of this study was to analyze the cytokine signature of conditioned medium produced by non-tumorigenic mammary epithelial cell line MCF10A, as well as MCF7 and MDA-MB-231 breast cancer cell lines, after single high doses of IR in order to understand their role in high radiation response. MATERIALS AND METHODS: We performed a cytokine profile of irradiated conditioned media of MCF10A, MCF7 and MDA-MB-231 cell lines treated with 9 or 23 Gy, by Luminex and ELISA analyses. RESULTS: Overall, our results show that both 9 Gy and 23 Gy of IR induce the release within the first 72 h of cytokines and growth factors potentially able to influence the tumor outcome, with a dose-independent and cell-line dependent signature. Moreover, our results show that the cell-senescence phenomenon does not correlate with the amount of 'senescence-associated secretory phenotype' (SASP) molecules released in media. Thus, additional mechanisms are probably involved in this process. CONCLUSIONS: These data open the possibility to evaluate cytokine profile as useful marker in modulating the personalized radiotherapy in breast cancer care.

Development of 99mTc-radiolabeled nanosilica for targeted detection of HER2-positive breast cancer.

The human epidermal growth factor receptor 2 (HER2) is normally associated with a highly aggressive and infiltrating phenotype in breast cancer lesions with propensity to spread into metastases. In clinic, the detection of HER2 in primary tumors and in their metastases is currently based on invasive methods. Recently, nuclear molecular imaging techniques, including positron emission tomography and single photon emission computed tomography (SPECT), allowed the detection of HER2 lesions in vivo. We have developed a 99mTc-radiolabeled nanosilica system, functionalized with a trastuzumab half-chain, able to act as drug carrier and SPECT radiotracer for the identification of HER2-positive breast cancer cells. To this aim, nanoparticles functionalized or not with trastuzumab half-chain, were radiolabeled using the 99mTc-tricarbonyl approach and evaluated in HER2 positive and negative breast cancer models. Cell uptake experiments, combined with flow cytometry and fluorescence imaging, suggested that active targeting provides higher efficiency and selectivity in tumor detection compared to passive diffusion, indicating that our radiolabeling strategy did not affect the nanoconjugate binding efficiency. Ex vivo biodistribution of 99mTc-nanosilica in a SK-BR-3 (HER2+) tumor xenograft at 4 h postinjection was higher in targeted compared to nontargeted nanosilica, confirming the in vitro data. In addition, viability and toxicity tests provided evidence on nanoparticle safety in cell cultures. Our results encourage further assessment of silica 99mTc-nanoconjugates to validate a safe and versatile nanoreporter system for both diagnosis and treatment of aggressive breast cancer.

A fully automatic approach for multimodal PET and MR image segmentation in gamma knife treatment planning.

BACKGROUND AND OBJECTIVES: Nowadays, clinical practice in Gamma Knife treatments is generally based on MRI anatomical information alone. However, the joint use of MRI and PET images can be useful for considering both anatomical and metabolic information about the lesion to be treated. In this paper we present a co-segmentation method to integrate the segmented Biological Target Volume (BTV), using [11C]-Methionine-PET (MET-PET) images, and the segmented Gross Target Volume (GTV), on the respective co-registered MR images. The resulting volume gives enhanced brain tumor information to be used in stereotactic neuro-radiosurgery treatment planning. GTV often does not match entirely with BTV, which provides metabolic information about brain lesions. For this reason, PET imaging is valuable and it could be used to provide complementary information useful for treatment planning. In this way, BTV can be used to modify GTV, enhancing Clinical Target Volume (CTV) delineation. METHODS: A novel fully automatic multimodal PET/MRI segmentation method for Leksell Gamma Knife® treatments is proposed. This approach improves and combines two computer-assisted and operator-independent single modality methods, previously developed and validated, to segment BTV and GTV from PET and MR images, respectively. In addition, the GTV is utilized to combine the superior contrast of PET images with the higher spatial resolution of MRI, obtaining a new BTV, called BTVMRI. A total of 19 brain metastatic tumors, undergone stereotactic neuro-radiosurgery, were retrospectively analyzed. A framework for the evaluation of multimodal PET/MRI segmentation is also presented. Overlap-based and spatial distance-based metrics were considered to quantify similarity concerning PET and MRI segmentation approaches. Statistics was also included to measure correlation among the different segmentation processes. Since it is not possible to define a gold-standard CTV according to both MRI and PET images without treatment response assessment, the feasibility and the clinical value of BTV integration in Gamma Knife treatment planning were considered. Therefore, a qualitative evaluation was carried out by three experienced clinicians. RESULTS: The achieved experimental results showed that GTV and BTV segmentations are statistically correlated (Spearman's rank correlation coefficient: 0.898) but they have low similarity degree (average Dice Similarity Coefficient: 61.87 ± 14.64). Therefore, volume measurements as well as evaluation metrics values demonstrated that MRI and PET convey different but complementary imaging information. GTV and BTV could be combined to enhance treatment planning. In more than 50% of cases the CTV was strongly or moderately conditioned by metabolic imaging. Especially, BTVMRI enhanced the CTV more accurately than BTV in 25% of cases. CONCLUSIONS: The proposed fully automatic multimodal PET/MRI segmentation method is a valid operator-independent methodology helping the clinicians to define a CTV that includes both metabolic and morphologic information. BTVMRI and GTV should be considered for a comprehensive treatment planning.

Reconstruction of uptake patterns in PET: The influence of regularizing prior.

PURPOSE: The effects of regularizing priors on the maximum likelihood (ML) reconstruction of activity patterns in Positron Emission Tomography (PET) were assessed. METHODS: Two edge-preserving priors (one originally proposed by Nuyts et al. and nowadays implemented and commercialized by General Electric Medical Systems as Q.Clear software, and a second one originally proposed by Rapisarda et al. and our group) were assessed and compared to a standard Ordered Subset (OS)-ML reconstruction, assumed as reference. The main difference between the two priors is that Nuyts prior (NY-p) penalizes relative voxel differences while Rapisarda prior (RP-p) absolute ones. Prior parameters were selected by imposing a reference noise texture inside uniform regions with activity comparable to that measured in 18 F-FluoroDeoxyGlucose (FDG) patient livers overall the field of view. Comparisons were then made: (a) on phantom data in terms of sphere recovery coefficients, ability to correctly reconstruct uniform irregularly shaped objects and heterogeneous patterns in patient backgrounds; (b) on patient data in terms of lesion detectability and image quality. RESULTS: On phantoms, both priors succeeded in improving all the assessed features with respect to standard OS-ML reconstruction, mainly thanks to the better signal convergence and to the noise breakup control. On 10 mm spheres, an average recovery coefficient augment of 9% (NY-p) and 34% (RP-p) was obtained; homogeneity of uniform activity objects augmented of 4% (NY-p) and 11% (RP-p); accuracy in reconstructing heterogeneous lesions improved on average of 5% (NY-p) and 15% (RP-p). On patients, lesion detectability resulted improved (on 27 of 30 lesions), regardless of lesion anatomical districts and position in the scanner field of view. NY-p provides a spatial resolution and a noise texture more uniform in the field of view and an image quality similar to standard OS-ML. RP-p has instead a behavior more dependent on the local counting statistics that imposes a trade-off between spatial resolution uniformity and noise texture homogeneity. CONCLUSIONS: The assessed regularizing priors improve PET uptake pattern reconstruction accuracy. Therefore, they should be considered both for oncological lesion detection and uptake spatial distribution assessment. Pitfalls and open challenges are also discussed.

Recurrent bladder carcinoma: clinical and prognostic role of 18 F-FDG PET/CT.

AIM: A small number of studies evaluated the detection rate of lesions from bladder carcinoma (BC) of 18 F-FDG PET/CT in the restaging process. However, the prognostic role of FDG PET/CT still remains unclear. The aim of the present study was to evaluate the accuracy, the effect upon treatment decision, and the prognostic value of FDG PET/CT in patients with suspected recurrent BC. MATERIALS AND METHODS: Forty-one patients affected by BC underwent FDG PET/CT for restaging purpose. The diagnostic accuracy of visually interpreted FDG PET/CT was assessed compared to histology (n = 8), other diagnostic imaging modalities (contrast-enhanced CT in 38/41 patients and MRI in 15/41) and clinical follow-up (n = 41). Semiquantitative PET values (SUVmax, SUVmean, SUL, MTV, TLG) were calculated using a graph-based method. Progression-free survival (PFS) and overall survival (OS) were assessed by using Kaplan-Meier curves. The risk of progression (hazard ratio, HR) was computed by Cox regression analysis by considering all the available variables. RESULTS: PET was considered positive in 21 of 41 patients. Of these, recurrent BC was confirmed in 20 (95 %). Sensitivity, specificity, positive predictive value, negative predictive value, and accuracy of FDG PET/CT were 87 %, 94 %, 95 %, 85 %, 90 %. AUC was 0.9 (95 %IC 0.8-1). Bayesian positive and negative likelihood ratios were 14.5 and 0.13, respectively. FDG PET/CT findings modified the therapeutic approach in 16 patients (modified therapy in 10 PET-positive patients, watch-and-wait in six PET-negative patients). PFS was significantly longer in patients with negative scan vs. those with pathological findings (85 % vs. 24 %, p < 0.05; HR = 12.4; p = 0.001). Moreover, an unremarkable study was associated with a longer OS (88 % vs. 47 % after 2 years and 87 % vs. 25 % after 3 years, respectively, p < 0.05). Standardized uptake value (SUV)max > 6 and total lesion glycolysis (TLG) > 8.5 were recognized as the most accurate thresholds to predict PFS (2-year PFS 62 % for SUVmax < 6 vs. 15 % for SUVmax > 6, p = 0.018; 2-year PFS 66 % for TLG < 8.5 vs. 18 % for TLG > 8.5, p = 0.09). CONCLUSION: A very good diagnostic performance for FDG PET/CT was confirmed in patients with suspected recurrent BC. FDG PET/CT allowed for a change in treatment decision in about 40 % of cases and showed an important prognostic value in assessing PFS and OS.

An enhanced random walk algorithm for delineation of head and neck cancers in PET studies.

An algorithm for delineating complex head and neck cancers in positron emission tomography (PET) images is presented in this article. An enhanced random walk (RW) algorithm with automatic seed detection is proposed and used to make the segmentation process feasible in the event of inhomogeneous lesions with bifurcations. In addition, an adaptive probability threshold and a k-means based clustering technique have been integrated in the proposed enhanced RW algorithm. The new threshold is capable of following the intensity changes between adjacent slices along the whole cancer volume, leading to an operator-independent algorithm. Validation experiments were first conducted on phantom studies: High Dice similarity coefficients, high true positive volume fractions, and low Hausdorff distance confirm the accuracy of the proposed method. Subsequently, forty head and neck lesions were segmented in order to evaluate the clinical feasibility of the proposed approach against the most common segmentation algorithms. Experimental results show that the proposed algorithm is more accurate and robust than the most common algorithms in the literature. Finally, the proposed method also shows real-time performance, addressing the physician's requirements in a radiotherapy environment.

High-Intensity Focused Ultrasound- and Radiation Therapy-Induced Immuno-Modulation: Comparison and Potential Opportunities.

In recent years, high-intensity focused ultrasound (HIFU) has emerged as a new and promising non-invasive and non-ionizing ablative technique for the treatment of localized solid tumors. Extensive pre-clinical and clinical studies have evidenced that, in addition to direct destruction of the primary tumor, HIFU-thermoablation may elicit long-term systemic host anti-tumor immunity. In particular, an important consequence of HIFU treatment includes the release of tumor-associated antigens (TAAs), the secretion of immuno-suppressing factors by cancer cells and the induction of cytotoxic T lymphocyte (CTL) activity. Radiation therapy (RT) is the main treatment modality used for many types of tumors and about 50% of all cancer patients receive RT, often used in combination with surgery and chemotherapy. It is well known that RT can modulate anti-tumor immune responses, modifying micro-environment and stimulating inflammatory factors that can greatly affect cell invasion, bystander effects, radiation tissue complications (such as fibrosis), genomic instability and thus, intrinsic cellular radio-sensitivity. To date, various combined therapeutic strategies (such as immuno-therapy) have been performed in order to enhance RT success in treating locally advanced and recurrent tumors. Recent works suggested the combined use of HIFU and RT treatments to increase the tumor cell radio-sensitivity, in order to synergize the effects reaching the maximum results with minimal doses of ionizing radiation (IR). Here, we highlight the opposite immuno-modulation roles of RT and HIFU, providing scientific reasons to test, by experimental approaches, the use of HIFU immune-stimulatory capacity to improve tumor radio-sensitivity, to reduce the RT induced inflammatory response and to decrease the dose-correlated side effects in normal tissues.

Fast and high temperature hyperthermia coupled with radiotherapy as a possible new treatment for glioblastoma.

BACKGROUND: A new transcranial focused ultrasound device has been developed that can induce hyperthermia in a large tissue volume. The purpose of this work is to investigate theoretically how glioblastoma multiforme (GBM) can be effectively treated by combining the fast hyperthermia generated by this focused ultrasound device with external beam radiotherapy. METHODS/DESIGN: To investigate the effect of tumor growth, we have developed a mathematical description of GBM proliferation and diffusion in the context of reaction-diffusion theory. In addition, we have formulated equations describing the impact of radiotherapy and heat on GBM in the reaction-diffusion equation, including tumor regrowth by stem cells. This formulation has been used to predict the effectiveness of the combination treatment for a realistic focused ultrasound heating scenario. Our results show that patient survival could be significantly improved by this combined treatment modality. DISCUSSION: High priority should be given to experiments to validate the therapeutic benefit predicted by our model.

Divergent in vitro/in vivo responses to drug treatments of highly aggressive NIH-Ras cancer cells: a PET imaging and metabolomics-mass-spectrometry study.

Oncogenic K-ras is capable to control tumor growth and progression by rewiring cancer metabolism. In vitro NIH-Ras cells convert glucose to lactate and use glutamine to sustain anabolic processes, but their in vivo environmental adaptation and multiple metabolic pathways activation ability is poorly understood. Here, we show that NIH-Ras cancer cells and tumors are able to coordinate nutrient utilization to support aggressive cell proliferation and survival. Using PET imaging and metabolomics-mass spectrometry, we identified the activation of multiple metabolic pathways such as: glycolysis, autophagy recycling mechanism, glutamine and serine/glycine metabolism, both under physiological and under stress conditions. Finally, differential responses between in vitro and in vivo systems emphasize the advantageous and uncontrolled nature of the in vivo environment, which has a pivotal role in controlling the responses to therapy.

Correlation between histological grade and positron emission tomography parameters in cervical carcinoma.

The aim of the present study was to evaluate the changes in cervical cancer glucose metabolism for different levels of cellular differentiation. The metabolic activity was measured by standardized uptake value (SUV), SUV normalized to lean body mass, metabolic tumor volume and total lesion glycolysis using fluorine-18 fluorodeoxyglucose positron emission tomography (PET). A correlation study of these values could be used to facilitate therapeutic choice and to improve clinical practice and outcome. This study considered 32 patients with diagnosed cervical cancers, at different International Federation of Gynecology and Obstetrics stages. Glucose metabolism was assessed by PET examination, and histological specimens were examined to determine their initial grade of differentiation. A correlation study of these values was evaluated. Histological examination showed that all cases were of squamous cell carcinoma. Regarding the differentiation of the tumor, 19 well- to moderately-differentiated tumors and 13 poorly-differentiated tumors were determined. Negative findings for correlations between metabolic parameters and initial grade of histological differentiation were found, and considering that histological grade has been shown to have no consistent prognostic value in cervical cancer treatment, PET imaging could play a significant role in cervical cancer prognosis.

Combining split-and-merge and multi-seed region growing algorithms for uterine fibroid segmentation in MRgFUS treatments.

Uterine fibroids are benign tumors that can affect female patients during reproductive years. Magnetic resonance-guided focused ultrasound (MRgFUS) represents a noninvasive approach that uses thermal ablation principles to treat symptomatic fibroids. During traditional treatment planning, uterus, fibroids, and surrounding organs at risk must be manually marked on MR images by an operator. After treatment, an operator must segment, again manually, treated areas to evaluate the non-perfused volume (NPV) inside the fibroids. Both pre- and post-treatment procedures are time-consuming and operator-dependent. This paper presents a novel method, based on an advanced direct region detection model, for fibroid segmentation in MR images to address MRgFUS post-treatment segmentation issues. An incremental procedure is proposed: split-and-merge algorithm results are employed as multiple seed-region selections by an adaptive region growing procedure. The proposed approach segments multiple fibroids with different pixel intensity, even in the same MR image. The method was evaluated using area-based and distance-based metrics and was compared with other similar works in the literature. Segmentation results, performed on 14 patients, demonstrated the effectiveness of the proposed approach showing a sensitivity of 84.05 %, a specificity of 92.84 %, and a speedup factor of 1.56× with respect to classic region growing implementations (average values).

A fully automatic 2D segmentation method for uterine fibroid in MRgFUS treatment evaluation.

PURPOSE: Magnetic Resonance guided Focused UltraSound (MRgFUS) represents a non-invasive surgical approach that uses thermal ablation to treat uterine fibroids. After the MRgFUS treatment, an operator must manually segment the treated fibroid areas to evaluate the NonPerfused Volume (NPV). This manual approach is operator-dependent, introducing issues of result reproducibility, which could lead to errors in the subsequent follow-up phase. Moreover, manual segmentation is time-consuming, and can have a negative impact on the optimization of both machine-time and operator-time. METHOD: To address these issues, in this paper a novel fully automatic method based on the unsupervised Fuzzy C-Means clustering and iterative optimal threshold selection algorithms for uterus and fibroid segmentation is proposed. The developed method could be used to enhance the current manual methodology performed by healthcare operators for post-operative NPV evaluation in uterine fibroid MRgFUS treatments. RESULTS: The proposed method was tested on 15 MR datasets of 15 different patients with uterine fibroids and evaluated using area-based and distance-based metrics. A comparison of extracted volume was also performed. Average values for fibroid (ROT) segmentation are SDI=88.67%, JI=80.70%, SE=89.79%, SP=88.73%, MAD=2.200 [pixels], MAXD=6.233 [pixels] and HD=2.988 [pixels]. Moreover, to make a quantitative evaluation of this method, our experimental results were compared with similar literature approaches. CONCLUSIONS: The proposed method provides a practical approach for the automatic evaluation of the boundary and volume of ablated fibroid regions, without any external user input. The achieved segmentation results show the validity and the effectiveness of the proposed solution.

Caveolin-1, breast cancer and ionizing radiation.

Breast cancer (BC) recovery has increased in recent years thanks to efforts of Omics-based research in this field. However, despite the important results obtained, BC remains a complex multifactorial pathology that is difficult to treat appropriately. Caveolin-1 (CAV1), the basic constituent protein of specialized plasma membrane invaginations called caveolae, is emerging as a potential therapeutic biomarker in BC. This factor may modulate BC response to chemotherapy and radiation therapy. In addition, recent reports describe the key role of CAV1 during cell response to oxidative stress. The aim of the present review was to describe the biological roles of CAV1 in BC considering its contrasting dual functions as an oncogene and as a tumor suppressor. In addition, we report on how CAV1 may contribute to tumor cell response to ionizing radiation treatment. Finally, new roles of CAV1 in BC both on epithelium and stroma may be useful as prognostic indicators for patient treatment and help clinicians in the selection of the best personalized therapy.