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.

Translation Imaging in Parkinson's Disease: Focus on Neuroinflammation

Parkinson's disease (PD) is characterized by the loss of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and the appearance of α-synuclein insoluble aggregates known as Lewy bodies. Neurodegeneration is accompanied by neuroinflammation mediated by cytokines and chemokines produced by the activated microglia. Several studies demonstrated that such an inflammatory process is an early event, and contributes to oxidative stress and mitochondrial dysfunctions. α-synuclein fibrillization and aggregation activate microglia and contribute to disease onset and progression. Mutations in different genes exacerbate the inflammatory phenotype in the monogenic compared to sporadic forms of PD. Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) with selected radiopharmaceuticals allow in vivo imaging of molecular modifications in the brain of living subjects. Several publications showed a reduction of dopaminergic terminals and dopamine (DA) content in the basal ganglia, starting from the early stages of the disease. Moreover, non-dopaminergic neuronal pathways are also affected, as shown by in vivo studies with serotonergic and glutamatergic radiotracers. The role played by the immune system during illness progression could be investigated with PET ligands that target the microglia/macrophage Translocator protein (TSPO) receptor. These agents have been used in PD patients and rodent models, although often without attempting correlations with other molecular or functional parameters. For example, neurodegeneration and brain plasticity can be monitored using the metabolic marker 2-Deoxy-2-[¹⁸F]fluoroglucose ([¹⁸F]-FDG), while oxidative stress can be probed using the copper-labeled diacetyl-bis(N-methyl-thiosemicarbazone) ([Cu]-ATSM) radioligand, whose striatal-specific binding ratio in PD patients seems to correlate with a disease rating scale and motor scores. Also, structural and functional modifications during disease progression may be evaluated by Magnetic Resonance Imaging (MRI), using different parameters as iron content or cerebral volume. In this review article, we propose an overview of in vivo clinical and non-clinical imaging research on neuroinflammation as an emerging marker of early PD. We also discuss how multimodal-imaging approaches could provide more insights into the role of the inflammatory process and related events in PD development.

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.

Changes in Glucose Metabolism during and after Radiotherapy in Non-Small Cell Lung Cancer

Aims and background

Evaluation of the metabolic response to radiotherapy in non-small cell lung cancer patients is commonly performed about three months after the end of radiotherapy. The aim of the present study was to assess with positron emission tomography/computed tomography (PET/CT) and [18F]fluorodeoxyglucose changes in glucose metabolism during and after radiotherapy in non-small cell lung cancer patients.

Methods and study design

In 6 patients, PET/CT scans with [18F]fluorodeoxyglucose were performed before (PET0), during (PET1; at a median of 14 days before the end of radiotherapy) and after the end of radiotherapy (PET2 and PET3, at a median of 28 and 93 days, respectively). The metabolic response was scored according to visual and semiquantitative criteria.

Results

Standardize maximum uptake at PET1 (7.9 ± 4.8), PET2 (5.1 ± 4.1) and PET3 (2.7 ± 3.1) were all significantly (P <0.05; ANOVA repeated measures) lower than at PET0 (16.1 ± 10.1). Standardized maximum uptake at PET1 was significantly higher than at both PET2 and PET3. There were no significant differences in SUVmax between PET2 and PET3. PET3 identified 4 complete and 2 partial metabolic responses, whereas PET1 identified 6 partial metabolic responses. Radiotherapy-induced increased [18F]fluorodeoxyglucose uptake could be visually distinguished from tumor uptake based on PET/CT integration and was less frequent at PET1 (n = 2) than at PET3 (n = 6).

Conclusions

In non-small cell lung cancer, radiotherapy induces a progressive decrease in glucose metabolism that is greater 3 months after the end of treatment but can be detected during the treatment itself. Glucose avid, radiotherapy-induced inflammation is more evident after the end of radiotherapy than during radiotherapy and does not preclude the interpretation of [18F]fluorodeoxyglucose images, particularly when using PET/CT.

Can magnetic resonance image-guided focused ultrasound surgery replace local oncology treatments? A review

Magnetic resonance image-guided focused ultrasound surgery (MRgFUS) is an innovative technology in the new panorama of treatment using ultrasound. It combines two well-known and distinct methodologies: high-intensity focused ultrasound (HIFU) and a magnetic resonance imaging system (MRI). This review on MRgFUS is focused on the technical aspects and the current clinical applications in oncology. More precisely, the advantages/disadvantages of MRgFUS compared to other local approaches such as surgery and radiotherapy are discussed in detail.

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.

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.

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 BTV_MRI. 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, BTV_MRI 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. BTV_MRI and GTV should be considered for a comprehensive treatment planning.

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.

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.

Simultaneous reconstruction of attenuation and activity in cardiac PET can remove CT misalignment artifacts

BACKGROUND

Misalignment between positron emission tomography (PET) and computed tomography (CT) data is known to generate artifactual defects in cardiac PET images due to imprecise attenuation correction (AC). In this work, the use of a maximum likelihood attenuation and activity (MLAA) algorithm is proposed to avoid such artifacts in time-of-flight (TOF) PET.

METHODS

MLAA was implemented and tested using a thorax/heart phantom and retrospectively on fourteen (13)N-ammonia PET/CT perfusion studies. Global and local misalignments between PET and CT data were generated by shifting matched CT images or using CT data representative of the end-inspiration phase. PET images were reconstructed with MLAA and a 3D-ordered-subsets-expectation-maximization (OSEM)-TOF algorithm. Images obtained with 3D-OSEM-TOF and matched CT were used as references. These images were compared (qualitatively and semi-quantitatively) with those reconstructed with 3D-OSEM-TOF and MLAA for which a misaligned CT was used, respectively, for AC and initialization.

RESULTS

Phantom experiment proved the capability of MLAA to converge toward the correct emission and attenuation distributions using, as input, only PET emission data, but convergence was very slow. Initializing MLAA with phantom CT images markedly improved convergence speed. In patient studies, when shifted or end-inspiration CT images were used for AC, 3D-OSEM-TOF reconstructions showed artifacts of increasing severity, size, and frequency with increasing mismatch. Such artifacts were absent in the corresponding MLAA images.

CONCLUSION

The proposed implementation of the MLAA algorithm is a feasible and robust technique to avoid AC mismatch artifacts in cardiac PET studies provided that a CT of the source is available, even if poorly aligned.

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.

Synthesis optimization of 2-(4-N-[11C]methylaminophenyl)-6-hydroxybenzothiazole ([11C]PIB), β-amyloid PET imaging tracer for Alzheimer's disease diagnosis

[11C]PIB is the most used amyloid plaques-specific positron-emitting radiotracers. The radiosynthesis of this compound, carried out by methylation of its precursor with [11C]methyl triflate in 2-butanone, has been improved optimizing the initial concentration and the purification method. Two HPLC methods were compared: good radiochemical yields, specific activities, and chemical purity above 98% were achieved by using as eluant acetonitrile/citrate and formulation in 10% ethanol.

Combination of gene expression and genome copy number alteration has a prognostic value for breast cancer

Specific genome copy number alterations, such as deletions and amplifications are an important factor in tumor development and progression, and are also associated with changes in gene expression. By combining analyses of gene expression and genome copy number we identified genes as candidate biomarkers of BC which were validated as prognostic factors of the disease progression. These results suggest that the proposed combined approach may become a valuable method for BC prognosis.

Gene Expression Profiling of MCF10A Breast Epithelial Cells Exposed to IOERT

BACKGROUND/AIM

Intraoperative electron radiation therapy (IOERT) is a therapeutic approach that delivers a single high dose of ionizing radiation (IR) directly to the tumor bed during cancer surgery. The main goal of IOERT is to counteract tumor growth by acting on residual cancer cells as well as to preserve healthy surrounding tissue from the side-effects of radiation therapy. The radiobiology of the healthy tissue response to IR is a topic of interest which may contribute to avoiding impairment of normal tissue and organ function and to reducing the risks of secondary cancer. The purpose of the study was to highlight cell and gene expression responses following IOERT treatment in the human non-tumorigenic MCF10A cell line in order to find new potential biomarkers of radiosensitivity/radioresistance.

MATERIAL AND METHODS

Gene-expression profiling of MCF10A cells treated with 9 and 23 Gy doses (IOERT boost and exclusive treatment, respectively), was performed by whole-genome cDNA microarrays. Real-time quantitative reverse transcription (qRT-PCR), immunofluorescence and immunoblot experiments were carried out to validate candidate IOERT biomarkers. Clonogenic tests and morphological evaluations to examine cellular effects induced by radiation were also conducted.

RESULTS

The study revealed a dose-dependent gene-expression profile and specific key genes that may be proposed as novel markers of radiosensitivity. Our results show consistent differences in non-tumorigenic cell tolerance and in the molecular response of MCF10A cells to different IOERTs. In particular, after 9 Gy of exposure, the selection of a radioresistant cell fraction was observed.

CONCLUSION

The possibility of clarifying the molecular strategies adopted by cells in choosing between death or survival after IR-induced damage opens-up new avenues for the selection of a proper personalized therapy schedule.

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.

Evaluation of image reconstruction algorithms encompassing Time-Of-Flight and Point Spread Function modelling for quantitative cardiac PET: phantom studies

BACKGROUND

To perform kinetic modelling quantification, PET dynamic data must be acquired in short frames, where different critical conditions are met. The accuracy of reconstructed images influences quantification. The added value of Time-Of-Flight (TOF) and Point Spread Function (PSF) in cardiac image reconstruction was assessed.

METHODS

A static phantom was used to simulate two extreme conditions: (i) the bolus passage and (ii) the steady uptake. Various count statistics and independent noise realisations were considered. A moving phantom filled with two different radionuclides was used to simulate: (i) a great range of contrasts and (ii) the cardio/respiratory motion. Analytical and iterative reconstruction (IR) algorithms also encompassing TOF and PSF modelling were evaluated.

RESULTS

Both analytic and IR algorithms provided good results in all the evaluated conditions. The amount of bias introduced by IR was found to be limited. TOF allowed faster convergence and lower noise levels. PSF achieved near full myocardial activity recovery in static conditions. Motion degraded performances, but the addition of both TOF and PSF maintained the best overall behaviour.

CONCLUSIONS

IR accounting for TOF and PSF can be recommended for the quantification of dynamic cardiac PET studies as they improve the results compared to analytic and standard IR.

A systems biology road map for the discovery of drugs targeting cancer cell metabolism

Despite their different histological and molecular properties, different types of cancers share few essential functional alterations. Some of these cancer hallmarks may easily be studied in in vitro cultures, while others are related to the way in which tumors grow in vivo. According to the systems biology paradigm, complex cellular functions arise as system-level properties from the dynamic interaction of a large number of biomolecules. We previously newly defined four basic cancer cell properties derived from known cancer hallmarks amenable to system-level investigation in cell cultures: enhanced growth, altered response to apoptotic cues, genomic instability and inability to enter senescence following oncogenic signaling. Here we summarize the major properties of enhanced growth that is dependent on metabolism rewiring - in which glucose is mostly used by fermentation while glutamine provides nitrogen and carbon atoms for biosyntheses - and controlled by oncogene signaling. We then briefly review the major drugs used to target signaling pathways in preclinical and clinical studies, whose clinical efficacy is unfortunately severely limited by tumor resistance, substantially due to signaling cross-talk. We present a systems biology roadmap that integrates different types of mathematical models with conventional and post-genomic biomolecular analyses that will provide a deeper mechanistic understanding of the links between metabolism and uncontrolled cancer cell growth. This approach is taken to be instrumental both in unraveling cancer's first principles and in designing novel drugs able to target one or more control or execution steps of the cancer rewired metabolism, in order to achieve permanent arrest of tumor development.

Portrait of inflammatory response to ionizing radiation treatment

Ionizing radiation (IR) activates both pro-and anti-proliferative signal pathways producing an imbalance in cell fate decision. IR is able to regulate several genes and factors involved in cell-cycle progression, survival and/or cell death, DNA repair and inflammation modulating an intracellular radiation-dependent response. Radiation therapy can modulate anti-tumour immune responses, modifying tumour and its microenvironment. In this review, we report how IR could stimulate inflammatory factors to affect cell fate via multiple pathways, describing their roles on gene expression regulation, fibrosis and invasive processes. Understanding the complex relationship between IR, inflammation and immune responses in cancer, opens up new avenues for radiation research and therapy in order to optimize and personalize radiation therapy treatment for each patient.

Metabolic impact of partial volume correction of [18F]FDG PET-CT oncological studies on the assessment of tumor response to treatment

AIM

The aim of this work is to evaluate the metabolic impact of Partial Volume Correction (PVC) on the measurement of the Standard Uptake Value (SUV) from [18F]FDG PET-CT oncological studies for treatment monitoring purpose.

METHODS

Twenty-nine breast cancer patients with bone lesions (42 lesions in total) underwent [18F]FDG PET-CT studies after surgical resection of breast cancer primitives, and before (PET-II) chemotherapy and hormone treatment. PVC of bone lesion uptake was performed on the two [18F]FDG PET-CT studies, using a method based on Recovery Coefficients (RC) and on an automatic measurement of lesion metabolic volume. Body-weight average SUV was calculated for each lesion, with and without PVC. The accuracy, reproducibility, clinical feasibility and the metabolic impact on treatment response of the considered PVC method was evaluated.

RESULTS

The PVC method was found clinically feasible in bone lesions, with an accuracy of 93% for lesion sphere-equivalent diameter >1 cm. Applying PVC, average SUV values increased, from 7% up to 154% considering both PET-I and PET-II studies, proving the need of the correction. As main finding, PVC modified the therapy response classification in 6 cases according to EORTC 1999 classification and in 5 cases according to PERCIST 1.0 classification.

CONCLUSION

PVC has an important metabolic impact on the assessment of tumor response to treatment by [18F]FDG PET-CT oncological studies.

Partial volume corrected 18F-FDG PET mean standardized uptake value correlates with prognostic factors in breast cancer

AIM

The aim of this paper was to assess the prognostic role of pretherapy partial volume corrected (PVC) 18F-fluorodeoxyglucose mean standardized uptake value (SUV) in breast cancer (BC).

METHODS

Forty oncological patients, BC diagnosed by biopsy, with breast tumor mass diameter >1 cm measured to the mammography, designed for surgical intervention, underwent a pretherapy semi-quantitative 18F-FDG positron emission tomography/computed tomography (18F-FDG PET/CT) whole-body study for tumor staging. Mean Body-Weight Standardized Uptake Value with Correction for Partial Volume effect (PVC- SUVBW-mean) was calculated in all mammary detected lesions. Excised tissues from primitive BC were sectioned and classified according to the WHO guidelines, evaluating biological features. Univariate (Mann-Withney/Kruskal-Wallis) and multivariate (linear regression, hierarchical clustering) statistical tests were performed between PVC-SUVBW-mean and biological indexes. ROC analysis was performed. PVC-SUVBW-mean thresholds were derived allowing to distinguish groups of BC patients with different biological characteristics. Specificity and Sensitivity were also calculated.

RESULTS

Statistical and multiple correlations between pretherapy 18F-FDG PET PVC-SUVBW-mean and histological type, grade, ER/PgR hormone receptors and Mib-1 cellular proliferation index were found. In our samples, PVC-SUVBW-mean <≈4 g/cc was found correlated to BC patients with Invasive Lobular Carcinoma (ILC) or well differentiated Invasive Ductal Carcinoma (IDC), a positive expression of ER and PgR and a negative expression of MiB-1, while PVC-SUVBW-mean >≈7.00 is associated to BC patients with moderately and poorly differentiated IDC, negative expression of ER and PgR and a positive expression of MiB-1.

CONCLUSION

Pretherapy PVC 18F-FDG PET PVC-SUVBW-mean measurement correlates with prognostic factors in BC and could be used to stratify patients before intervention.

Integration of mRNA expression profile, copy number alterations, and microRNA expression levels in breast cancer to improve grade definition

Defining the aggressiveness and growth rate of a malignant cell population is a key step in the clinical approach to treating tumor disease. The correct grading of breast cancer (BC) is a fundamental part in determining the appropriate treatment. Biological variables can make it difficult to elucidate the mechanisms underlying BC development. To identify potential markers that can be used for BC classification, we analyzed mRNAs expression profiles, gene copy numbers, microRNAs expression and their association with tumor grade in BC microarray-derived datasets. From mRNA expression results, we found that grade 2 BC is most likely a mixture of grade 1 and grade 3 that have been misclassified, being described by the gene signature of either grade 1 or grade 3. We assessed the potential of the new approach of integrating mRNA expression profile, copy number alterations, and microRNA expression levels to select a limited number of genomic BC biomarkers. The combination of mRNA profile analysis and copy number data with microRNA expression levels led to the identification of two gene signatures of 42 and 4 altered genes (FOXM1, KPNA4, H2AFV and DDX19A) respectively, the latter obtained through a meta-analytical procedure. The 42-based gene signature identifies 4 classes of up- or down-regulated microRNAs (17 microRNAs) and of their 17 target mRNA, and the 4-based genes signature identified 4 microRNAs (Hsa-miR-320d, Hsa-miR-139-5p, Hsa-miR-567 and Hsa-let-7c). These results are discussed from a biological point of view with respect to pathological features of BC. Our identified mRNAs and microRNAs were validated as prognostic factors of BC disease progression, and could potentially facilitate the implementation of assays for laboratory validation, due to their reduced number.

Gene expression profiling of epithelial-mesenchymal transition in primary breast cancer cell culture

BACKGROUND/AIM

Epithelial-mesenchymal transition (EMT) is a process co-opted by cancer cells to invade and form metastases. In the present study we analyzed gene expression profiles of primary breast cancer cells in culture in order to highlight genes related to EMT.

MATERIALS AND METHODS

Microarray expression analysis of primary cells isolated from a specimen of a patient with an infiltrating ductal carcinoma of the breast was performed. Real-Time Quantitative Reverse Transcription PCR (qRT-PCR) analyses validated microarray gene expression trends.

RESULTS

Thirty-six candidate genes were selected and used to generate a molecular network displaying the tight relationship among them. The most significant Gene Ontology biological processes characterizing this network were involved in cell migration and motility.

CONCLUSION

Our data revealed the involvement of new genes which displayed tight relationships among them, suggesting a molecular network in which they could contribute to control of EMT in breast cancer. This study may offer a basis for understanding complex mechanisms which regulate breast cancer progression and for designing individualized anticancer therapies.

Machine learning on brain MRI data for differential diagnosis of Parkinson's disease and Progressive Supranuclear Palsy

BACKGROUND

Supervised machine learning has been proposed as a revolutionary approach for identifying sensitive medical image biomarkers (or combination of them) allowing for automatic diagnosis of individual subjects. The aim of this work was to assess the feasibility of a supervised machine learning algorithm for the assisted diagnosis of patients with clinically diagnosed Parkinson's disease (PD) and Progressive Supranuclear Palsy (PSP).

METHOD

Morphological T1-weighted Magnetic Resonance Images (MRIs) of PD patients (28), PSP patients (28) and healthy control subjects (28) were used by a supervised machine learning algorithm based on the combination of Principal Components Analysis as feature extraction technique and on Support Vector Machines as classification algorithm. The algorithm was able to obtain voxel-based morphological biomarkers of PD and PSP.

RESULTS

The algorithm allowed individual diagnosis of PD versus controls, PSP versus controls and PSP versus PD with an Accuracy, Specificity and Sensitivity>90%. Voxels influencing classification between PD and PSP patients involved midbrain, pons, corpus callosum and thalamus, four critical regions known to be strongly involved in the pathophysiological mechanisms of PSP.

COMPARISON WITH EXISTING METHODS

Classification accuracy of individual PSP patients was consistent with previous manual morphological metrics and with other supervised machine learning application to MRI data, whereas accuracy in the detection of individual PD patients was significantly higher with our classification method.

CONCLUSIONS

The algorithm provides excellent discrimination of PD patients from PSP patients at an individual level, thus encouraging the application of computer-based diagnosis in clinical practice.

High-intensity focused ultrasound plus concomitant radiotherapy: a new weapon in oncology?

The potential impact of high-intensity focused ultrasound (HIFU) to general medicine and oncology seems very high. However, while in the research area, the development of this technique is very rapid and unchallenged. The direct application of HIFU to human tumour therapy is hampered by various technical difficulties, which may confine its role to a marginal device in the surgery armamentarium. To deploy the full potential of focused ultrasound in oncology, it seems necessary to review the basic relationship between HIFU and external beam radiotherapy. This is the aim of the present work.

A Decision Support System for the assisted diagnosis of brain tumors: a feasibility study for ¹⁸F-FDG PET preclinical studies

Decision support systems for the assisted medical diagnosis offer the main feature of giving assessments which are poorly affected from arbitrary clinical reasoning. Aim of this work was to assess the feasibility of a decision support system for the assisted diagnosis of brain cancer, such approach presenting potential for early diagnosis of tumors and for the classification of the degree of the disease progression. For this purpose, a supervised learning algorithm combined with a pattern recognition method was developed and cross-validated in ¹⁸F-FDG PET studies of a model of a brain tumour implantation.

Motion management in positron emission tomography/computed tomography for radiation treatment planning

Hybrid positron emission tomography (PET)/computed tomography (CT) scanners combine, in a unique gantry, 2 of the most important diagnostic imaging systems, a CT and a PET tomograph, enabling anatomical (CT) and functional (PET) studies to be performed in a single study session. Furthermore, as the 2 scanners use the same spatial coordinate system, the reconstructed CT and PET images are spatially co-registered, allowing an accurate localization of the functional signal over the corresponding anatomical structure. This peculiarity of the hybrid PET/CT system results in improved tumor characterization for oncological applications, and more recently, it was found to be also useful for target volume definition (TVD) and treatment planning in radiotherapy (RT) applications. In fact, the use of combined PET/CT information has been shown to improve the RT treatment plan when compared with that obtained by a CT alone. A limiting factor to the accuracy of TVD by PET/CT is organ and tumor motion, which is mainly due to patient respiration. In fact, respiratory motion has a degrading effect on PET/CT image quality, and this is also critical for TVD, as it can lead to possible tumor missing or undertreatment. Thus, the management of respiratory motion is becoming an increasingly essential component in RT treatment planning; indeed, it has been recognized that the use of personalized motion information can improve TVD and, consequently, permit increased tumor dosage while sparing surrounding healthy tissues and organs at risk. This review describes the methods used for motion management in PET/CT for radiation treatment planning. The article covers the following: (1) problems caused by organ and lesion motion owing to respiration, and the artifacts generated on CT, PET, and PET/CT images; (2) data acquisition and processing techniques used to manage respiratory motion in PET/CT studies; and (3) the use of personalized motion information for TVD and radiation treatment planning.

Respiratory gated PET/CT in a European multicentre retrospective study: added diagnostic value in detection and characterization of lung lesions

PURPOSE

The aim of our work is to evaluate the added diagnostic value of respiratory gated (4-D) positron emission tomography/computed tomography (PET/CT) in lung lesion detection/characterization in a large patient population of a multicentre retrospective study.

METHODS

The data of 155 patients (89 men, 66 women, mean age 63.9 ± 11.1 years) from 5 European centres and submitted to standard (3-D) and 4-D PET/CT were retrospectively analysed. Overall, 206 lung lesions were considered for the analysis (mean ± SD lesions dimension 14.7 ± 11.8 mm). Maximum standardized uptake values (SUV(max)) and lesion detectability were assessed for both 3-D and 4-D PET/CT studies; 3-D and 4-D PET/CT findings were compared to clinical follow-up as standard reference.

RESULTS

Mean ± SD 3-D and 4-D SUV(max) values were 5.2 ± 5.1 and 6.8 ± 6.1 (p < 0.0001), respectively, with an average percentage increase of 30.8 %. In 3-D PET/CT, 86 of 206 (41.7 %) lesions were considered positive, 70 of 206 (34 %) negative and 50 of 206 (24.3 %) equivocal, while in 4-D PET/CT 117 of 206 (56.8 %) lesions were defined as positive, 80 of 206 (38.8 %) negative and 9 of 206 (4.4 %) equivocal. In 34 of 50 (68 %) 3-D equivocal lesions follow-up data were available and the presence of malignancy was confirmed in 21 of 34 (61.8 %) lesions, while in 13 of 34 (38.2 %) was excluded. In 31 of these 34 controlled lesions, 20 of 34 (58.8 %) and 11 of 34 (32.4 %) were correctly classified by 4-D PET/CT as positive and negative, respectively; 3 of 34 (8.8 %) remained equivocal. With equivocal lesions classified as positive, the overall accuracy of 3-D and 4-D was 85.7 and 92.8 %, respectively, while the same figures were 80.5 and 94.2 % when equivocal lesions were classified as negative.

CONCLUSION

The respiratory gated PET/CT technique is a valuable clinical tool in diagnosing lung lesions, improving quantification and confidence in reporting, reducing 3-D undetermined findings and increasing the overall accuracy in lung lesion detection and characterization.

Can magnetic resonance image-guided focused ultrasound surgery replace local oncology treatments? A review

Magnetic resonance image-guided focused ultrasound surgery (MRgFUS) is an innovative technology in the new panorama of treatment using ultrasound. It combines two well-known and distinct methodologies: high-intensity focused ultrasound (HIFU) and a magnetic resonance imaging system (MRI). This review on MRgFUS is focused on the technical aspects and the current clinical applications in oncology. More precisely, the advantages/disadvantages of MRgFUS compared to other local approaches such as surgery and radiotherapy are discussed in detail.

PET/CT for radiotherapy: image acquisition and data processing

This paper focuses on acquisition and processing methods in positron emission tomography/computed tomography (PET/CT) for radiotherapy (RT) applications. The recent technological evolutions of PET/CT systems are described. Particular emphasis is dedicated to the tools needed for the patient positioning and immobilization, to be used in PET/CT studies as well as during RT treatment sessions. The effect of organ and lesion motion due to patient's respiration on PET/CT imaging is discussed. Breathing protocols proposed to minimize PET/CT spatial mismatches in relation to respiratory movements are illustrated. The respiratory gated (RG) 4D-PET/CT techniques, developed to measure and compensate for organ and lesion motion, are then introduced. Finally a description is provided of different acquisition and data processing techniques, implemented with the aim at improving: i) image quality and quantitative accuracy of PET images, and ii) target volume definition and treatment planning in RT, by using specific and personalised motion information.

Detection and compensation of organ/lesion motion using 4D-PET/CT respiratory gated acquisition techniques

PURPOSE

To describe the degradation effects produced by respiratory organ and lesion motion on PET/CT images and to define the role of respiratory gated (RG) 4D-PET/CT techniques to compensate for such effects.

METHODS

Based on the literature and on our own experience, technical recommendations and clinical indications for the use of RG 4D PET/CT have been outlined.

RESULTS

RG 4D-PET/CT techniques require a state of the art PET/CT scanner, a respiratory monitoring system and dedicated acquisition and processing protocols. Patient training is particularly important to obtain a regular breathing pattern. An adequate number of phases has to be selected to balance motion compensation and statistical noise. RG 4D PET/CT motion free images may be clinically useful for tumour tissue characterization, monitoring patient treatment and target definition in radiation therapy planning.

CONCLUSIONS

RG 4D PET/CT is a valuable tool to improve image quality and quantitative accuracy and to assess and measure organ and lesion motion for radiotherapy planning.

Image-based point spread function implementation in a fully 3D OSEM reconstruction algorithm for PET

The interest in positron emission tomography (PET) and particularly in hybrid integrated PET/CT systems has significantly increased in the last few years due to the improved quality of the obtained images. Nevertheless, one of the most important limits of the PET imaging technique is still its poor spatial resolution due to several physical factors originating both at the emission (e.g. positron range, photon non-collinearity) and at detection levels (e.g. scatter inside the scintillating crystals, finite dimensions of the crystals and depth of interaction). To improve the spatial resolution of the images, a possible way consists of measuring the point spread function (PSF) of the system and then accounting for it inside the reconstruction algorithm. In this work, the system response of the GE Discovery STE operating in 3D mode has been characterized by acquiring (22)Na point sources in different positions of the scanner field of view. An image-based model of the PSF was then obtained by fitting asymmetric two-dimensional Gaussians on the (22)Na images reconstructed with small pixel sizes. The PSF was then incorporated, at the image level, in a three-dimensional ordered subset maximum likelihood expectation maximization (OS-MLEM) reconstruction algorithm. A qualitative and quantitative validation of the algorithm accounting for the PSF has been performed on phantom and clinical data, showing improved spatial resolution, higher contrast and lower noise compared with the corresponding images obtained using the standard OS-MLEM algorithm.

Two-dimensional vs three-dimensional imaging in whole body oncologic PET/CT: a Discovery-STE phantom and patient study

AIM

To evaluate the performance of the positron emission tomography (PET)/computed tomography (CT) Discovery-STE (D-STE) scanner for lesion detectability in two-dimensional (2D) and three-dimensional (3D) acquisition.

METHODS

A NEMA 2001 Image-Quality phantom with 11 lesions (7-37 mm in diameter) filled with a solution of 18F (lesion/background concentration ratio: 4.4) was studied. 2D and 3D PET scans were sequentially acquired (10 min each) in list mode (LM). Each scan was unlisted into 4, 3 and 2-min scans. Ten [18F]FDG PET oncological patient studies were also evaluated. Each patient underwent a 3D PET/CT whole body scan, followed by a 2D PET scan (4 min LM) and a 3D PET scan (4 min LM) over a single field of view. Both 2D and 3D scans were unlisted in 3 and 2-min scans. Data were evaluated quantitatively by calculating quality measurements and qualitatively by two physicians who judged lesion detectability compared to statistical variations in background activity.

RESULTS

Quantitative and qualitative evaluations showed the superiority of 3D over 2D across all measures of quality. In particular, lesion detectability was better in 3D than in 2D at equal scan times and 3D acquisition provided images comparable in quality to 2D in approximately half the time. Interobserver variability was lower in evaluation of 3D scans and lesion shape and volume were better depicted.

CONCLUSION

In oncological applications, the D-STE system demonstrated good performance in 2D and 3D acquisition, while 3D exhibited better image quality, data accuracy and consistency of lesion detectability, resulting in shorter scan times and higher patient throughput.

Using deconvolution to improve PET spatial resolution in OSEM iterative reconstruction

OBJECTIVES

A novel approach to the PET image reconstruction is presented, based on the inclusion of image deconvolution during conventional OSEM reconstruction. Deconvolution is here used to provide a recovered PET image to be included as "a priori" information to guide OSEM toward an improved solution.

METHODS

Deconvolution was implemented using the Lucy-Richardson (LR) algorithm: Two different deconvolution schemes were tested, modifying the conventional OSEM iterative formulation: 1) We built a regularizing penalty function on the recovered PET image obtained by deconvolution and included it in the OSEM iteration. 2) After each conventional global OSEM iteration, we deconvolved the resulting PET image and used this "recovered" version as the initialization image for the next OSEM iteration. Tests were performed on both simulated and acquired data.

RESULTS

Compared to the conventional OSEM, both these strategies, applied to simulated and acquired data, showed an improvement in image spatial resolution with better behavior in the second case. In this way, small lesions, present on data, could be better discriminated in terms of contrast.

CONCLUSIONS

Application of this approach to both simulated and acquired data suggests its efficacy in obtaining PET images of enhanced quality.

PET/CT and radiotherapy

This article reviews the state of the art of PET/CT applications in radiotherapy, specifically its use in disease staging, patient selection, treatment planning and treatment evaluation. Diseases for which radiotherapy with radical intent is indicated will be considered, as well as those in which PET/CT may actually change the course of disease. The methodological and technological aspects of PET/CT in radiotherapy are discussed, focusing on the problem of target volume definition with CT and PET functional imaging and the problem of tumor motion with respect to imaging and dose delivery.

Early diagnosis of Alzheimer's disease using a grid implementation of statistical parametric mapping analysis

A quantitative statistical analysis of perfusional medical images may provide powerful support to the early diagnosis for Alzheimer's Disease (AD). A Statistical Parametric Mapping algorithm (SPM), based on the comparison of the candidate with normal cases, has been validated by the neurological research community to quantify ipometabolic patterns in brain PET/SPECT studies. Since suitable "normal patient" PET/SPECT images are rare and usually sparse and scattered across hospitals and research institutions, the Data Grid distributed analysis paradigm ("move code rather than input data") is well suited for implementing a remote statistical analysis use case, described in the present paper. Different Grid environments (LCG, AliEn) and their services have been used to implement the above-described use case and tackle the challenging problems related to the SPM-based early AD diagnosis.

Automatic registration of PET and CT studies for clinical use in thoracic and abdominal conformal radiotherapy

AIM

Implementation and validation of an automatic registration method based on mutual information (MI) for the integration of thoracic and abdominal positron emission tomography (PET)/computed tomography (CT) studies, with the purpose to facilitate in a clinical context the inclusion of PET metabolic information in conformal radiotherapy (RT).

METHODS

Registration was obtained by modeling a rigid spatial transformation between CT and PET transmission studies. The registration method was based on Normalized Mutual Information (NMI), by iteratively transforming the PET volume, until its optimal alignment to the CT study is achieved, in correspondence of the maximum of NMI. To avoid entrapment in local maxima and to improve convergence speed we introduced a multiresolution scheme. Accuracy of the proposed approach was investigated in experimental data, relative to phantom and patient studies, acquired in conditions similar to clinical situations.

RESULTS

In phantom studies the mean error in the 3D space is 3.6 mm (range 3-4 mm) in thoracic region and 3.2 mm (range 2.9-3.7 mm) in abdominal region, considerably less than PET spatial resolution. In patient studies the spatial mean error increases with respect to phantom studies (5.4 mm and 5.2 mm for thorax and abdomen, respectively) but remains comparable to the PET spatial resolution. The accuracy of spatial realignment was thus found adequate for the registration of PET/CT registration, if good patient repositioning was adopted.

CONCLUSIONS

The proposed registration method, based on MI, was validated for the integration of PET/CT studies of patients candidate for thoracic and abdominal conformal RT. The method is automatic and provided with a user interface, thus suitable for clinical use.