Improving the channeler ant model for lung CT analysis

The Channeler Ant Model (CAM) is an algorithm based on virtual ant colonies, conceived for the segmentation of complex structures with different shapes and intensity in a 3D environment. It exploits the natural capabilities of virtual ant colonies to modify the environment and communicate with each other by pheromone deposition. When applied to lung CTs, the CAM can be turned into a Computer Aided Detection (CAD) method for the identification of pulmonary nodules and the support to radiologists in the identification of early-stage pathological objects. The CAM has been validated with the segmentation of 3D artificial objects and it has already been successfully applied to the lung nodules detection in Computed Tomography images within the ANODE09 challenge. The model improvements for the segmentation of nodules attached to the pleura and to the vessel tree are discussed, as well as a method to enhance the detection of low-intensity nodules. The results on five datasets annotated with different criteria show that the analytical modules (i.e. up to the filtering stage) provide a sensitivity in the 80 - 90% range with a number of FP/scan of the order of 20. The classification module, although not yet optimised, keeps the sensitivity in the 70 - 85% range at about 10 FP/scan, in spite of the fact that the annotation criteria for the training and the validation samples are different

Particle beam microstructure reconstruction and coincidence discrimination in PET monitoring for hadron therapy

Positron emission tomography is one of the most mature techniques for monitoring the particles range in hadron therapy, aiming to reduce treatment uncertainties and therefore the extent of safety margins in the treatment plan. In-beam PET monitoring has been already performed using inter-spill and post-irradiation data, i.e., while the particle beam is off or paused. The full beam acquisition procedure is commonly discarded because the particle spills abruptly increase the random coincidence rates and therefore the image noise. This is because random coincidences cannot be separated by annihilation photons originating from radioactive decays and cannot be corrected with standard random coincidence techniques due to the time correlation of the beam-induced background with the ion beam microstructure. The aim of this paper is to provide a new method to recover in-spill data to improve the images obtained with full-beam PET acquisitions. This is done by estimating the temporal microstructure of the beam and thus selecting input PET events that are less likely to be random ones. The PET detector we used was the one developed within the INSIDE project and tested at the CNAO synchrotron-based facility. The data were taken on a PMMA phantom irradiated with 72 MeV proton pencil beams. The obtained results confirm the possibility of improving the acquired PET data without any external signal coming from the synchrotron or ad-hoc detectors

Prostaglandin E2 Stimulates the Expansion of Regulatory Hematopoietic Stem and Progenitor Cells in Type 1 Diabetes

Hematopoietic stem and progenitor cells (HSPCs) are multipotent stem cells that have been harnessed as a curative therapy for patients with hematological malignancies. Notably, the discovery that HSPCs are endowed with immunoregulatory properties suggests that HSPC-based therapeutic approaches may be used to treat autoimmune diseases. Indeed, infusion with HSPCs has shown promising results in the treatment of type 1 diabetes (T1D) and remains the only “experimental therapy” that has achieved a satisfactory rate of remission (nearly 60%) in T1D. Patients with newly diagnosed T1D have been successfully reverted to normoglycemia by administration of autologous HSPCs in association with a non-myeloablative immunosuppressive regimen. However, this approach is hampered by a high incidence of adverse effects linked to immunosuppression. Herein, we report that while the use of autologous HSPCs is capable of improving C-peptide production in patients with T1D, ex vivo modulation of HSPCs with prostaglandins (PGs) increases their immunoregulatory properties by upregulating expression of the immune checkpoint-signaling molecule PD-L1. Surprisingly, CXCR4 was upregulated as well, which could enhance HSPC trafficking toward the inflamed pancreatic zone. When tested in murine and human in vitro autoimmune assays, PG-modulated HSPCs were shown to abrogate the autoreactive T cell response. The use of PG-modulated HSPCs may thus provide an attractive and novel treatment of autoimmune diabetes

Online proton therapy monitoring: Clinical test of a Silicon-photodetector-based in-beam PET

Particle therapy exploits the energy deposition pattern of hadron beams. The narrow Bragg Peak at the end of range is a major advantage but range uncertainties can cause severe damage and require online verification to maximise the effectiveness in clinics. In-beam Positron Emission Tomography (PET) is a non-invasive, promising in-vivo technique, which consists in the measurement of the β+ activity induced by beam-tissue interactions during treatment, and presents the highest correlation of the measured activity distribution with the deposited dose, since it is not much influenced by biological washout. Here we report the first clinical results obtained with a state-of-the-art in-beam PET scanner, with on-the-fly reconstruction of the activity distribution during irradiation. An automated time-resolved quantitative analysis was tested on a lacrimal gland carcinoma case, monitored during two consecutive treatment sessions. The 3D activity map was reconstructed every 10 s, with an average delay between beam delivery and image availability of about 6 s. The correlation coefficient of 3D activity maps for the two sessions (above 0.9 after 120 s) and the range agreement (within 1 mm) prove the suitability of in-beam PET for online range verification during treatment, a crucial step towards adaptive strategies in particle therapy

Mast cell disorders, melanoma and pancreatic carcinoma: from a clinical observation to a brief review of the literature.

Mastocytosis can be associated with other clonal or non-clonal hematologic diseases as well as a variety of non-hematologic malignancies. A 75-year-old Caucasian male patient was referred to us with a 5-month history of neutrophilic leukocytosis and mild splenomegaly. He had developed a cutaneous melanoma sixteen years ago. According to the clinical and pathological features, a final diagnosis of systemic mastocytosis was established. The patient started treatment with interferon-α at a dose of 3 MIU/day, combined with low doses of prednisone. We observed a rapid disappearance of symptoms. Unfortunately, after 3 months a diagnosis of pancreatic adenocarcinoma was established. A review of the literature suggests that mastocytes could have a pivotal role in several malignancies. Different chemokines, mitogenic factors, chemical mediators of inflammation, and specific gene mutations could explain the association between mastocytosis and other hematologic and non-hematologic disorders. </p

Localization of anatomical changes in patients during proton therapy with in-beam PET monitoring: a voxel-based morphometry approach exploiting Monte Carlo simulations

Purpose: In-beam positron emission tomography (PET) is one of the modalities that can be used for in vivo noninvasive treatment monitoring in proton therapy. Although PET monitoring has been frequently applied for this purpose, there is still no straightforward method to translate the information obtained from the PET images into easy-to-interpret information for clinical personnel. The purpose of this work is to propose a statistical method for analyzing in-beam PET monitoring images that can be used to locate, quantify, and visualize regions with possible morphological changes occurring over the course of&nbsp;treatment. Methods: We selected a patient treated for squamous cell carcinoma (SCC) with proton therapy, to perform multiple Monte Carlo (MC) simulations of the expected PET signal at the start of treatment, and to study how the PET signal may change along the treatment course due to morphological changes. We performed voxel-wise two-tailed statistical tests of the simulated PET images, resembling the voxel-based morphometry (VBM) method commonly used in neuroimaging data analysis, to locate regions with significant morphological changes and to quantify the&nbsp;change. Results: The VBM resembling method has been successfully applied to the simulated in-beam PET images, despite the fact that such images suffer from image artifacts and limited statistics. Three dimensional probability maps were obtained, that allowed to identify interfractional morphological changes and to visualize them superimposed on the computed tomography (CT) scan. In particular, the characteristic color patterns resulting from the two-tailed statistical tests lend themselves to trigger alarms in case of morphological changes along the course of&nbsp;treatment. Conclusions: The statistical method presented in this work is a promising method to apply to PET monitoring data to reveal interfractional morphological changes in patients, occurring over the course of treatment. Based on simulated in-beam PET treatment monitoring images, we showed that with our method it was possible to correctly identify the regions that changed. Moreover we could quantify the changes, and visualize them superimposed on the CT scan. The proposed method can possibly help clinical personnel in the replanning procedure in adaptive proton therapy treatments

In-vivo range verification analysis with in-beam PET data for patients treated with proton therapy at CNAO

Morphological changes that may arise through a treatment course are probably one of the most significant sources of range uncertainty in proton therapy. Non-invasive in-vivo treatment monitoring is useful to increase treatment quality. The INSIDE in-beam Positron Emission Tomography (PET) scanner performs in-vivo range monitoring in proton and carbon therapy treatments at the National Center of Oncological Hadrontherapy (CNAO). It is currently in a clinical trial (ID: NCT03662373) and has acquired in-beam PET data during the treatment of various patients. In this work we analyze the in-beam PET (IB-PET) data of eight patients treated with proton therapy at CNAO. The goal of the analysis is twofold. First, we assess the level of experimental fluctuations in inter-fractional range differences (sensitivity) of the INSIDE PET system by studying patients without morphological changes. Second, we use the obtained results to see whether we can observe anomalously large range variations in patients where morphological changes have occurred. The sensitivity of the INSIDE IB-PET scanner was quantified as the standard deviation of the range difference distributions observed for six patients that did not show morphological changes. Inter-fractional range variations with respect to a reference distribution were estimated using the Most-Likely-Shift (MLS) method. To establish the efficacy of this method, we made a comparison with the Beam's Eye View (BEV) method. For patients showing no morphological changes in the control CT the average range variation standard deviation was found to be 2.5&nbsp;mm with the MLS method and 2.3&nbsp;mm with the BEV method. On the other hand, for patients where some small anatomical changes occurred, we found larger standard deviation values. In these patients we evaluated where anomalous range differences were found and compared them with the CT. We found that the identified regions were mostly in agreement with the morphological changes seen in the CT scan