Search

Image-based data mining (IBDM) and voxel-based analysis (VBA) have shown great promise in the retrospective analysis of routine clinical data, offering a way to analyze a patient population without selection. In radiation therapy, IBDM analyzes whole dose distributions for their effect on a given outcome with no prior assumptions. Recent extensions in IBDM methodologies include per voxel survival analyses, allowing the generation of more robust and testable hypotheses. An essential aspect to produce solid conclusions includes applying the correct statistical techniques to account for multiple testing. There is a growing interest in applying IBDM/VBA techniques in radiation therapy, which is a relatively new area with limited examples in the literature. We present this editorial to discuss guidelines for best practice. In doing so, we highlight 3 recently published papers applying IBDM techniques to radiation therapy data 1 , 2 , 3 and suggest alternative, more robust analysis methods.

PurposeTo evaluate the feasibility and sensitivity of multimodality PET/CT and MRI imaging for non-invasive characterization of brain microglial/macrophage activation occurring during the acute phase in a mouse model of relapsing remitting multiple sclerosis (RR-MS) using [18F]DPA-714, a selective radioligand for the 18-kDa translocator protein (TSPO), superparamagnetic iron oxide particles (SPIO), and ex vivo immunohistochemistry.MethodsExperimental autoimmune encephalomyelitis (EAE) was induced in female SJL/J mice by immunization with PLP139–151. Seven symptomatic EAE mice and five controls underwent both PET/CT and MRI studies between 11 and 14 days post-immunization. SPIO was injected i.v. in the same animals immediately after [18F]DPA-714 and MRI acquisition was performed after 24 h. Regional brain volumes were defined according to a mouse brain atlas on co-registered PET and SPIO-MRI images. [18F]DPA-714 standardized uptake value (SUV) ratios (SUVR), with unaffected neocortex as reference, and SPIO fractional volumes (SPIO-Vol) were generated. Both SUVR and SPIO-Vol values were correlated with the clinical score (CS) and among them. Five EAE and four control mice underwent immunohistochemical analysis with the aim of identifying activated microglia/macrophage and TSPO expressions.ResultsSUVR and SPIO-Vol values were significantly increased in EAE compared with controls in the hippocampus (p p p p p p ConclusionsThese preliminary results suggest that both activated microglia and infiltrated macrophages are present in vulnerable brain regions during the acute phase of PLP-EAE and contribute to disease severity. Both [18F]DPA-714-PET and SPIO-MRI appear suitable modalities for preclinical study of neuroinflammation in MS mice models.

A Special Issue of Physica Medica – European Journal of Medical Physics, focused on some important points of contact between the world of magnetic resonance and that of medical physics, was published during 2021. This Editorial describes and comments on the content of this Focus Issue, which contains articles from leading groups invited by the Guest Editors.

Recently, 2D or 3D methods for dose distribution analysis have been proposed as evolutions of the Dose Volume Histogram (DVH) approaches. Those methods, collectively referred to as pixel- or voxel-based (VB) methods, evaluate local dose response patterns and go beyond the organ-based philosophy of Normal Tissue Complication Probability (NTCP) modelling. VB methods have been introduced in the context of radiation oncology in the very last years following the virtuous example of neuroimaging experience. In radiation oncology setting, dose mapping is a suitable scheme to compare spatial patterns of local dose distributions between patients who develop toxicity and who do not. In this critical review, we present the methods that include spatial dose distribution information for evaluating different toxicity endpoints after radiation therapy. The review addresses two main topics. First, the critical aspects in dose map building, namely the spatial normalization of the dose distributions from different patients. Then, the issues related to the actual dose map comparison, i.e. the viable options for a robust VB statistical analysis and the potential pitfalls related to the adopted solutions. To elucidate the different theoretical and technical issues, the covered topics are illustrated in relation to practical applications found in the existing literature. We conclude the overview on the VB philosophy in radiation oncology by introducing new phenomenological approaches to NTCP modelling that accounts for inhomogeneous organ radiosensitivity.

Purpose Radiation pneumonitis (RP) is commonly associated with thoracic radiation therapy, and its incidence is related to dose and volume of the normal lung in the path of radiation. Our aim was to investigate dose patterns associated with RP in patients enrolled in a randomized trial of intensity modulated radiation therapy (IMRT) versus passive scattering proton therapy (PSPT) for locally advanced non-small cell lung cancer. Methods We analyzed 178 patients prospectively treated with PSPT or IMRT for non-small cell lung cancer to a prescribed dose of 66 or 74 Gy in conventional daily fractionation with concurrent chemotherapy. Forty patients (22%) developed clinically symptomatic RP. Voxel-based analysis of local dose differences was done with a nonparametric permutation test accounting for multiple comparisons. From the obtained 3-dimensional significance maps, we derived clusters of voxels that exhibited dose differences between groups at a statistical significance level of 0.05. Results The voxel-based analysis highlighted that (1) significant dose differences between patients with and without RP were found in the lower part of the lungs and in the heart and (2) the anatomic regions significantly spared by PSPT and the clusters in which doses were significantly correlated with RP development were disjoint. Conclusions The analyzed trial data provide an unprecedented opportunity to substantiate previous hypotheses regarding the role of the heart and the lower lungs in the development of RP. Knowledge of this relationship between RP and thoracic regional radiosensitivity should be considered in clinical practice and in the design of future trials.

Purpose To present a new formalism for a robust computation of Dose-Surface Histograms (DSHs) to be exploited in the analysis of surface effects in radiation induced toxicity phenomena. Methods A new formal recipe for the DSH extraction is described. It is based on the computation of the Dose-Volume Histogram (DVH) on a 3D structure in the limit of vanishing thickness to approach the two-dimensional organ manifold. The theory is customized for the application to skin description. Results The derived formalism resulted in a redefinition of the generalized equivalent uniform dose (gEUD) and, accordingly, in an extension of the scope of the classical Lyman-Kutcher-Burman (LKB) Normal Tissue Complication Probability (NTCP) to a DSH-based toxicity modeling. Conclusions Our approach properly fits the intrinsic 3D nature of the DSH computation issue, and guarantees the rotational invariance and the robustness of the results. The proposed formalism can be easily implemented in treatment planning systems for dose optimization and potentially paves the way to a consistent analysis of radiation-induced morbidity endpoints related to surface effects in hollow organs.

Proper regulation of neurogenesis, the process by which new neurons are generated from neural stem and progenitor cells (NS/PCs), is essential for embryonic brain development and adult brain function. The transcription regulator Patz1 is ubiquitously expressed in early mouse embryos and has a key role in embryonic stem cell maintenance. At later stages, the detection of Patz1 expression mainly in the developing brain suggests a specific involvement of Patz1 in neurogenesis. To address this point, we first got insights in Patz1 expression profile in different brain territories at both embryonic and postnatal stages, evidencing a general decreasing trend with respect to time. Then, we performed in vivo and ex vivo analysis of Patz1-knockout mice, focusing on the ventricular and subventricular zone, where we confirmed Patz1 enrichment through the analysis of public RNA-seq datasets. Both embryos and adults showed a significant reduction in the number of Patz1-null NS/PCs, as well as of their self-renewal capability, compared to controls. Consistently, molecular analysis revealed the downregulation of stemness markers in NS/PCs derived from Patz1-null mice. Overall, these data demonstrate the requirement of Patz1 for NS/PC maintenance and proliferation, suggesting new roles for this key transcription factor specifically in brain development and plasticity, with possible implications for neurodegenerative disorders and glial brain tumors.

Purpose To investigate thoracic dose–response patterns for pericardial effusion (PCE) and mortality in patients treated for locally advanced Non-Small-Cell Lung Cancer (NSCLC) by Intensity Modulated RT (IMRT) or Passive-Scattering Proton Therapy (PSPT). Methods Among 178 patients, 43.5% developed grade ≥ 2 PCE. Clinical and dosimetric factors associated with PCE or overall survival (OS) were identified via multi-variable Cox proportional hazards modeling. The Voxel-Based Analyses (VBAs) of local dose differences between patients with and without PCE and mortality was performed. The robustness of VBA results was assessed by a novel characterization of spatial properties of dose distributions based on probabilistic independent component analysis (PICA) and connectograms. Results Several non-dosimetric variables were selected by the multivariable analysis for the considered outcomes, while the time-dependent PCE onset was uncorrelated with the OS (p = 0.34) at a multi-variable Cox analysis. Despite the significant PSPT dosimetric advantage, the RT technique did not affect the occurrence of PCE or OS. VBAs highlighted largely overlapping clusters significantly associated with PCE endpoints in heart and lungs. No significant dosimetric patterns related to mortality endpoints were found. PICA identified 43 components homogeneously scattered within thorax, while connectograms showed modest correlations between doses in main cardio-pulmonary substructures. Conclusions Spatially resolved analysis highlighted dose patterns related to radiation-induced cardiac toxiciy and the observed organ-based dose–response mismatch in PSPT and IMRT. Indeed, the thoracic regions spared by PSPT poorly overlapped with the areas involved in PCE development, as highlited by VBA. PICA and connectograms proved valuable tools for assessing the robusteness of obtained VBA inferences.

Simple Summary The pathophysiology of radiation pneumonitis (RP) after thoracic cancer radiation treatments is still not completely understood although the identification of underlying RP mechanisms may improve the therapeutic window of thoracic cancer patients. The aim of our retrospective study was to explore the dose–response patterns associated with RP by a multi-center voxel-based analysis. In a heterogeneously treated population of 382 thoracic cancer patients, we confirmed the previously described heart–lung interaction in the development of RP. The empowerment of VBA with a novel description of dose map spatial properties based on probabilistic independent component analysis (PICA) and connectograms provided valuable additional and independent information on the radiobiology of RP. Abstract This study investigates the dose–response patterns associated with radiation pneumonitis (RP) in patients treated for thoracic malignancies with different radiation modalities. To this end, voxel-based analysis (VBA) empowered by a novel strategy for the characterization of spatial properties of dose maps was applied. Data from 382 lung cancer and mediastinal lymphoma patients from three institutions treated with different radiation therapy (RT) techniques were analyzed. Each planning CT and biologically effective dose map (α/β = 3 Gy) was spatially normalized on a common anatomical reference. The VBA of local dose differences between patients with and without RP was performed and the clusters of voxels with dose differences that significantly correlated with RP at a p-level of 0.05 were generated accordingly. The robustness of VBA inference was evaluated by a novel characterization for spatial properties of dose maps based on probabilistic independent component analysis (PICA) and connectograms. This lays robust foundations to the obtained findings that the lower parts of the lungs and the heart play a prominent role in the development of RP. Connectograms showed that the dataset can support a radiobiological differentiation between the main heart and lung substructures.

The spread of the novel human respiratory coronavirus (SARS-CoV-2) is a global public health emergency. There is no known successful treatment as of this time, and there is a need for medical options to mitigate this current epidemic. SARS-CoV-2 uses the angiotensin-converting enzyme 2 (ACE2) receptor and is primarily trophic for the lower and upper respiratory tract. A number of current studies on COVID-19 have demonstrated the substantial increase in pro-inflammatory factors in the lungs during infection. The virus is also documented in the central nervous system and, particularly in the brainstem, which plays a key role in respiratory and cardiovascular function. Currently, there are few antiviral approaches, and several alternative drugs are under investigation. Two of these are Idelalisib and Ebastine, already proposed as preventive strategies in airways and allergic diseases. The interesting and evolving potential of phosphoinositide 3-kinase δ (PI3Kδ) inhibitors, together with Ebastine, lies in their ability to suppress the release of pro-inflammatory cytokines, such as IL-1β, IL-8, IL-6, and TNF-α, by T cells. This may represent an optional therapeutic choice for COVID-19 to reduce inflammatory reactions and mortality, enabling patients to recover faster. This concise communication aims to provide new potential therapeutic targets capable of mitigating and alleviating SARS-CoV-2 pandemic infection.

editorial comment of the potential effect of COVID 19 on radiation related lung toxicity

Background/aim Our group has previously demonstrated, in in vitro and in vivo studies on triple-negative breast cancer, that morphine promoted breast cancer progression whereas naloxone was able to reduce it. In this subsequent investigation, we aimed to assess the combinatorial effects of these two drugs in an animal model of triple negative breast cancer. Materials and methods In order to evaluate the in vivo effects of the combination of morphine and naloxone in human breast cancer, a mouse model of human triple-negative breast cancer was generated by injecting the MDA-MB-231 cells subcutaneously in nude mice. Naloxone and morphine were daily intraperitoneally co-injected in mice for 4 weeks at two different doses. Micro-vessel formation was detected by fluorescein isothiocyanate-dextran (100 μl) injected into the lateral tail vein of mice and confirmed by immunohistochemistry for PECAM-1 on mice tumor sections. Results In vivo experiments showed that naloxone was able to counteract the promoting effects of morphine on tumor growth. No impairment of micro-vessel formation in tumors of mice treated with the two drugs was observed. Conclusion Herein, we demonstrated that naloxone was able to counteract the promoting effects of morphine on tumor growth without impairing micro-vessel formation.

Introduction: Aim of this study is to elucidate possible mechanisms of extrapyramidal damage in Fabry Disease (FD), a condition in which involvement of the motor system has been recently suggested, by simultaneously assessing morphometric and susceptibility changes of striatonigral pathway and their possible correlations with clinical variables. Methods: In this cross-sectional study, we investigated possible differences in terms of Quantitative Susceptibility Mapping (QSM) values and volumes of different extrapyramidal relays, including striatum and substantia nigra (SN), in 30 FD patients (M/F = 11/19, mean age 42.6 +/- 12.2) and 37 healthy controls (HC) (M/F = 16/21, mean age 43.2 +/- 14.6). Patients underwent a clinical examination for the study of different motor functions, and the relationship between MRI and clinical variables was tested using the Spearman's coefficient. Results: Compared to HC, FD patients showed an increase in susceptibility values of the SN (p < 0.001) and striatum (p = 0.001), while no difference emerged for the other tested extrapyramidal structures, suggesting their relative sparing. The increased susceptibility was coupled to a reduced volume of the SN (p < 0.001), but not of the striatum (p = 0.34). Finally, no significant correlation emerged when probing the relationship between these modifications and the clinical variables. Conclusion: In FD patients, susceptibility and volumetric alterations are present throughout the extrapyramidal pathway, with the SN being particularly affected by these changes. Such results are in line with the subtle extrapyramidal involvement recently suggested in FD, and could further contribute to the understanding of the physiopathological bases of cerebral involvement in FD.

Gut microbiota, a group of 1014 bacteria, eukaryotes and virus living in gastrointestinal tract, is crucial for many physiological processes in particular plays an important role in inflammatory and immune reactions. Several internal and external factors can influence this population, and shifts in their composition, have been demonstrated to contribute and affect different diseases. During dysbiosis several bacteria related to inflammation, one of the most necessary factors in carcinogenesis; it has been shown that some bacterial strains through deregulation of different signals/pathways may affect tumor development through the production of many factors. Gut microbiota might be considered as a holistic hub point for cancer development: direct and indirect involvements have been studying in several neoplasms such as colon rectal cancer, hepatocellular carcinoma and breast cancer. This review discuss over the evidence of crosstalk between gut microbiota and cancer, its ability to modulate chemotherapy, radiotherapy and immunotherapy, and the possibility that the intestinal microbial is a new target for therapeutic approaches to improve the prognosis and quality of life of cancer patients.

Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD (p = 0.027). Multivariable logistic modeling resulted in a single variable model including S 20Gy, the relative skin surface receiving more than 20 Gy (OR = 31.4). The cut off for S 20Gy was 1.1% of the BSA. LKB model parameters were TD50 = 9.5 Gy, m = 0.24, n = 0.62. Both NTCP models showed comparably high prediction and calibration performances. Despite skin toxicity has long been considered a potential limiting factor in the clinical use of PSPT, no significant differences in RD incidence was found between RT modalities. Once externally validated, the availability of NTCP models for prediction of severe RD may advance treatment planning optimization.

To devise a novel Spatial Normalization framework for Voxel-based analysis (VBA) in brain radiotherapy. VBAs rely on accurate spatial normalization of different patients' planning CTs on a common coordinate system (CCS). The cerebral anatomy, well characterized by MRI, shows instead poor contrast in CT, resulting in potential inaccuracies in VBAs based on CT alone.We analyzed 50 meningioma patients treated with proton-therapy, undergoing planning CT and T1-weighted (T1w) MRI. The spatial normalization pipeline based on MR and CT images consisted in: intra-patient registration of CT to T1w, inter-patient registration of T1w to MNI space chosen as CCS, doses propagation to MNI. The registration quality was compared with that obtained by Statistical Parametric Mapping software (SPM), used as benchmark. To evaluate the accuracy of dose normalization, the dose organ overlap (DOO) score was computed on gray matter, white matter and cerebrospinal fluid before and after normalization. In addition, the trends in the DOOs distribution were investigated by means of cluster analysis.The registration quality was higher for the proposed method compared to SPM (p 0.001). The DOO scores showed a significant improvement after normalization (p 0.001). The cluster analysis highlighted 2 clusters, with one of them including the majority of data and exhibiting acceptable DOOs.Our study presents a robust tool for spatial normalization, specifically tailored for brain dose VBAs. Furthermore, the cluster analysis provides a formal criterion for patient exclusion in case of non-acceptable normalization results. The implemented framework lays the groundwork for future reliable VBAs in brain irradiation studies.

Purpose To develop normal tissue complication probability (NTCP) models for radiation-induced alopecia (RIA) in brain tumor patients treated with proton therapy (PT). Methods and materials We analyzed 116 brain tumor adult patients undergoing scanning beam PT (median dose 54 GyRBE; range 36–72) for CTCAE v.4 grade 2 (G2) acute (≤90 days), late (>90 days) and permanent (>12 months) RIA. The relative dose-surface histogram (DSH) of the scalp was extracted and used for Lyman-Kutcher-Burman (LKB) modelling. Moreover, DSH metrics (Sx: the surface receiving ≥ X Gy, D2%: near maximum dose, Dmean: mean dose) and non-dosimetric variables were included in a multivariable logistic regression NTCP model. Model performances were evaluated by the cross-validated area under the receiver operator curve (ROC-AUC). Results Acute, late and permanent G2-RIA was observed in 52%, 35% and 19% of the patients, respectively. The LKB models showed a weak dose-surface effect (0.09 ≤ n ≤ 0.19) with relative steepness 0.29 ≤ m ≤ 0.56, and increasing tolerance dose values when moving from acute and late (22 and 24 GyRBE) to permanent RIA (44 GyRBE). Multivariable modelling selected S21Gy for acute and S25Gy, for late G2-RIA as the most predictive DSH factors. Younger age was selected as risk factor for acute G2-RIA while surgery as risk factor for late G2-RIA. D2% was the only variable selected for permanent G2-RIA. Both LKB and logistic models exhibited high predictive performances (ROC-AUCs range 0.86–0.90). Conclusion We derived NTCP models to predict G2-RIA after PT, providing a comprehensive modelling framework for acute, late and permanent occurrences that, once externally validated, could be exploited for individualized scalp sparing treatment planning strategies in brain tumor patients.

Background Platelet-rich-plasma (PRP) is largely used, thanks to its properties, as wound therapy after surgical resection. Several studies and clinical findings have demonstrated that the PRP can accelerate the regeneration and the repair of tissues through the action of the platelet-derived growth factors. Material and methods Our study aimed to investigate the effects of PRP-gel on the rate of tumor relapse by using a mouse model of Human Fibrosarcoma (HF). The radical resection of tumors of mice was conducted under fluorescence-guidance (FGR) by using MacroFluo microscope, after a primary tumor removal with bright-light surgery (BLS). Results It was found that the lesion recurrence and the tumor growth were reduced in mice treated with PRP observed in each group of treatment (50%) after 30 days from tumor excision, respect to controls (without statistical significance; p = 0.12). The histopathological and immune-histochemical analysis did not report differences in cellular morphology between the tumors of control and PRP-treated mice. Conclusion Our data suggest that PRP-gel, used as an adjuvant treatment for the stimulation of tissue repair and speed up recovery, can impair tumor growth and slow the tumor.

Thoracic radiation therapy (RT) is often associated with lung side effects, whose etiology is still controversial. Our aim was to explore correlations between local dose in the thoracic anatomy and the radiation-induced lung damage (RILD). To this end, we designed a robust scheme for voxel-based analysis (VBA) to explore dose patterns associated with RILD in non-small-cell lung cancer (NSCLC) patients receiving stereotactic body RT (SBRT). We analyzed 106 NSCLC SBRT patients (median prescription dose: 50 Gy; range: [40-54] Gy) in 4 fractions (range: [3-5]) with clinical and dosimetric records suitable for the analysis. The incidence of acute G1 RILD (RTOG grade ⩾ 1) was 68%. Each planning CT and dose map was spatially normalized to a common anatomical reference using a B-spline inter-patient registration algorithm after masking the gross tumor volume. The tumor-subtracted dose maps were converted into biologically effective dose maps (α/β = 3 Gy). VBA was performed according to a non-parametric permutation test accounting for multiple comparison, based on a cluster analysis method. The underlying general linear model of RILD was designed to include dose maps and each non-dosimetric variable significantly correlated with RILD. The clusters of voxels with dose differences significantly correlated with RILD at a given p -level (S p ) were generated. The only non-dosimetric variable significantly correlated with RILD was the chronic obstructive pulmonary disease (p = 0.034). Patients with G1 RILD received significantly (p ⩽ 0.05) higher doses in two voxel clusters S 0.05 in the lower-left lung (14 cm3) and in an area (64 cm3) largely included within the ventricles. The applied VBA represents a powerful tool to probe the dose susceptibility of inhomogeneous organs in clinical radiobiology studies. The identified subregions with dose differences associated with G1 RILD in both the heart and lower lungs endorse a trend of previously reported hypotheses on lung toxicity radiobiology.

The contemporary approach to the management of a cancer patient requires an "ab initio" involvement of different medical domains in order to correctly design an individual patient's pathway toward cure. With new therapeutic tools in every medical field developing faster than ever before the patient care outcomes can be achieved if all surgical, drug, and radiation options are considered in the design of the appropriate therapeutic strategy for a given patient. Radiation therapy (RT) is a clinical discipline in which experts from different fields continuously interact in order to manage the multistep process of the radiation treatment. RT is found to be an appropriate intervention for diverse indications in about 50% of cancer patients during the course of their disease. Technologies are essential in dealing with the complexity of RT treatments and for driving the increasingly sophisticated RT approaches becoming available for the treatment of Cancer. High conformal techniques, namely intensity modulated or volumetric modulated arc techniques, ablative techniques (Stereotactic Radiotherapy and Stereotactic Radiosurgery), particle therapy (proton or carbon ion therapy) allow for success in treating irregularly shaped or critically located targets and for the sharpness of the dose fall-off outside the target. The advanced on-board imaging, including real-time position management systems, makes possible image-guided radiation treatment that results in substantial margin reduction and, in select cases, implementation of an adaptive approach. The therapeutic gains of modern RT are also due in part to the enhanced anticancer activity obtained by coadministering RT with chemotherapy, targeted molecules, and currently immune checkpoints inhibitors. These main clinically relevant steps forward in Radiation Oncology represent a change of gear in the field that may have a profound impact on the management of cancer patients.

Mathematical models of normal tissue complication probability (NTCP) able to robustly predict radiation-induced morbidities (RIM) play an essential role in the identification of a personalized optimal plan, and represent the key to maximizing the benefits of technological advances in radiation therapy (RT). Most modern RT techniques pose, however, new challenges in estimating the risk of RIM. The aim of this report is to schematically review NTCP models in the framework of advanced radiation therapy techniques. Issues relevant to hypofractionated stereotactic body RT and ion beam therapy are critically reviewed. Reirradiation scenarios for new or recurrent malignances and NTCP are also illustrated. A new phenomenological approach to predict RIM is suggested.

Background: Different modern radiation therapy treatment solutions for breast cancer (BC) and regional nodal irradiation (RNI) have been proposed. In this study, we evaluate the potential reduction in radiation-induced skin morbidity obtained by intensity modulated proton therapy (IMPT) compared with intensity modulated photon therapy (IMXT) for left-side BC and RNI. Material and Methods: Using CT scans from 10 left-side BC patients, treatment plans were generated using IMXT and IMPT techniques. A dose of 50 Gy (or Gy [RBE] for IMPT) was prescribed to the target volume (involved breast, the internal mammary, supraclavicular, and infraclavicular nodes). Two single filed optimization IMPT (IMPT1 and IMPT2) plans were calculated without and with skin optimization. For each technique, skin dose-metrics were extracted and normal tissue complication probability (NTCP) models from the literature were employed to estimate the risk of radiation-induced skin morbidity. NTCPs for relevant organs-at-risk (OARs) were also considered for reference. The non-parametric Anova (Friedman matched-pairs signed-rank test) was used for comparative analyses. Results: IMPT improved target coverage and dose homogeneity even if the skin was included into optimization strategy (HIIMPT2 = 0.11 vs. HIIMXT = 0.22 and CIIMPT2 = 0.96 vs. CIIMXT = 0.82, p < .05). A significant relative skin risk reduction (RR = NTCPIMPT/NTCPIMXT) was obtained with IMPT2 including the skin in the optimization with a RR reduction ranging from 0.3 to 0.9 depending on the analyzed skin toxicity endpoint/model. Both IMPT plans attained significant OARs dose sparing compared with IMXT. As expected, the heart and lung doses were significantly reduced using IMPT. Accordingly, IMPT always provided lower NTCP values. Conclusions: IMPT guarantees optimal target coverage, OARs sparing, and simultaneously minimizes the risk of skin morbidity. The applied model-based approach supports the potential clinical relevance of IMPT for left-side BC and RNI and might be relevant for the setup of cost-effectiveness evaluation strategies based on NTCP predictions, as well as for establishing patient selection criteria.

In radiation oncology, the need for a modern Normal Tissue Complication Probability (NTCP) philosophy to include voxel-based evidence on organ radio-sensitivity (RS) has been acknowledged. Here a new formalism (Probabilistic Atlas for Complication Estimation, PACE) to predict radiation-induced morbidity (RIM) is presented. The adopted strategy basically consists in keeping the structure of a classical, phenomenological NTCP model, such as the Lyman-Kutcher-Burman (LKB), and replacing the dose distribution with a collection of RIM odds, including also significant non-dosimetric covariates, as input of the model framework. The theory was first demonstrated in silico on synthetic dose maps, classified according to synthetic outcomes. PACE was then applied to a clinical dataset of thoracic cancer patients classified for lung fibrosis. LKB models were trained for comparison. Overall, the obtained learning curves showed that the PACE model outperformed the LKB and predicted synthetic outcomes with an accuracy >0.8. On the real patients, PACE performance, evaluated by both discrimination and calibration, was significantly higher than LKB. This trend was confirmed by cross-validation. Furthermore, the capability to infer the spatial pattern of underlying RS map for the analyzed RIM was successfully demonstrated, thus paving the way to new perspectives of NTCP models as learning tools.

Simple Summary Dyspnea is a common symptomatic side-effect of thoracic radiation therapy. The aim of this study is to build a predictive model of any-grade radiation-induced dyspnea within six months after stereotactic body radiation therapy in patients treated for non-small cell lung cancer. The occurrence of pre-treatment chronic obstructive pulmonary disease and higher relative lungs volume receiving more than 15 Gy as well as heart volume were shown to be risk factors for dyspnea. The obtained results encourage further studies on the topic, which could validate the present organ-based findings and explore the voxel-based landscape of radiation dose sensitivity in the development of dyspnea. Abstract In this study, we investigated the prognostic factors for radiation-induced dyspnea after hypo-fractionated radiation therapy (RT) in 106 patients treated with Stereotactic Body RT for Non-Small-Cell Lung Cancer (NSCLC). The median prescription dose was 50 Gy (range: 40–54 Gy), delivered in a median of four fractions (range: 3–12). Dyspnea within six months after SBRT was scored according to CTCAE v.4.0. Biologically Effective Dose (α/β = 3 Gy) volume histograms for lungs and heart were extracted. Dosimetric parameters along with patient-specific and treatment-related factors were analyzed, multivariable logistic regression method with Leave-One-Out (LOO) internal validation applied. Model performance was evaluated by the area under the receiver operating characteristic (ROC) curve (AUC) and calibration plot parameters. Fifty-seven patients (53.8%) out of 106 developed dyspnea of any grade after SBRT (25/57 grade ≥ 2 cases). A three-variable predictive model including patient comorbidity (COPD), heart volume and the relative lungs volume receiving more than 15 Gy was selected. The model displays an encouraging performance given by a training ROC-AUC = 0.71 [95%CI 0.61–0.80] and a LOO-ROC-AUC = 0.64 [95%CI 0.53–0.74]. Further modeling efforts are needed for dyspnea prediction in hypo-fractionated treatments in order to identify patients at high risk for developing lung toxicity more accurately.

Different studies showed correlations between gadolinium-based contrast agent (GBCA) administrations and dentate nucleus (DN) T1-weighted hyperintensity. The clinical impact of gadolinium retention, however, is still largely unknown. The aim of this study was to investigate relations between MRI and clinical disability in relapsing–remitting multiple sclerosis (RR-MS) patients. In this retrospective study, clinical data were obtained from 74 RR-MS patients at baseline and after a mean follow-up time of 3.6 years, including the expanded disability status scale (EDSS) score and its change (ΔEDSS). Patients were considered showing clinical worsening if they score a ΔEDSS ≥ 1 (for baseline EDSS ≤ 5.5) or ΔEDSS ≥ 0.5 (for baseline EDSS > 5.5). From the MRI data, the presence of bilateral DN hyperintensity was recorded along with the calculation of longitudinal relaxation rate (R1) maps. Patients with DN hyperintensity showed similar ΔEDSS change compared to those without visible changes on T1-weighted images (p = 0.32). Similarly, no DN-R1 difference was found comparing stable patients with those showing a significant clinical worsening (p = 0.54). Finally, no significant effect of DN-R1 values explained the variance in ΔEDSS (p = 0.76), thus suggesting their independence from the clinical outcome. MS patients with DN hyperintensity show similar EDSS changes compared to subjects without DN high-signal intensity. Furthermore, mean DN-R1 values of patients with significant clinical worsening were comparable to those of stable subjects and were unrelated to clinical disability. Taken together, these findings suggest that gadolinium retention in the brain of MS patients does not affect their clinical worsening, expressed by the EDSS change.

Ulcerative dermatitis (UD) is an idiopathic, spontaneous and progressive disease typically affecting C57BL/6 aged mice with an unknown aetiopathogenesis. For this study, we evaluated 25 cases of UD in C57BL/6NCrl-Tg(HMGA1P6)1Pg mice. Formalin-fixed, paraffin-embedded skin samples were submitted to morphological investigations. Immunohistochemical analysis was performed to characterize and quantify inflammatory cells using CD3, CD45/B220, CD4, CD8 and IL-17 antibodies. Mast cell-bound IgE was investigated by immunofluorescence, whereas serum and cryopreserved skin samples were collected for molecular analysis. Student's t-test (two-tailed) was performed to assess significant differences between the two groups. Affected skin showed extensive areas of ulceration and diffuse, severe and mixed inflammatory infiltrates. No relevant changes were observed in control mice. Immunohistochemical analysis showed a predominant CD3 + CD4 + leukocyte population with fewer CD45/B220 and IL-17 immunolabelled cells and mast cell-bound IgE. Increases in TNFα, IL-1β and Il-6 mRNA expression were observed in the skin of affected animals compared to controls. Serum TNFα and IL-6 did not vary between affected and control mice. Inflammatory infiltrates and cytokine expression were consistent with both Th2/IgE and Th17 differentiation, a typical pattern of a type I hypersensitivity reaction. Overall, our data suggest an allergic-based aetiopathogenesis of UD in C57BL/6NCrl-Tg(HMGA1P6)1Pg mice.

POZ/BTB and AT-hook-containing zinc finger protein 1 (PATZ1) is an emerging cancer-related gene that is downregulated in different human malignancies, including thyroid cancer, where its levels gradually decrease going from papillary thyroid carcinomas (PTC) to poorly differentiated and undifferentiated highly aggressive anaplastic carcinomas (ATC). The restoration of PATZ1 expression in thyroid cancer cells reverted their malignant phenotype by inducing mesenchymal-to-epithelial transition, thus validating a tumor suppressor role for PATZ1 and suggesting its involvement in thyroid cancer progression. Here, we investigated the consequences of the homozygous and heterozygous loss of PATZ1 in the context of a mouse modeling of PTC, represented by mice carrying the RET/PTC1 oncogene under the thyroid specific control of the thyroglobulin promoter RET/PTC1 (RET/PTC1TG). The phenotypic analysis of RET/PTC1TG mice intercrossed with Patz1-knockout mice revealed that deficiency of both Patz1 alleles enhanced thyroid cancer incidence in RET/PTC1TG mice, but not the heterozygous knockout of the Patz1 gene. However, both RET/PTC1TG;Patz1+/- and RET/PTC1TG;Patz1-/- mice developed a more aggressive thyroid cancer phenotype-characterized by higher Ki-67 expression, presence of ATCs, and increased incidence of solid variants of PTC-than that shown by RET/PTC1TG; Patz1+/+ compound mice. These results confirm that PATZ1 downregulation has a critical role in thyroid carcinogenesis, showing that it cooperates with RET/PTC1 in thyroid cancer progression.