Diagnostic imaging and CEUS findings in a rare case of Desmoid-type fibromatosis. A case report

Desmoid-type fibromatosis (DF), also known as aggressive fibromatosis, is a locally aggressive benign fibroblastic neoplasm that can infiltrate or recur but cannot metastasize. It is rare, with an estimated annual incidence of two to four new cases per million people. Most DFs occur sporadically, but it may also be associated with the hereditary syndrome familial adenomatous polyposis. Treatment is necessary when the disease is symptomatic, especially in case of compression of critical structures. When possible, surgical resection is the treatment of choice; however, recurrence is common. Due to the high rate of recurrence, imaging plays an important role not only in diagnosis, but also in the management of DF. Although there are a number of studies describing CT and MRI findings of DF, there is no description of contrast-enhanced ultrasound findings

Mammographic breast density in infertile and parous women

BACKGROUND: Mammographic breast density is a useful marker for breast cancer risk, as breast density is considered one of the strongest breast cancer risk factors. The study objective was to evaluate and compare mammographic breast density in infertile and parous women, as infertility may be associated with high breast density and cancer occurrence. METHODS: This study evaluated mammographic breast density using two different systems, BIRADS and Boyd. A selected patient population of 151 women with primary infertility (case group) was compared to 154 parous women who had at least one previous pregnancy (control group). Both groups were premenopausal women aged ≥ 35. RESULTS: Evaluation of mammographic features showed that 66.9% of case group patients and 53.9% of control group patients were classified BIRADS-3/BIRADS-4; p < 0.05. Adjusted Odds ratio for the case group in the categories BIRADS-3/BIRADS-4 was 1.78 (95% CI: 1.10-2.89). Using the Boyd classification system, 53.6% of case group patients and 31.8% of control group patients were classified E/F; p < 0.05. Adjusted Odds ratio for case group patients in Boyd categories E/F was 2.05 (95 % CI: 1.07-3.93). CONCLUSIONS: Both systems yielded a higher percentage of increased breast density in the case group. Boyd and BIRADS classification systems indicate to what extend breast cancer lesions may be missed on mammography due to masking by dense tissue. Therefore, patients with a high BIRADS or Boyd score should undergo further investigation

Inflationary Perturbations in Palatini Generalised Gravity

We examine the generation of primordial perturbations during an inflationary epoch in generalised theories of gravity when the equations of motion are derived using the Palatini variational principle. Both f(R) and Scalar-Tensor theories are considered and we compare our results with those obtained under the conventional metric formalism. Non-linear generalisations of the action lead to different theories under the two variational choices and we obtain distinct results for scalar and tensor spectral indices and their ratio. We find the following general result; inflation driven solely by f(R) modifications alone do not result in suitable curvature perturbations whilst Scalar-Tensor theories generate nearly scalar invariant curvature perturbations but no tensor modes.Comment: 9 page

Coalescing binary systems of compact objects: Dynamics of angular momenta

The end state of a coalescing binary of compact objects depends strongly on the final total mass M and angular momentum J. Since gravitational radiation emission causes a slow evolution of the binary system through quasi-circular orbits down to the innermost stable one, in this paper we examine the corresponding behavior of the ratio J/M^2 which must be less than 1(G/c) or about 0.7(G/c) for the formation of a black hole or a neutron star respectively. The results show cases for which, at the end of the inspiral phase, the conditions for black hole or neutron star formation are not satisfied. The inclusion of spin effects leads us to a study of precession equations valid also for the calculation of gravitational waveforms.Comment: 22 pages, AASTeX and 13 figures in PostScrip

CNN-Based Approaches with Different Tumor Bounding Options for Lymph Node Status Prediction in Breast DCE-MRI

Background: The axillary lymph node status (ALNS) is one of the most important prognostic factors in breast cancer (BC) patients, and it is currently evaluated by invasive procedures. Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI), highlights the physiological and morphological characteristics of primary tumor tissue. Deep learning approaches (DL), such as convolutional neural networks (CNNs), are able to autonomously learn the set of features directly from images for a specific task. Materials and Methods: A total of 155 malignant BC lesions evaluated via DCE-MRI were included in the study. For each patient’s clinical data, the tumor histological and MRI characteristics and axillary lymph node status (ALNS) were assessed. LNS was considered to be the final label and dichotomized (LN+ (27 patients) vs. LN− (128 patients)). Based on the concept that peritumoral tissue contains valuable information about tumor aggressiveness, in this work, we analyze the contributions of six different tumor bounding options to predict the LNS using a CNN. These bounding boxes include a single fixed-size box (SFB), a single variable-size box (SVB), a single isotropic-size box (SIB), a single lesion variable-size box (SLVB), a single lesion isotropic-size box (SLIB), and a two-dimensional slice (2DS) option. According to the characteristics of the volumes considered as inputs, three different CNNs were investigated: the SFB-NET (for the SFB), the VB-NET (for the SVB, SIB, SLVB, and SLIB), and the 2DS-NET (for the 2DS). All the experiments were run in 10-fold cross-validation. The performance of each CNN was evaluated in terms of accuracy, sensitivity, specificity, the area under the ROC curve (AUC), and Cohen’s kappa coefficient (K). Results: The best accuracy and AUC are obtained by the 2DS-NET (78.63% and 77.86%, respectively). The 2DS-NET also showed the highest specificity, whilst the highest sensibility was attained by the VB-NET based on the SVB and SIB as bounding options. Conclusion: We have demonstrated that a selective inclusion of the DCE-MRI’s peritumoral tissue increases accuracy in the lymph node status prediction in BC patients using CNNs as a DL approach

Are you planning to be a radiation oncologist? A survey by the young group of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO)

Background and purpose The Young Section of the Italian Association of Radiotherapy and Clinical Oncology (yAIRO) circulated an online questionnaire survey among residents currently enrolled within Italian radiotherapy residency schools to investigate the profiles, motivations, knowledge of the radiotherapy discipline, organizations and the needs of younger members.Materials and Methods The survey was developed by the yAIRO steering committee and included questions about the demo-graphic characteristics of the residents (Profile A), the background of their clinical experience during the school of medicine and national residency admission test performance (Profile B) and the residents' knowledge of the scientific associations active in the field of radiotherapy (Profile C).Results Out of 400 residents actually in training, 134 responded to the questionnaire (response rate 33.5%). According to most of the residents, radiotherapy was not adequately studied during the medical school (n. 95; 71%) and an Internship in Radiotherapy was not mandatory (n. 99; 74%). Only a minority of the residents had chosen to complete a master's degree thesis in radiotherapy (n. 12; 9%). A low percentage of the residents stated that they were aware of the Italian Association of Radiotherapy and Clinical Oncology (AIRO), its young section (yAIRO) and the European Society for Radiotherapy and Oncology (ESTRO) when they were in School of Medicine (respectively, 11%, 7% and 13%).Conclusions The results of the survey require a profound reflection on the current teaching methods of Radiation Oncology in our country, highlighting the need for a better integration in the framework of the School of Medicine core curriculum

Parenteral Nutrition in Liver Resection

Albeit a very large number of experiments have assessed the impact of various substrates on liver regeneration after partial hepatectomy, a limited number of clinical studies have evaluated artificial nutrition in liver resection patients. This is a peculiar topic because many patients do not need artificial nutrition, while several patients need it because of malnutrition and/or prolonged inability to feeding caused by complications. The optimal nutritional regimen to support liver regeneration, within other postoperative problems or complications, is not yet exactly defined. This short review addresses relevant aspects and potential developments in the issue of postoperative parenteral nutrition after liver resection

Synchronous anal canal cancer and cervical cancer: report of a case and management implication

Background: This is the case report of a synchronous anal canal cancer and cervical cancer in a patient who underwent definitive chemoradiotherapy (CRT) and radical surgery for anal canal and cervical carcinoma, respectively. Case Report: A 55-year-old woman was diagnosed with cT4a cN1 Mx anal canal squamous cell carcinoma and stage IA2 cervical squamous cell carcinoma, based on biopsy and imaging. Definitive CRT consisted of radiotherapy (total dose of 59.4 Gy) and concomitant mitomycin (10 mg/m(2)) and 5-fluorouracil (750 mg/m(2)/5 daily continuous infusion) during the first and last week of radiation. The patient exhibited a complete clinical and radiological response. A radical hysterectomy with pelvic lymphadenectomy was then performed. At the last follow-up (30 months), the patient is still disease-free without any treatment-associated complications. Conclusion: There is limited information in the literature regarding treatment strategy and outcome of patients with synchronous anal canal and cervical cancer. A two-step treatment, including CRT and radical hysterectomy, is likely to be accepted as valid option

3T MRI-radiomic approach to predict for lymph node status in breast cancer patients

Simple SummaryBreast cancer is the most common cancer in women worldwide. The axillary lymph node status is one of the main prognostic factors. Currently, the methods to define the lymph node status are invasive and not without sequelae (from biopsy to lymphadenectomy). Radiomics is a new tool, and highly varied, but with high potential that has already shown excellent results in numerous fields of application. In our study, we have developed a classifier validated on a relatively large number of patients, which is able to predict lymph node status using a combination of patients clinical features, primary breast cancer histological features and radiomics features based on 3 Tesla post contrast-MR images. This approach can accurately select breast cancer patients who may avoid unnecessary biopsy and lymphadenectomy in a non-invasive way.Background: axillary lymph node (LN) status is one of the main breast cancer prognostic factors and it is currently defined by invasive procedures. The aim of this study is to predict LN metastasis combining MRI radiomics features with primary breast tumor histological features and patients' clinical data. Methods: 99 lesions on pre-treatment contrasted 3T-MRI (DCE). All patients had a histologically proven invasive breast cancer and defined LN status. Patients' clinical data and tumor histological analysis were previously collected. For each tumor lesion, a semi-automatic segmentation was performed, using the second phase of DCE-MRI. Each segmentation was optimized using a convex-hull algorithm. In addition to the 14 semantics features and a feature ROI volume/convex-hull volume, 242 other quantitative features were extracted. A wrapper selection method selected the 15 most prognostic features (14 quantitative, 1 semantic), used to train the final learning model. The classifier used was the Random Forest. Results: the AUC-classifier was 0.856 (label = positive or negative). The contribution of each feature group was lower performance than the full signature. Conclusions: the combination of patient clinical, histological and radiomics features of primary breast cancer can accurately predict LN status in a non-invasive way

GPS observables in general relativity

I present a complete set of gauge invariant observables, in the context of general relativity coupled with a minimal amount of realistic matter (four particles). These observables have a straightforward and realistic physical interpretation. In fact, the technology to measure them is realized by the Global Positioning System: they are defined by the physical reference system determined by GPS readings. The components of the metric tensor in this physical reference system are gauge invariant quantities and, remarkably, their evolution equations are local.Comment: 6 pages, 1 figure, references adde