Prediction of breast cancer Invasive Disease Events using transfer learning on clinical data as image-form.

Background And Objective: Detecting patients at high risk of occurrence of an Invasive Disease Event after a first diagnosis of breast cancer, such as recurrence, distant metastasis, contralateral tumor and second tumor, could support clinical decision-making processes in the treatment of this malignancy. Though several machine learning models analyzing both clinical and histopathological information have been developed in literature to address this task, these approaches turned out to be unsuitable for describing this problem.

Methods: In this study, we designed a novel artificial intelligence-based approach which converts clinical information into an image-form to be analyzed through Convolutional Neural Networks.

Tricuspid regurgitation and heart failure: the fate of treated vs. untreated cohort in the percutaneous era.

Aims: Tricuspid regurgitation (TR) is associated with heart failure (HF) and reduced survival. Within a short-time period, transcatheter tricuspid valve repair or replacement (TTVR/TTVr) for TR has evolved from innovation to clinical reality. The present study's aim is to provide 1-year results between TR patients treated with TTVR and TTVr compared with untreated patients, in terms of cardiac survival, rehospitalization, right-side HF symptom development, and New York Heart Association (NYHA) improvement.

Gender differences in outcomes after left atrial appendage closure with Watchman FLX device: insights from the Italian-FLX registry.

Introduction: Recent studies have shown gender differences in cardiovascular outcomes after left atrial appendage closure (LAAC), highlighting different complication rates and adverse events, particularly in short-term assessments. As a result, there remains a significant knowledge gap on how these differences directly impact the efficacy and safety of LAAC procedures. The aim of this retrospective study was to investigate the clinical outcomes of LAAC in women and men using the Watchman FLX device.

Treatment of Thoracic SMARCA4-Deficient Undifferentiated Tumors: Where We Are and Where We Will Go.

Recently, the fifth edition of the WHO classification recognized the thoracic -deficient undifferentiated tumor (SMARCA4-UT) as a separate entity from conventional non-small cell lung cancer with deficiency because of the different clinicopathological characteristics of these two diseases. SMARCA4-UT mainly occurs in young to middle-aged adults and involves a large mass compressing the tissues surrounding the mediastinum and lung parenchyma. Unfortunately, SMARCA4-UT shows a high probability of recurrence after upfront surgery as well as radiotherapy resistance; moreover, chemotherapy has low efficacy.

Explainable 3D CNN based on baseline breast DCE-MRI to give an early prediction of pathological complete response to neoadjuvant chemotherapy.

Background: So far, baseline Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) has played a key role for the application of sophisticated artificial intelligence-based models using Convolutional Neural Networks (CNNs) to extract quantitative imaging information as earlier indicators of pathological Complete Response (pCR) achievement in breast cancer patients treated with neoadjuvant chemotherapy (NAC). However, these models did not exploit the DCE-MRI exams in their full geometry as 3D volume but analysed only few individual slices independently, thus neglecting the depth information.

Method: This study aimed to develop an explainable 3D CNN, which fulfilled the task of pCR prediction before the beginning of NAC, by leveraging the 3D information of post-contrast baseline breast DCE-MRI exams.

Consolidative thoracic radiation therapy for extensive-stage small cell lung cancer in the era of first-line chemoimmunotherapy: preclinical data and a retrospective study in Southern Italy.

Background: Consolidative thoracic radiotherapy (TRT) has been commonly used in the management of extensive-stage small cell lung cancer (ES-SCLC). Nevertheless, phase III trials exploring first-line chemoimmunotherapy have excluded this treatment approach. However, there is a strong biological rationale to support the use of radiotherapy (RT) as a boost to sustain anti-tumor immune responses.

Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence.

Non-Small cell lung cancer (NSCLC) is one of the most dangerous cancers, with 85% of all new lung cancer diagnoses and a 30-55% of recurrence rate after surgery. Thus, an accurate prediction of recurrence risk in NSCLC patients during diagnosis could be essential to drive targeted therapies preventing either overtreatment or undertreatment of cancer patients. The radiomic analysis of CT images has already shown great potential in solving this task; specifically, Convolutional Neural Networks (CNNs) have already been proposed providing good performances.

A CT-based transfer learning approach to predict NSCLC recurrence: The added-value of peritumoral region.

Non-small cell lung cancer (NSCLC) represents 85% of all new lung cancer diagnoses and presents a high recurrence rate after surgery. Thus, an accurate prediction of recurrence risk in NSCLC patients at diagnosis could be essential to designate risk patients to more aggressive medical treatments. In this manuscript, we apply a transfer learning approach to predict recurrence in NSCLC patients, exploiting only data acquired during its screening phase.

A Machine Learning Approach for Predicting Capsular Contracture after Postmastectomy Radiotherapy in Breast Cancer Patients.

In recent years, immediate breast reconstruction after mastectomy surgery has steadily increased in the treatment pathway of breast cancer (BC) patients due to its potential impact on both the morpho-functional and aesthetic type of the breast and the quality of life. Although recent studies have demonstrated how recent radiotherapy techniques have allowed a reduction of adverse events related to breast reconstruction, capsular contracture (CC) remains the main complication after post-mastectomy radio-therapy (PMRT). In this study, we evaluated the association of the occurrence of CC with some clinical, histological and therapeutic parameters related to BC patients.

Immunotherapy in Elderly Patients Affected by Non-Small Cell Lung Cancer: A Narrative Review.

Lung cancer is the leading cause of cancer-related deaths worldwide. Non-small cell lung cancer (NSCLC) accounts for approximately 80% of all lung cancers, and most NSCLC is diagnosed in the advanced stage. The advent of immune check point inhibitors (ICIs) changed the therapeutic scenario both in metastatic disease (in first and subsequent lines) and earlier settings.

A machine learning ensemble approach for 5- and 10-year breast cancer invasive disease event classification.

Designing targeted treatments for breast cancer patients after primary tumor removal is necessary to prevent the occurrence of invasive disease events (IDEs), such as recurrence, metastasis, contralateral and second tumors, over time. However, due to the molecular heterogeneity of this disease, predicting the outcome and efficacy of the adjuvant therapy is challenging. A novel ensemble machine learning classification approach was developed to address the task of producing prognostic predictions of the occurrence of breast cancer IDEs at both 5- and 10-years.

An Invasive Disease Event-Free Survival Analysis to Investigate Ki67 Role with Respect to Breast Cancer Patients' Age: A Retrospective Cohort Study.

Characterization of breast cancer into intrinsic molecular profiles has allowed women to live longer, undergoing personalized treatments. With the aim of investigating the relation between different values of ki67 and the predisposition to develop a breast cancer-related IDE at different ages, we enrolled 900 patients with a first diagnosis of invasive breast cancer, and we partitioned the dataset into two sub-samples with respect to an age value equal to 50 years. For each sample, we performed a Kaplan−Meier analysis to compare the IDE-free survival curves obtained with reference to different ki67 values.

Cemiplimab in an Elderly Frail Population of Patients With Locally Advanced or Metastatic Cutaneous Squamous Cell Carcinoma: A Single-Center Real-Life Experience From Italy.

Background: Cutaneous squamous cell carcinoma (CSCC) is the second most common skin cancer whose incidence is growing parallel to the lengthening of the average lifespan. Cemiplimab, an antiPD-1 monoclonal antibody, is the first approved immunotherapy for patients with locally advanced CSCC (laCSCC) or metastatic CSCC (mCSCC) thanks to phase I and II studies showing high antitumor activity and good tolerability. Nevertheless, at present, very few data are available regarding cemiplimab in real-life experience and in frail, elderly, and immunosuppressed patients as well as regarding biomarkers able to predict response so as to guide therapeutic choices.

Advancement study of CancerMath model as prognostic tools for predicting Sentinel lymph node metastasis in clinically negative T1 breast cancer patients.

Purpose: Sentinel lymph node biopsy (SLNB) is an invasive surgical procedure and although it has fewer complications and is less severe than axillary lymph node dissection, it is not a risk-free procedure. Large prospective trials have documented SLNB that it is considered non-therapeutic in early stage breast cancer.

Methods: Web-calculator CancerMath (CM) allows you to estimate the probability of having positive lymph nodes valued on the basis of tumour size, age, histologic type, grading, expression of estrogen receptor, progesterone receptor.

Early prediction of neoadjuvant chemotherapy response by exploiting a transfer learning approach on breast DCE-MRIs.

The dynamic contrast-enhanced MR imaging plays a crucial role in evaluating the effectiveness of neoadjuvant chemotherapy (NAC) even since its early stage through the prediction of the final pathological complete response (pCR). In this study, we proposed a transfer learning approach to predict if a patient achieved pCR (pCR) or did not (non-pCR) by exploiting, separately or in combination, pre-treatment and early-treatment exams from I-SPY1 TRIAL public database. First, low-level features, i.

Radiomic Feature Reduction Approach to Predict Breast Cancer by Contrast-Enhanced Spectral Mammography Images.

Contrast-enhanced spectral mammography (CESM) is an advanced instrument for breast care that is still operator dependent. The aim of this paper is the proposal of an automated system able to discriminate benign and malignant breast lesions based on radiomic analysis. We selected a set of 58 regions of interest (ROIs) extracted from 53 patients referred to Istituto Tumori "Giovanni Paolo II" of Bari (Italy) for the breast cancer screening phase between March 2017 and June 2018.

A Clinical Decision Support System for Predicting Invasive Breast Cancer Recurrence: Preliminary Results.

The mortality associated to breast cancer is in many cases related to metastasization and recurrence. Personalized treatment strategies are critical for the outcomes improvement of BC patients and the Clinical Decision Support Systems can have an important role in medical practice. In this paper, we present the preliminary results of a prediction model of the Breast Cancer Recurrence (BCR) within five and ten years after diagnosis.

Examining the Relationship between Circulating CD4- CD8- Double-Negative T Cells and Outcomes of Immuno-Checkpoint Inhibitor Therapy-Looking for Biomarkers and Therapeutic Targets in Metastatic Melanoma.

Background: The role of circulating CD4/CD8 double-negative T cells (DNTs) in the immune response to melanoma is poorly understood, as are the effects of checkpoint inhibitors on T cell subpopulations.

Methods: We performed a basal and longitudinal assessment of circulating immune cells, including DNTs, in metastatic melanoma patients treated with checkpoint blockade in a single-center cohort, and examined the correlations levels of immune cells with clinical features and therapy outcomes.

Results: Sixty-eight patients (48 ipilimumab, 20 PD1 inhibitors) were enrolled in the study.

The Management of Oligoprogression in the Landscape of New Therapies for Metastatic Melanoma.

: A limited degree of progression after a response to treatment is labelled as oligoprogression and is a hot topic of metastatic melanoma (MM) management. Rogue progressive metastases could benefit from local treatment, which could allow the continuation of ongoing systemic therapy, also known as treatment beyond progression (TBP). : We retrospectively reviewed 214 selected MM patients who developed oligoprogression during treatment with v-Raf murine sarcoma viral oncogene homolog B (BRAF)/mitogen-activated-extracellular signal-regulated kinase (MEK) or programmed cell death protein 1 (PD-1) inhibitors and received a local treatment continuing TBP.