Next-level precision medicine: why the theragnostic approach is the future.

Theragnostics represents one of the most innovative fields of precision medicine with a huge potential in the field of oncology in the next years. The use of a pair of selective radiopharmaceuticals for cellular receptors, used for diagnostic and therapeutic purposes (PRRT), finds applications in the Neuroendocrine tumors and metastatic Castration-Resistant prostate cancer (mCRPC) thanks, respectively, to somatostatin receptor agonists and PSMA-based peptides. Further evolutions of theragnostics will be possible to the radioimmunoconjugates used both in the diagnostic (Immuno-PET) and in the therapeutic fields (radioimmunotherapy). It is evident that in the "omics-era," theragnostics could become a necessary method, not only in order to improve our knowledge of tumor biology, but also, to find more and more targeted therapies in a multidisciplinary context and in a tailor-based approach.

Ab initio molecular dynamics of solvation effects and reactivity at the interface between water and ascorbic acid covered anatase TiO2 (101).

In this work, we present a detailed study of the interaction between ascorbic acid (L-asc) and anatase TiO2 (101) surface both in gas phase and in contact with water by using density functional theory and ab initio molecular dynamics simulations. In gas phase, L-asc strongly binds the TiO2 (101) surface as a dianion (L-asc2- ), adopting a bridging bidentate coordination mode (BB), with the two acid protons transferred to two surface 2-fold bridging oxygens (O2c). AIMD simulations show that the interaction between the organic ligand and the anatase surface is stable and comparable to the vacuum one despite the possible solvent effects and/or possible structural distortions of the ligand. In addition, during the AIMD simulations hydroxylation phenomena occur forming transient H3 O+ ions at the solid-liquid interface. For the first time, our results provide insight into the role of the ascorbic acid on the electronic properties of the TiO2 (101), the influence of the water environment on the ligand-surface interaction and the nature of the solid-liquid interface.

Breast Imaging Physics in Mammography (Part II).

One of the most frequently detected neoplasms in women in Italy is breast cancer, for which high-sensitivity diagnostic techniques are essential for early diagnosis in order to minimize mortality rates. As addressed in Part I of this work, we have seen how conditions such as high glandular density or limitations related to mammographic sensitivity have driven the optimization of technology and the use of increasingly advanced and specific diagnostic methodologies. While the first part focused on analyzing the use of a mammography machine from a physical and dosimetric perspective, in this paper, we will examine other techniques commonly used in breast imaging: contrast-enhanced mammography, digital breast tomosynthesis, radio imaging, and include some notes on image processing. We will also explore the differences between these various techniques to provide a comprehensive overview of breast lesion detection techniques. We will examine the strengths and weaknesses of different diagnostic modalities and observe how, with the implementation of improvements over time, increasingly effective diagnoses can be achieved.

Automated 3D Ultrasound as an Adjunct to Screening Mammography Programs in Dense Breast: Literature Review and Metanalysis.

Purpose: The purpose of this meta-analysis is to investigate the effectiveness of supplementing screening mammography with three-dimensional automated breast ultrasonography (3D ABUS) in improving breast cancer detection rates in asymptomatic women with dense breasts. Materials and Methods: We conducted a thorough review of scientific publications comparing 3D ABUS and mammography. Articles for inclusion were sourced from peer-reviewed journal databases, namely MEDLINE (PubMed) and Scopus, based on an initial screening of their titles and abstracts. To ensure a sufficient sample size for meaningful analysis, only studies evaluating a minimum of 20 patients were retained. Eligibility for evaluation was further limited to articles written in English. Additionally, selected studies were required to have participants aged 18 or above at the time of the study. We analyzed 25 studies published between 2000 and 2021, which included a total of 31,549 women with dense breasts. Among these women, 229 underwent mammography alone, while 347 underwent mammography in combination with 3D ABUS. The average age of the women was 50.86 years (±10 years standard deviation), with a range of 40-56 years. In our efforts to address and reduce bias, we applied a range of statistical analyses. These included assessing study variation through heterogeneity assessment, accounting for potential study variability using a random-effects model, exploring sources of bias via meta-regression analysis, and checking for publication bias through funnel plots and the Egger test. These methods ensured the reliability of our study findings. Results: According to the 25 studies included in this metanalysis, out of the total number of women, 27,495 were diagnosed with breast cancer. Of these, 211 were diagnosed through mammography alone, while an additional 329 women were diagnosed through the combination of full-field digital mammography (FFDSM) and 3D ABUS. This represents an increase of 51.5%. The rate of cancers detected per 1000 women screened was 23.25‱ (95% confidence interval [CI]: 21.20, 25.60; p < 0.001) with mammography alone. In contrast, the addition of 3D ABUS to mammography increased the number of tumors detected to 20.95‱ (95% confidence interval [CI]: 18.50, 23; p < 0.001) per 1000 women screened. Discussion: Even though variability in study results, lack of long-term outcomes, and selection bias may be present, this systematic review and meta-analysis confirms that supplementing mammography with 3D ABUS increases the accuracy of breast cancer detection in women with ACR3 to ACR4 breasts. Our findings suggest that the combination of mammography and 3D ABUS should be considered for screening women with dense breasts. Conclusions: Our research confirms that adding 3D automated breast ultrasound to mammography-only screening in patients with dense breasts (ACR3 and ACR4) significantly (p < 0.05) increases the cancer detection rate.

The Role of Imaging of Lymphatic System to Prevent Cancer Related Lymphedema.

Lymphedema is a progressive chronic condition affecting approximately 250 million people worldwide, a number that is currently underestimated. In Western countries, the most common form of lymphedema of the extremities is cancer-related and less radical surgical intervention is the main option to prevent it. Standardized protocols in the areas of diagnosis, staging and treatment are strongly required to address this issue. The aim of this study is to review the main diagnostic methods, comparing new emerging procedures to lymphoscintigraphy, considered as the golden standard to date. The roles of Magnetic Resonance Lymphangiography (MRL) or indocyanine green ICG lymphography are particularly reviewed in order to evaluate diagnostic accuracy, potential associations with lymphoscintigraphy, and future directions guided by AI protocols. The use of imaging to treat lymphedema has benefited from new techniques in the area of lymphatic vessels anatomy; these perspectives have become of value in many clinical scenarios to prevent cancer-related lymphedema.

Breast Imaging Physics in Mammography (Part I).

Breast cancer is the most frequently diagnosed neoplasm in women in Italy. There are several risk factors, but thanks to screening and increased awareness, most breast cancers are diagnosed at an early stage when surgical treatment can most often be conservative and the adopted therapy is more effective. Regular screening is essential but advanced technology is needed to achieve quality diagnoses. Mammography is the gold standard for early detection of breast cancer. It is a specialized technique for detecting breast cancer and, thus, distinguishing normal tissue from cancerous breast tissue. Mammography techniques are based on physical principles: through the proper use of X-rays, the structures of different tissues can be observed. This first part of the paper attempts to explain the physical principles used in mammography. In particular, we will see how a mammogram is composed and what physical principles are used to obtain diagnostic images.

Sex life and low back pain: The impact of intradiscal ozone therapy in patients with herniated lumbar disc.

STUDY DESIGN: Retrospective cohort study. OBJECTIVES: To assess the improvement of sexual impairment after percutaneous intradiscal ozone therapy in patients complaining of low back pain (LBP) due to lumbar disc herniation. METHODS: Between January 2018 and June 2021, 157 consecutive imaging-guided percutaneous intradiscal ozone therapies were performed on 122 patients with LBP and/or sciatic pain due to lumbar disc herniation. Oswestry Disability Index (ODI) was administered before the treatment and at 1-month and 3-month follow-ups and the ODI Section 8 (ODI-8/sex life) values were retrospectively reviewed to evaluate the improvement of sexual impairment and disability. RESULTS: Mean age of patients was 54.63 ± 12.40. Technical success was achieved in all cases (157/157). Clinical success was registered in 61.97% (88/142) of patients at 1-month follow-up and in 82.69% (116/142) at 3-month follow-up. The mean ODI-8/sex life was 3.73 ± 1.29 before the procedure, 1.71 ± 1.37 at 1-month follow up and 0.44 ± 0.63 at 3-month follow-up. Compared to older patients, subjects under 50 years showed a significantly slower recovery of sexual impairment (p = 0.003). The treated levels were L3-L4, L4-L5, and L5-S1 in 4, 116, and 37 patients, respectively. Patients with L3-L4 disc herniation showed less sexual disability at presentation, with a significantly faster improvement of sexual life (p = 0.03). CONCLUSIONS: Percutaneous intradiscal ozone therapy is highly effective in reducing sexual impairment due to lumbar disc herniation, and the improvement is faster in older patients and in the case of L3-L4 disc involvement.

Radiomics in Breast Imaging: Future Development.

Breast cancer is the most common and most commonly diagnosed non-skin cancer in women. There are several risk factors related to habits and heredity, and screening is essential to reduce the incidence of mortality. Thanks to screening and increased awareness among women, most breast cancers are diagnosed at an early stage, increasing the chances of cure and survival. Regular screening is essential. Mammography is currently the gold standard for breast cancer diagnosis. In mammography, we can encounter problems with the sensitivity of the instrument; in fact, in the case of a high density of glands, the ability to detect small masses is reduced. In fact, in some cases, the lesion may not be particularly evident, it may be hidden, and it is possible to incur false negatives as partial details that may escape the radiologist's eye. The problem is, therefore, substantial, and it makes sense to look for techniques that can increase the quality of diagnosis. In recent years, innovative techniques based on artificial intelligence have been used in this regard, which are able to see where the human eye cannot reach. In this paper, we can see the application of radiomics in mammography.

Impact of the systematic introduction of tomosynthesis on breast biopsies: 10 years of results.

Digital Breast Tomosynthesis (DBT) is a cutting-edge technology introduced in recent years as an in-depth analysis of breast cancer diagnostics. Compared with 2D Full-Field Digital Mammography, DBT has demonstrated greater sensitivity and specificity in detecting breast tumors. This work aims to quantitatively evaluate the impact of the systematic introduction of DBT in terms of Biopsy Rate and Positive Predictive Values for the number of biopsies performed (PPV-3). For this purpose, we collected 69,384 mammograms and 7894 biopsies, of which 6484 were Core Biopsies and 1410 were stereotactic Vacuum-assisted Breast Biopsies (VABBs), performed on female patients afferent to the Breast Unit of the Istituto Tumori "Giovanni Paolo II" of Bari from 2012 to 2021, thus, in the period before, during and after the systematic introduction of DBT. Linear regression analysis was then implemented to investigate how the Biopsy Rate had changed over the 10 year screening. The next step was to focus on VABBs, which were generally performed during in-depth examinations of mammogram detected lesions. Finally, three radiologists from the institute's Breast Unit underwent a comparative study to ascertain their performances in terms of breast cancer detection rates before and after the introduction of DBT. As a result, it was demonstrated that both the overall Biopsy Rate and the VABBs Biopsy Rate significantly decreased following the introduction of DBT, with the diagnosis of an equal number of tumors. Besides, no statistically significant differences were observed among the three operators evaluated. In conclusion, this work highlights how the systematic introduction of DBT has significantly impacted the breast cancer diagnostic procedure, by improving the diagnostic quality and thereby reducing needless biopsies, resulting in a consequent reduction in costs.

SGLT2 breast expression could affect the cardiovascular performance in pre-menopausal women with fatty vs. non fatty breast via over-inflammation and sirtuins' down regulation.

OBJECTIVES: To evaluate the expression of sodium-glucose transporter 2 (SGLT2), inflammatory cytokines, and sirtuins in breast fat tissue at baseline, and serum cytokines of fatty vs. non-fatty pre-menopausal women at baseline, and at 12 months of follow-up. To correlate SGLT2/cytokines/sirtuins expression to clinical variables, and their changes (Δ) at follow-up, as intima-media wall thickness (IMT), left ventricle mass (LVM), left ventricle ejection fraction (LVEF), and myocardial performance index (MPI), and its normalization. BACKGROUND: Pre-menopausal women with the lowest breast fat density (fatty breast) vs. higher breast fat density (non-fatty breast) are a high-risk population for cardiovascular diseases and worse prognosis. METHODS: We analyzed SGLT2/cytokines/sirtuins of excised fatty breasts of fatty vs. non-fatty pre-menopausal women. We correlated SGLT2/cytokines/sirtuins to Δ IMT, Δ LVM, Δ LVEF, and Δ MPI, and normal cardiac performance (NCP) at 1 year of follow-up. RESULTS: fatty vs. non-fatty breast over-expressed SGLT2/inflammatory cytokines, with lowest values of sirtuins (p<0.05). We found a direct correlation between SGLT2 (R2 0.745), TNFα (R2 0.262), and ΔMPI (p<0.05), and an inverse correlation between breast density (R2 -0.198), SIRT-3 (R2-0.181), and ΔMPI (p<0.05). Fatty breast (0.761, CI 95% [0.101-0.915]), SGLT2 (0.812, CI 95% [0.674-0.978]) and SIRT-3 (1.945, CI 95% [1.201-3.148]) predicted NCP at 1 year of follow-up. CONCLUSIONS: fatty vs. non-fatty breast women over-expressed SGLT2/inflammatory cytokines, and down-regulated breast sirtuins. SGLT2/inflammatory cytokines expression and inversely the tissue sirtuin 3 (tSIRT3) and breast percentage density linked to ΔMPI at 1 year of follow-up. Fatty breast and SGLT2 inversely predicted NCP; SIRT-3 increased the probability of NCP at 1 year of follow-up.

Machine Learning Approaches with Textural Features to Calculate Breast Density on Mammography.

BACKGROUND: breast cancer (BC) is the world's most prevalent cancer in the female population, with 2.3 million new cases diagnosed worldwide in 2020. The great efforts made to set screening campaigns, early detection programs, and increasingly targeted treatments led to significant improvement in patients' survival. The Full-Field Digital Mammograph (FFDM) is considered the gold standard method for the early diagnosis of BC. From several previous studies, it has emerged that breast density (BD) is a risk factor in the development of BC, affecting the periodicity of screening plans present today at an international level. OBJECTIVE: in this study, the focus is the development of mammographic image processing techniques that allow the extraction of indicators derived from textural patterns of the mammary parenchyma indicative of BD risk factors. METHODS: a total of 168 patients were enrolled in the internal training and test set while a total of 51 patients were enrolled to compose the external validation cohort. Different Machine Learning (ML) techniques have been employed to classify breasts based on the values of the tissue density. Textural features were extracted only from breast parenchyma with which to train classifiers, thanks to the aid of ML algorithms. RESULTS: the accuracy of different tested classifiers varied between 74.15% and 93.55%. The best results were reached by a Support Vector Machine (accuracy of 93.55% and a percentage of true positives and negatives equal to TPP = 94.44% and TNP = 92.31%). The best accuracy was not influenced by the choice of the features selection approach. Considering the external validation cohort, the SVM, as the best classifier with the 7 features selected by a wrapper method, showed an accuracy of 0.95, a sensitivity of 0.96, and a specificity of 0.90. CONCLUSIONS: our preliminary results showed that the Radiomics analysis and ML approach allow us to objectively identify BD.

Diffusion-weighted imaging and apparent diffusion coefficient mapping of head and neck lymph node metastasis: a systematic review.

Aim: Head and neck squamous cell cancer (HNSCC) is the ninth most common tumor worldwide. Neck lymph node (LN) status is the major indicator of prognosis in all head and neck cancers, and the early detection of LN involvement is crucial in terms of therapy and prognosis. Diffusion-weighted imaging (DWI) is a non- invasive imaging technique used in magnetic resonance imaging (MRI) to characterize tissues based on the displacement motion of water molecules. This review aims to provide an overview of the current literature concerning quantitative diffusion imaging for LN staging in patients with HNSCC. Methods: This systematic review performed a literature search on the PubMed database (https://pubmed.ncbi.nlm.nih.gov/) for all relevant, peer-reviewed literature on the subject following the preferred reporting items for systematic reviews and meta-analyses (PRISMA) criteria, using the keywords: DWI, MRI, head and neck, staging, lymph node. Results: After excluding reviews, meta-analyses, case reports, and bibliometric studies, 18 relevant papers out of the 567 retrieved were selected for analysis. Conclusions: DWI improves the diagnosis, treatment planning, treatment response evaluation, and overall management of patients affected by HNSCC. More robust data to clarify the role of apparent diffusion coefficient (ADC) and DWI parameters are needed to develop models for prognosis and prediction in HNSCC cancer using MRI.

Expression of c-MET in Estrogen Receptor Positive and HER2 Negative Resected Breast Cancer Correlated with a Poor Prognosis.

Introduction: The mesenchymal-epithelial transition factor (c-MET) receptor is overexpressed in about 14−54% of invasive breast cancers, but its prognostic value in clinical practice is still unclear. Methods: In order to investigate the relationship between c-MET expression levels and prognosis, we retrospectively reviewed the clinical features and outcomes of 105 women with estrogen receptor positive HER2 negative (ER+/HER2-) resected breast cancer. We used the Kaplan Meier method to estimate Disease Free Survival (DFS) and Breast Cancer Specific Survival (BCSS) in the subgroups of patients with high (≥50%) and low (<50%) c-MET expression. Univariate and multivariate Cox proportional regression models were performed to assess the prognostic impact of clinicopathological parameters for DFS an BCSS. Results: High c-MET values significantly correlated with tumor size, high Ki67 and low (<20%) progesterone receptor expression. At a median follow up of 60 months, patients with high c-MET tumor had significantly worse (p = 0.00026) and BCSS (p = 0.0013). Univariate analysis showed a significant association between large tumor size, elevated Ki67, c-MET values and increased risk of recurrence or death. The multivariate COX regression model showed that tumor size and high c-MET expression were independent predictors of DFS (p = 0.019 and p = 0.022). Moreover, large tumor size was associated with significantly higher risk of cancer related death at multivariate analysis (p = 0.017), while a trend towards a poorer survival was registered in the high c-MET levels cohort (p = 0.084). Conclusions: In our series, high c-MET expression correlated with poor survival outcomes. Further studies are warranted to validate the clinical relevance and applicability of c-MET as a prognostic factor in ER+/HER2- early BC.

A Multimodal Knowledge-Based Deep Learning Approach for MGMT Promoter Methylation Identification.

Glioblastoma Multiforme (GBM) is considered one of the most aggressive malignant tumors, characterized by a tremendously low survival rate. Despite alkylating chemotherapy being typically adopted to fight this tumor, it is known that O(6)-methylguanine-DNA methyltransferase (MGMT) enzyme repair abilities can antagonize the cytotoxic effects of alkylating agents, strongly limiting tumor cell destruction. However, it has been observed that MGMT promoter regions may be subject to methylation, a biological process preventing MGMT enzymes from removing the alkyl agents. As a consequence, the presence of the methylation process in GBM patients can be considered a predictive biomarker of response to therapy and a prognosis factor. Unfortunately, identifying signs of methylation is a non-trivial matter, often requiring expensive, time-consuming, and invasive procedures. In this work, we propose to face MGMT promoter methylation identification analyzing Magnetic Resonance Imaging (MRI) data using a Deep Learning (DL) based approach. In particular, we propose a Convolutional Neural Network (CNN) operating on suspicious regions on the FLAIR series, pre-selected through an unsupervised Knowledge-Based filter leveraging both FLAIR and T1-weighted series. The experiments, run on two different publicly available datasets, show that the proposed approach can obtain results comparable to (and in some cases better than) the considered competitor approach while consisting of less than 0.29% of its parameters. Finally, we perform an eXplainable AI (XAI) analysis to take a little step further toward the clinical usability of a DL-based approach for MGMT promoter detection in brain MRI.

Supine versus Prone 3D Abus Accuracy in Breast Tumor Size Evaluation.

Breast-conserving surgery (BCS) with negative resection margins decreases the locoregional recurrence rate. Breast cancer size is one of the main determinants of Tumor-Node-Metastasis (TNM) staging. Our study aimed to investigate the accuracy of supine 3D automated breast ultrasound (3D ABUS) compared to prone 3D ABUS in the evaluation of tumor size in breast cancer patient candidates for BCS. In this prospective two-center study (Groups 1 and 2), we enrolled patients with percutaneous biopsy-proven early-stage breast cancer, in the period between June 2019 and May 2020. Patients underwent hand-held ultrasound (HHUS), contrast-enhanced magnetic resonance imaging (CE-MRI) and 3D ABUS-supine 3D ABUS in Group 1 and prone 3D ABUS in Group 2. Histopathological examination (HE) was considered the reference standard. Bland-Altman analysis and plots were used. Eighty-eight patients were enrolled. Compared to prone, supine 3D ABUS showed better agreement with HE, with a slight tendency toward underestimation (mean difference of -2 mm). Supine 3D ABUS appears to be a useful tool and more accurate than HHUS in the staging of breast cancer.

Comparison between two packages for pectoral muscle removal on mammographic images.

BACKGROUND: Pectoral muscle removal is a fundamental preliminary step in computer-aided diagnosis systems for full-field digital mammography (FFDM). Currently, two open-source publicly available packages (LIBRA and OpenBreast) provide algorithms for pectoral muscle removal within Matlab environment. PURPOSE: To compare performance of the two packages on a single database of FFDM images. METHODS: Only mediolateral oblique (MLO) FFDM was considered because of large presence of pectoral muscle on this type of projection. For obtaining ground truth, pectoral muscle has been manually segmented by two radiologists in consensus. Both LIBRA's and OpenBreast's removal performance with respect to ground truth were compared using Dice similarity coefficient and Cohen-kappa reliability coefficient; Wilcoxon signed-rank test has been used for assessing differences in performances; Kruskal-Wallis test has been used to verify possible dependence of the performance from the breast density or image laterality. RESULTS: FFDMs from 168 consecutive women at our institution have been included in the study. Both LIBRA's Dice-index and Cohen-kappa were significantly higher than OpenBreast (Wilcoxon signed-rank test P < 0.05). No dependence on breast density or laterality has been found (Kruskal-Wallis test P > 0.05). CONCLUSION: Libra has a better performance than OpenBreast in pectoral muscle delineation so that, although our study has not a direct clinical application, these results are useful in the choice of packages for the development of complex systems for computer-aided breast evaluation.

SGLT2-inhibitors reduce the cardiac autonomic neuropathy dysfunction and vaso-vagal syncope recurrence in patients with type 2 diabetes mellitus: the SCAN study.

BACKGROUND: In patients with type 2 diabetes mellitus (T2DM) the vaso-vagal syncope (VVS) recurrence could be due to the alteration of autonomic system function, evaluated by heart rate variability (HRV), and by 123I-metaiodobenzylguanidine (123I-mIBG) myocardial scintigraphy indexes: Heart to Mediastinum ratio (H/Mlate), and Washout rate (WR). The SGLT2-I could modulate/reduce autonomic dysfunction in T2DM patients with VVS. This effect could reduce the VVS recurrence in T2DM patients. METHODS: In a prospective multicenter study, after propensity score matching, we studied a population of 324 T2DM patients with VVS, divided into 161 SGLT2-I-users vs. 163 Non-SGLT2-I users. In these patients as SGLT2-I-users vs. Non-SGLT2-I users, we investigated the HRV and 123I-MIBG modifications and VVS recurrence at 12 months of follow-up. RESULTS: At follow-up end, the SGLT2-I-users vs. Non-SGLT2-I users had best glucose homeostasis and lower values of inflammatory markers, and resting heart rate (p < 0.05). The SGLT2-I-users vs. Non-SGLT2-I users evidenced the lowest low frequency/high frequency ratio (LF/HFr), a significant difference for all the indexes of autonomic dysfunction via ECG Holter analysis, and higher values of H/Mlate (p < 0.05). Finally, comparing SGLT2-I-users vs. Non-SGLT2-I users, we found a higher rate of VVS recurrence events, specifically of the vasodepressor VVS recurrence at 1-year follow-up (p < 0.05). We did not find a significant difference of mixed and cardio-inhibitory VVS recurrence events at 1 year of follow-up in the study cohorts (p > 0.05). At the Cox regression analysis H/Mlate (0.710, [0.481-0.985]), and SGLT2-I therapy (0.550, [0.324-0.934]) predicted all causes of syncope recurrence at 1 year of follow-up. CONCLUSIONS: Non-SGLT2-I users vs. SGLT2-I-users had alterations of the autonomic nervous system, with a higher rate of VVS recurrence at 1 year of follow-up. The indexes of cardiac denervation predicted the VVS recurrence, while the SGLT2-I reduced the risk of VVS recurrence. CLINICAL TRIAL REGISTRATION NUMBER: NCT03717207.

Robustness Evaluation of a Deep Learning Model on Sagittal and Axial Breast DCE-MRIs to Predict Pathological Complete Response to Neoadjuvant Chemotherapy.

To date, some artificial intelligence (AI) methods have exploited Dynamic Contrast-Enhanced Magnetic Resonance Imaging (DCE-MRI) to identify finer tumor properties as potential earlier indicators of pathological Complete Response (pCR) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC). However, they work either for sagittal or axial MRI protocols. More flexible AI tools, to be used easily in clinical practice across various institutions in accordance with its own imaging acquisition protocol, are required. Here, we addressed this topic by developing an AI method based on deep learning in giving an early prediction of pCR at various DCE-MRI protocols (axial and sagittal). Sagittal DCE-MRIs refer to 151 patients (42 pCR; 109 non-pCR) from the public I-SPY1 TRIAL database (DB); axial DCE-MRIs are related to 74 patients (22 pCR; 52 non-pCR) from a private DB provided by Istituto Tumori "Giovanni Paolo II" in Bari (Italy). By merging the features extracted from baseline MRIs with some pre-treatment clinical variables, accuracies of 84.4% and 77.3% and AUC values of 80.3% and 78.0% were achieved on the independent tests related to the public DB and the private DB, respectively. Overall, the presented method has shown to be robust regardless of the specific MRI protocol.

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. The analysis on patients under 50 years old resulted in a p-value < 0.001, highlighting how the behaviors of patients characterized by a ki67 ranging from 10% to 20% and greater than 20% were statistically significantly similar. Conversely, patients over 50 years old characterized by a ki67 ranging from 10% to 20% showed an IDE-free survival probability significantly greater than patients with a ki67 greater than 20%, with a p-value of 0.01. Our work shows that the adoption of two different ki67 values, namely, 10% and 20%, might be discriminant in designing personalized treatments for patients under 50 years old and over 50 years old, respectively.

A ultrasound-based radiomic approach to predict the nodal status in clinically negative breast cancer patients.

In breast cancer patients, an accurate detection of the axillary lymph node metastasis status is essential for reducing distant metastasis occurrence probabilities. In case of patients resulted negative at both clinical and instrumental examination, the nodal status is commonly evaluated performing the sentinel lymph-node biopsy, that is a time-consuming and expensive intraoperative procedure for the sentinel lymph-node (SLN) status assessment. The aim of this study was to predict the nodal status of 142 clinically negative breast cancer patients by means of both clinical and radiomic features extracted from primary breast tumor ultrasound images acquired at diagnosis. First, different regions of interest (ROIs) were segmented and a radiomic analysis was performed on each ROI. Then, clinical and radiomic features were evaluated separately developing two different machine learning models based on an SVM classifier. Finally, their predictive power was estimated jointly implementing a soft voting technique. The experimental results showed that the model obtained by combining clinical and radiomic features provided the best performances, achieving an AUC value of 88.6%, an accuracy of 82.1%, a sensitivity of 100% and a specificity of 78.2%. The proposed model represents a promising non-invasive procedure for the SLN status prediction in clinically negative patients.