A multicentric study of radiomics and artificial intelligence analysis on contrast-enhanced mammography to identify different histotypes of breast cancer.

OBJECTIVE: To evaluate the performance of radiomic analysis on contrast-enhanced mammography images to identify different histotypes of breast cancer mainly in order to predict grading, to identify hormone receptors, to discriminate human epidermal growth factor receptor 2 (HER2) and to identify luminal histotype of the breast cancer. METHODS: From four Italian centers were recruited 180 malignant lesions and 68 benign lesions. However, only the malignant lesions were considered for the analysis. All patients underwent contrast-enhanced mammography in cranium caudal (CC) and medium lateral oblique (MLO) view. Considering histological findings as the ground truth, four outcomes were considered: (1) G1 + G2 vs. G3; (2) HER2 + vs. HER2 - ; (3) HR + vs. HR - ; and (4) non-luminal vs. luminal A or HR + /HER2- and luminal B or HR + /HER2 + . For multivariate analysis feature selection, balancing techniques and patter recognition approaches were considered. RESULTS: The univariate findings showed that the diagnostic performance is low for each outcome, while the results of the multivariate analysis showed that better performances can be obtained. In the HER2 + detection, the best performance (73% of accuracy and AUC = 0.77) was obtained using a linear regression model (LRM) with 12 features extracted by MLO view. In the HR + detection, the best performance (77% of accuracy and AUC = 0.80) was obtained using a LRM with 14 features extracted by MLO view. In grading classification, the best performance was obtained by a decision tree trained with three predictors extracted by MLO view reaching an accuracy of 82% on validation set. In the luminal versus non-luminal histotype classification, the best performance was obtained by a bagged tree trained with 15 predictors extracted by CC view reaching an accuracy of 94% on validation set. CONCLUSIONS: The results suggest that radiomics analysis can be effectively applied to design a tool to support physician decision making in breast cancer classification. In particular, the classification of luminal versus non-luminal histotypes can be performed with high accuracy.

Analysis of a monocentric computed tomography dosimetric database using a radiation dose index monitoring software: dose levels and alerts before and after the implementation of the adaptive statistical iterative reconstruction on CT images.

OBJECTIVE: To analyze dosimetric data of a single center by a radiation dose index monitoring software evaluating quantitatively the dose reduction obtained with the implementation of the adaptive statistical iterative reconstruction (ASIR) on Computed Tomography in terms of both the value of the dose length product (DLP) and the alerts provided by the dose tool. METHODS: Dosimetric quantities were acquired using Qaelum DOSE tool (QAELUM NV, Leuven-Heverlee, Belgium). Dose data pertaining to CT examinations were performed using a General Electric Healthcare CT tomography with 64 detectors. CT dose data were collected over 4 years (January 1, 2017 to December 31, 2020) and included CT dose length product (DLP). Moreover, all CT examinations that triggered a high radiation dose (twice the median for that study description), termed alerts on Dose tool, were retrieved for the analysis. Two radiologists retrospectively assessed CT examinations in consensus for the images quality and for the causes of the alerts issued. A Chi-square test was used to assess whether there were any statistically significant differences among categorical variable while a Kruskal Wallis test was considered to assess differences statistically significant for continuous variables. RESULTS: Differences statistically significant were found for the DLP median values between the dosimetric data recorded on 2017-2018 versus 2019-2020. The differences were linked to the implementation of ASIR technique at the end of 2018 on the CT scanner. The highest percentage of alerts was reported in the CT study group "COMPLETE ABDOMEN + CHEST + HEAD" (range from 1.26% to 2.14%). A reduction year for year was relieved linked to the CT protocol optimization with a difference statistically significant. The highest percentage of alerts was linked to wrong study label/wrong study protocol selection with a range from 29 to 40%. CONCLUSIONS: Automated methods of radiation dose data collection allowed for detailed radiation dose analysis according to protocol and equipment over time. The use of CT ASIR technique could determine considerable reduction in radiation dose.

Effects of the Hypnotic Alkylphenol Derivative Propofol on Breast Cancer Progression. A Focus on Preclinical and Clinical Studies.

Propofol is a hypnotic alkylphenol derivative with many biological activities. It is predominantly used in anesthesia and is the most used parenteral anesthetic agent in the United States. Accumulating preclinical studies have shown that this compound may inhibit cancer recurrence and metastasis. Nevertheless, other investigations provided evidence that this compound may promote breast cancer cell progression by modulating different molecular pathways. Clinical data on this topic are scarce and derive from retrospective analyses. For this reason, we reviewed and evaluated the available data to reveal insight into this controversial issue. More preclinical and clinical investigations are necessary to determine the potential role of propofol in the proliferation of breast cancer cells.

Evaluation of average glandular dose and investigation of the relationship with compressed breast thickness in dual energy contrast enhanced digital mammography and digital breast tomosynthesis.

PURPOSE: To quantitatively assess the dose of Dual energy contrast enhanced digital mammography (CEDM) and digital breast tomosynthesis (DBT) and to investigate the relationship between average absorbed glandular dose (AGD), compressed breast thickness (CBT) and compression force (CF). MATERIALS AND METHODS: All CEDM and DBT examinations were performed in cranio-caudal (CC) and medio-lateral oblique (MLO) view. Exposure parameters of 135 mammographic procedures that using AEC (automatic exposure control) mode were recorded. AGDs were calculated. Kruskal Wallis test was performed. RESULTS: CBT population ranged from 23 to 94 mm with a thickness median value of 52 mm in CC view and of 57 mm in MLO views. CEDM AGD median value was significatively lower than DBT AGD in each views (p << 0.01). AGD showed a positive correlation and linear regression with CBT for both CEDM and DBT while CF did not show a correlation and linear regression with AGD. The highest values were found for MLO view: R2 of 0.74 for CEDM and R2 of 0.61 for DBT. Kruskal Wallis test shows that there was a difference statistically significant between AGD values of CEDM and DBT in CC view respect to MLO views (p < 0.01). CONCLUSIONS: Dose values of both techniques meet the recommendations for maximum dose in mammography. The results of the present study indicated that there was significant difference between AGD for CEDM and DBT exposure in different views (AGD in CC views had the lowest value) and that CBT could influence the AGD while CF was not correlated to AGD.

Risk management in magnetic resonance: failure mode, effects, and criticality analysis.

The aim of the study was to perform a risk management procedure in "Magnetic Resonance Examination" process in order to identify the critical phases and sources of radiological errors and to identify potential improvement projects including procedures, tests, and checks to reduce the error occurrence risk. In this study we used the proactive analysis "Failure Mode Effects Criticality Analysis," a qualitative and quantitative risk management procedure; has calculated Priority Risk Index (PRI) for each activity of the process; have identified, on the PRI basis, the most critical activities and, for them, have defined improvement projects; and have recalculated the PRI after implementation of improvement projects for each activity. Time stop and audits are performed in order to control the new procedures. The results showed that the most critical tasks of "Magnetic Resonance Examination" process were the reception of the patient, the patient schedule drafting, the closing examination, and the organization of activities. Four improvement projects have been defined and executed. PRI evaluation after improvement projects implementation has shown that the risk decreased significantly following the implementation of procedures and controls defined in improvement projects, resulting in a reduction of the PRI between 43% and 100%.