Diagnostic challenges and potential early indicators of breast periprosthetic anaplastic large cell lymphoma: A case report.

RATIONALE: Anaplastic large T-cell lymphoma (BI-ALCL) is a rare primitive lymphoma described in women with breast implant prostheses, which has been arousing interest in recent years due to its potentially high social impact. The difficult diagnosis associated with the high and increasing number of prosthetic implants worldwide has led to hypothesize an underestimation of the real impact of the disease among prosthesis-bearing women. The aim of this work is to search for specific radiological signs of disease linked to the chronic inflammatory pathogenetic mechanism. PATIENT CONCERNS: This work describes a case of BI-ALCL in an American woman with no personal or family history of cancer, who underwent breast augmentation for esthetic purposes at our Institute. After about 10 years of relative well-being, the patient returned to our Institute with clear evidence of breast asymmetry due to the increase in volume of the right breast which had progressively become larger over a period of 6 months. There was no evidence of palpable axillary lymph nodes or other noteworthy signs. DIAGNOSIS: The ultrasound and magnetic resonance (MR) tests indicated the presence of seroma with amorphous material in the exudate which was confirmed by indirect signs, visible in right breast mammography. Due to suspected cold seroma, an ultrasound-guided needle aspiration was performed for the cytological analysis of the effusion which highlighted the presence of a number of large-sized atypical cells with an irregular nucleus with CD30 immunoreactivity, leucocyte common antigen (CD45) compatible with the BI-ALCL diagnosis. INTERVENTIONS: In our case, a capsulectomy was performed because the disease was limited inside the capsule and periprosthetic seroma. The final histological examination confirmed the stage. LESSONS: The patient is being monitored and shows no signs of recurrence of disease >24 months after surgery. CONCLUSION: A diagnosis of BI-ALCL can be reached using new radiological indicators, such as fibrin, which is clearly visible by MR in the form of nonvascularized debris of amorphous material hypointense in all sequences, free flowing or adhered to the external surface of the prosthesis.

A machine learning approach on multiscale texture analysis for breast microcalcification diagnosis.

BACKGROUND: Screening programs use mammography as primary diagnostic tool for detecting breast cancer at an early stage. The diagnosis of some lesions, such as microcalcifications, is still difficult today for radiologists. In this paper, we proposed an automatic binary model for discriminating tissue in digital mammograms, as support tool for the radiologists. In particular, we compared the contribution of different methods on the feature selection process in terms of the learning performances and selected features. RESULTS: For each ROI, we extracted textural features on Haar wavelet decompositions and also interest points and corners detected by using Speeded Up Robust Feature (SURF) and Minimum Eigenvalue Algorithm (MinEigenAlg). Then a Random Forest binary classifier is trained on a subset of a sub-set features selected by two different kinds of feature selection techniques, such as filter and embedded methods. We tested the proposed model on 260 ROIs extracted from digital mammograms of the BCDR public database. The best prediction performance for the normal/abnormal and benign/malignant problems reaches a median AUC value of 98.16% and 92.08%, and an accuracy of 97.31% and 88.46%, respectively. The experimental result was comparable with related work performance. CONCLUSIONS: The best performing result obtained with embedded method is more parsimonious than the filter one. The SURF and MinEigen algorithms provide a strong informative content useful for the characterization of microcalcification clusters.

Anaplastic large-cell periprosthetic lymphoma of the breast: could fibrin be an early radiological indicator of the presence of disease?

PURPOSE: The onset characteristics of the anaplastic large cell lymphoma (BI-ALCL) are non-specific and the diagnosis is often difficult and based on clinical suspicion and cytological sampling. The presence of non-pathognomonic radiological signs may delay the diagnosis of BI-ALCL, influencing patient prognosis. This could have an important social impact, considering that the incidence of BI-ALCL correlates with the number of prosthetic implants, which is in constant increase worldwide. The aim of this study was to verify if fibrin can represent a potential early radiological sign of the disease. METHODS: In this study, we present two cases of our series and review the previous studies already described in literature, searching for any early radiological sign of the disease and reporting a diagnostic work-up process for an early diagnosis. RESULTS: Signs clearly recognizable only of magnetic resonance were the following: thickening and hyperemia of the fibrous capsule with seroma and amorphous material (fibrin) present in 8 out of 10 cases (80%) detected on magnetic resonance images (certain or doubtful). CONCLUSION: The presence of fibrin in the periprosthetic effusion, well detectable by magnetic resonance imaging, could represent an early pathognomonic sign of the disease.

Role of the contrast-enhanced spectral mammography for the diagnosis of breast metastases from extramammary neoplasms.

PURPOSE: Extramammary breast tumors are quite unusual but they might represent the first semiotic sign of non negative mammography. Thus, the need for an early and accurate diagnosis is crucial, with the purpose of planning and optimize the therapeuthical strategy and consequently to improve the clinical outcome of patients. METHODS: Due to the intrinsic characteristics of this technique, CESM lends itself as a useful and reliable tool for a complex diagnosis, since it may simultaneously provide both the data of the mammographic semiotic and the dynamic one of an examination with a contrast medium. RESULTS: In this article, the most common radiological signs of this type of lesions are summarized through an analysis of the published literature. The article focuses on the different mammographic semeiotics in primary and secondary malignant lesions in the breast, on the different aspects of metastases deriving from blood and lymphatic spread, as well as on the common analogies between metastatic lesions and fibroadenomas. Moreover, the characteristics of a unique case of breast metastasis from pleural mesothelioma, analyzed by Contrast-Enhanced Spectral Mammography, are described. CONCLUSIONS: On the basis of our experience, CESM could represent an extremely valid method to address a correct diagnosis in complex cases of potentially metastatic lesions.

Fully Automated Support System for Diagnosis of Breast Cancer in Contrast-Enhanced Spectral Mammography Images.

Contrast-Enhanced Spectral Mammography (CESM) is a novelty instrumentation for diagnosing of breast cancer, but it can still be considered operator dependent. In this paper, we proposed a fully automatic system as a diagnostic support tool for the clinicians. For each Region Of Interest (ROI), a features set was extracted from low-energy and recombined images by using different techniques. A Random Forest classifier was trained on a selected subset of significant features by a sequential feature selection algorithm. The proposed Computer-Automated Diagnosis system is tested on 48 ROIs extracted from 53 patients referred to Istituto Tumori "Giovanni Paolo II" of Bari (Italy) from the breast cancer screening phase between March 2017 and June 2018. The present method resulted highly performing in the prediction of benign/malignant ROIs with median values of sensitivity and specificity of 87 . 5 % and 91 . 7 % , respectively. The performance was high compared to the state-of-the-art, even with a moderate/marked level of parenchymal background. Our classification model outperformed the human reader, by increasing the specificity over 8 % . Therefore, our system could represent a valid support tool for radiologists for interpreting CESM images, both reducing the false positive rate and limiting biopsies and surgeries.