Primary Breast Lymphoma: A Rare Clinical Entity

Radiomics based on 18 F-FDG PET/CT could differentiate breast carcinoma from breast lymphoma using machine-learning approach: A preliminary study

PURPOSE

Our study assessed the ability ¹⁸ F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) radiomics to differentiate breast carcinoma from breast lymphoma using machine-learning approach.

METHODS

Sixty-five breast nodules from 44 patients diagnosed as breast carcinoma or breast lymphoma were included. Standardized uptake value (SUV) and radiomic features from CT and PET images were extracted using local image features extraction software. Six discriminative models including PETa (based on clinical, SUV and radiomic features from PET images), PETb (SUV and radiomic features from PET images), PETc (radiomic features only from PET images), CTa (clinical and radiomic features from CT images), CTb (radiomic features only from CT images), and SUV model were generated using least absolute shrinkage and selection operator method and linear discriminant analysis. The areas under the receiver operating characteristic curve (AUCs), accuracy, sensitivity, and specificity were calculated to evaluate the discriminative ability of these models.

RESULTS

PETa and CTa models showed the best ability to differentiation in training and validation group (AUCs of 0.867 and 0.806 for PETa model, AUCs of 0.891 and 0.759 for CTa model, respectively).

CONCLUSION

Models based on clinical, SUV, and radiomic features of ¹⁸ F-FDG PET/CT images could accurately discriminate breast carcinoma from breast lymphoma.

Ability of 18F-FDG PET/CT Radiomic Features to Distinguish Breast Carcinoma from Breast Lymphoma

Purpose. To investigate the value of SUV metrics and radiomic features based on the ability of ¹⁸F-FDG PET/CT in differentiating between breast lymphoma and breast carcinoma. Methods. A total of 67 breast nodules from 44 patients who underwent ¹⁸F-FDG PET/CT pretreatment were retrospectively analyzed. Radiomic parameters and SUV metrics were extracted using the LIFEx package on PET and CT images. All texture parameters were divided into six groups: histogram (HISTO), SHAPE, gray-level co-occurrence matrix (GLCM), gray-level run-length matrix (GLRLM), neighborhood gray-level different matrix (NGLDM), and gray-level zone-length matrix (GLZLM). Receiver operating characteristics (ROC) curves were generated to evaluate the discriminative ability of each parameter, and the optimal parameter in each group was selected to generate a new predictive variable by using binary logistic regression. PET predictive variable, CT predictive variable, the combination of PET and CT predictive variables, and SUV_max were compared in terms of areas under the curve (AUCs), sensitivity, specificity, and accuracy. Results. Except for SUVmin (p=0.971), the averages of FDG uptake metrics of lymphoma were significantly higher than those of carcinoma (p ≤ 0.001), with the following median values: SUV_mean, 4.75 versus 2.38 g/ml (P < 0.001); SUV_std, 2.04 versus 0.88 g/ml (P=0.001); SUV_max, 10.69 versus 4.76 g/ml (P=0.001); SUV_peak, 9.15 versus 2.78 g/ml (P < 0.001); TLG, 42.24 versus 9.90 (P < 0.001). In the ROC curves analysis based on radiomic features and SUV_max, the AUC for SUV_max was 0.747, for CT texture parameters was 0.729, for PET texture parameters was 0.751, and for the combination of CT and PET texture parameters was 0.771. Conclusion. The SUV metrics in ¹⁸FDG PET/CT images showed a potential ability in the differentiation between breast lymphoma and carcinoma. The combination of SUV_max and PET/CT texture analysis may be promising to provide an effectively discriminant modality for the differential diagnosis of breast lymphoma and carcinoma, even for the differentiation of subtypes of lymphoma.

Primary breast diffuse large B cell lymphoma - report of 6 cases from South India with review of literature

The breast is an uncommon site of involvement in non-Hodgkin lymphoma, and primary breast lymphoma (PBL) is a disease localized to one or both breasts with or without regional lymph nodes involvement. The objectives of the study were to review the clinical profile, epidemiological parameters and assess the outcomes exclusively in women with primary diffuse large B cell lymphoma (DLBCL) of breast. This was a retrospective observational study done at Kidwai Memorial Institute of Oncology, Bangalore, India. We studied 6 consecutive female patients, diagnosed with primary DLBCL of breast between January 2007 and December 2011. Median age at diagnosis was 45 years (range 33-56 years). B symptoms were present in 3 patients. One patient had central nervous system involvement with high risk International Prognostic Index (IPI). 3 patients underwent lumpectomy and 3 core biopsy. All received anthracycline based chemotherapy, with rituximab in one patient and 3 received involved field radiotherapy. Three patients achieved complete response; one is disease free at 15 months. Two relapsed at 8 and 53 months and both were alive with disease. One achieved partial response, one had progressive disease and response was not assessed in one (but died due to toxicity). Primary breast DLBCL is a rare entity and multi modality combination therapy involving chemotherapy and radiation can give a longer overall survival and thus avoiding the morbidity of mastectomy.