Background: Solitary fibrous tumors (SFT) are uncommon mesenchymal neoplasms which can arise in any anatomical location. Pleural SFTs have been most frequently documented; however, breast SFT is an exceedingly rare entity and seldom present in male breast, with only 8 previously reported cases. Recently, STAT6 immunostaining was considered to be a definitive marker of SFT, however, no case of the male breast SFT showing STAT6 positivity preoperatively has been reported. Methods and Results: We describe a case of breast SFT in a 73-year-old male patient with a 12-month history of a palpable breast mass. The only associated clinical symptom was bilateral gynecomastia. An ultrasound scan examination revealed an oval, well-circumscribed and hypoechoic mass with hypervascularity. A core-needle biopsy was performed, and microscopic examination with immunohistochemistry confirmed the diagnosis of SFT. He underwent a complete surgical resection with clear margins, and there were no signs of high cellularity, remarkable mitotic activity, pleomorphism, hemorrhage or necrosis. Conclusion: A perioperative immunohistochemical evaluation for diffuse and intense nuclear expression of STAT6 was helpful to distinguish SFT from myofibroblastoma. We, herein, describe the first case of SFT in a male breast, confirmed by STAT6 immunostaining positivity. We also conducted a literature review of all previous cases of breast SFTs.
PurposePositron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) are useful for detecting axillary lymph node (ALN) metastasis in invasive ductal breast cancer (IDC); however, there is limited clinical evidence to demonstrate the effectiveness of the combination of PET/CT plus MRI. Further axillary surgery is not recommended against ALN micrometastasis (lesion ≤2 mm) seen in sentinel lymph nodes, especially for patients who received proper adjuvant therapy. We aimed to evaluate the efficacy of a prediction model based on PET/CT plus MRI for ALN macrometastasis (lesion >2 mm) and explore the possibility of risk stratification of patients using the preoperative PET/CT plus MRI and biopsy findings.Materials and methodsWe retrospectively investigated 361 female patients (370 axillae; mean age, 56 years ± 12 [standard deviation]) who underwent surgery for primary IDC at a single center between April 2017 and March 2020. We constructed a prediction model with logistic regression. Patients were divided into low-risk and high-risk groups using a simple integer risk score, and the false negative rate for ALN macrometastasis was calculated to assess the validity. Internal validation was also achieved using a 5-fold cross-validation.ResultsThe PET/CT plus MRI model included five predictor variables: maximum standardized uptake value of primary tumor and ALN, primary tumor size, ALN cortical thickness, and histological grade. In the derivation (296 axillae) and validation (74 axillae) cohorts, 54% and 61% of patients, respectively, were classified as low-risk, with a false-negative rate of 11%. Five-fold cross-validation yielded an accuracy of 0.875.ConclusionsOur findings demonstrate the validity of the PET/CT plus MRI prediction model for ALN macrometastases. This model may aid the preoperative identification of low-risk patients for ALN macrometastasis and provide helpful information for PET/MRI interpretation.
Objective We occasionally observed internal mammary lymph node metastases of breast cancer in a clinical setting. However, unlike a standard treatment in axillary metastasis, surgical resection for internal mammary lymph node metastasis is not prevalent because of unclear safety and benefits. Thus, we aimed to evaluate the diagnostic ability and clinical outcomes of positron emission tomography/computed tomography and video-assisted thoracoscopic surgery. Methods We retrospectively investigated 34 patients with breast cancer with abnormal 18F-fluorodeoxyglucose uptake in internal mammary lymph nodes, at a single centre, between January 2015 and June 2022 and identified 11 female patients (mean age ± SD, 51.5 ± 12.9 years) who underwent video-assisted thoracoscopic surgery resection. Positron emission tomography/computed tomography was used to determine the clinical stage. We reviewed the surgical pathology of eleven and two patients who underwent direct-view internal mammary lymph node resection to calculate the positive predictive value of positron emission tomography/computed tomography. Results Ipsilateral fluorodeoxyglucose accumulation was observed, with an average maximum standardized uptake value of 8.9 (range, 3.1–24.0). No perioperative complications occurred, and all patients who underwent video-assisted thoracoscopic surgery alone were discharged from the hospital on post-operative day 2 or 3. The estimated positive predictive value was 80%. All patients were alive, and seven of nine patients with metastasis were relapse-free, at a mean follow-up period of 17.9 months (range, 1–51). However, two patients had recurrence at 16 and 14 months after surgery for internal mammary lymph node relapse. Conclusions Radiotherapy is the standard treatment for suspected internal mammary lymph node metastasis detected using positron emission tomography/computed tomography; however, we could safely perform minimally invasive video-assisted thoracoscopic surgery resection, leading to a definite pathological diagnosis.
Background: Positron emission tomography/computed tomography (PET/CT) and magnetic resonance imaging (MRI) are useful imaging modalities for the preoperative nodal staging in breast cancer; however, clinical evidence demonstrating the diagnostic accuracy of the combination of PET/CT and MRI is limited. The purpose of this study is to establish a clinical prediction model based on PET/CT plus contrast-enhanced MRI for ALN metastasis, and explore the possibility of non-invasive patients’ risk stratification using the PET/CT plus MRI model preoperatively. Methods: A total of 361 women (370 axillae; mean age, 56 years ± 12 [standard deviation]) who underwent surgery for primary invasive ductal carcinoma at a single institution between April 2017 and March 2020 were evaluated. Subjects were divided into two cohorts: a derivation cohort (n = 333) and a validation cohort (n = 37). In the derivation cohort, we constructed a prediction model with logistic regression to estimate the potential explanatory variables obtained by PET/CT, MRI, and preoperative core-needle biopsy. Using a simple integer risk score, patients were divided into low-risk and high-risk groups. We assessed the predictive ability of the PET/CT plus MRI model using the area under the curve (AUC), and internal validation was achieved by risk scoring system in the validation cohort. Results: The PET/CT plus MRI model included five predictor variables: maximum standardized uptake value of primary tumor and ALN, primary tumor size, ALN cortical thickness, and histological grade. The PET/CT plus MRI model had significantly improved AUC of 0.867 (p < 0.05) as compared to those of the PET/CT model (AUC = 0.821) and MRI model (AUC = 0.815). We assigned the weighted scores to each retained variables in the PET/CT plus MRI model, and determined the optimal cut-off value of 7 (range, 0−17). In the derivation and validation cohorts, 55% and 65% of the patients were classified as low-risk by the risk scoring system, with negative predictive values of 97% and 100%, respectively. Conclusions: Our findings demonstrated a better diagnostic accuracy of the clinical prediction model utilizing both PET/CT and MRI than previous models based on either PET/CT or MRI, and the negative predictive value of 97% was not inferior to that of sentinel lymph node biopsy. Thus, the preoperative risk evaluation of axillary lymph node macrometastasis using our integrated model could be useful while considering individualized therapy for patients with invasive ductal breast cancer. Further validation should be performed for clinical applications. Citation Format: Shun Kawaguchi, Nobuko Tamura, Kiyo Tanaka, Yoko Kobayashi, Junichiro Sato, Keiichi Kinowaki, Masato Shiiba, Makiko Ishihara, Hidetaka Kawabata. Diagnostic Accuracy of 18F-FDG PET/CT plus Contrast-Enhanced MRI for Axillary Lymph Node Metastasis Involved in Invasive Ductal Carcinoma [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P5-01-02.
Background Invasive lobular carcinoma (ILC) grows diffusely in a single-cell fashion, sometimes presenting only subtle changes in preoperative imaging; therefore, axillary lymph node (ALN) metastases of ILC are difficult to detect using magnetic resonance imaging (MRI). Preoperative underestimation of nodal burden occurs more frequently in ILC than in invasive ductal carcinoma (IDC), however, the morphological assessment for metastatic ALNs of ILC have not fully been investigated. We hypothesized that the high false-negative rate in ILC is caused by the discrepancy in the MRI findings of ALN metastases between ILC and IDC and aimed to identify the MRI finding with a strong correlation with ALN metastasis of ILC. Method This retrospective analysis included 120 female patients (mean ± standard deviation age, 57.2 ± 11.2 years) who underwent upfront surgery for ILC at a single center between April 2011 and June 2022. Of the 120 patients, 35 (29%) had ALN metastasis. Using logistic regression, we constructed prediction models based on MRI findings: primary tumor size, focal cortical thickening (FCT), cortical thickness, long-axis diameter (LAD), and loss of hilum (LOH). Results The area under the curves were 0.917 (95% confidence interval [CI] 0.869–0.968), 0.827 (95% CI 0.758–0.896), 0.754 (95% CI 0.671–0.837), and 0.621 (95% CI 0.531–0.711) for the FCT, cortical thickness, LAD, and LOH models, respectively. Conclusions FCT may be the most relevant MRI finding for ALN metastasis of ILC, and although its prediction model may lead to less underestimation of the nodal burden, rigorous external validation is required. Supplementary Information The online version contains supplementary material available at 10.1007/s12282-023-01457-2.
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