Glazebrook, Katrina N.

Abstract Objective To evaluate the clinical value of breast MRI in radiation-associated angiosarcoma of the breast (RAASB) for assessing disease extent at diagnosis and after neoadjuvant therapy compared with clinical examination and surgical pathology. Methods This IRB-approved retrospective study included 25 patients with breast MRIs between1995 and 2020. MRI estimated disease extent was compared to clinical exam and surgical pathology. MRI findings were evaluated for additional disease and impact on clinical management. Agreement between MRI and clinical assessment of disease was evaluated using Cohen’s kappa statistic. Results Baseline MRI demonstrated moderate agreement with clinical disease extent (Cohen’s κ = 0.44; 95% CI, 0.14-0.75). Thirteen of 24 (54%) of MRIs reflected clinical exam, 4/24 (17%) MRIs underestimated disease, and 5/24 (21%) MRIs overestimated disease. Baseline MRI changed surgical management in 4/24 (17%). In 8 patients who proceeded directly to surgery, MRI reflected pathology in 6/8 (75%). In 10 patients with post-neoadjuvant MRI, 4/10 (40%) pathology and MRI extent were similar, 5/10 (50%) MRI overestimated disease, and 1/10 (10%) MRI underestimated disease. Conclusion MRI has clinical value in assessing RAASB with the potential for significantly altering surgical management. In this small cohort, post-neoadjuvant MRI demonstrated limited additional clinical value. Larger studies are needed to define the optimal role and timing of post-neoadjuvant MRI. Advances in knowledge Baseline MRI detected additional disease not identified on initial clinical exam in 5/24 (21%) and changed surgical management in 4/24 (17%). Although baseline MRI demonstrated moderate agreement with clinical examination, post-neoadjuvant MRI frequently overestimated residual disease when compared with final pathology.

Abstract Objectives To describe the feasibility and evaluate the performance of multiphasic photon-counting detector (PCD) CT for detecting breast cancer and nodal metastases with correlative dynamic breast MRI and digital mammography as the reference standard. Methods Adult females with biopsy-proven breast cancer undergoing staging breast MRI were prospectively recruited to undergo a multiphasic PCD-CT using a 3-phase protocol: a non-contrast ultra-high-resolution (UHR) scan and 2 intravenous contrast-enhanced scans with 50 and 180 s delay. Three breast radiologists compared CT characteristics of the index malignancy, regional lymphadenopathy, and extramammary findings to MRI. Results Thirteen patients underwent both an MRI and PCD-CT (mean age: 53 years, range: 36-75 years). Eleven of thirteen cases demonstrated suspicious mass or non-mass enhancement on PCD-CT when compared to MRI. All cases with metastatic lymphadenopathy (3/3 cases) demonstrated early avid enhancement similar to the index malignancy. All cases with multifocal or multicentric disease on MRI were also identified on PCD-CT (3/3 cases), including a 4 mm suspicious satellite lesion. Four of five patients with residual suspicious post-biopsy calcifications on mammograms were detected on the UHR PCD-CT scan. Owing to increased field-of-view at PCD-CT, a 5 mm thoracic vertebral metastasis was identified at PCD-CT and not with the breast MRI. Conclusions A 3-phase PCD-CT scan protocol shows initial promising results in characterizing breast cancer and regional lymphadenopathy similar to MRI and detects microcalcifications in 80% of cases. Advances in knowledge UHR and spectral capabilities of PCD-CT may allow for comprehensive characterization of breast cancer and may represent an alternative to breast MRI in select cases.

Abstract Adenomyoepithelioma (AME) is a rare, usually benign breast neoplasm with low potential for malignant transformation. Imaging features are nonspecific and overlap with other benign and malignant breast lesions. On mammography, AME most often presents as a mass, usually oval in shape, with variable reported margins. Less commonly, AME can present mammographically as an asymmetry or can be mammographically occult. Associated calcifications are uncommon. On US, AME is usually seen as a hypoechoic oval mass, but it can also manifest as a complex cystic and solid mass. On US, the majority of AME have noncircumscribed margins (indistinct, angular, or microlobulated). Internal vascularity is usually present, and posterior enhancement can be seen. Although there is limited literature on MRI features, the most frequent finding is an irregular mass with washout kinetics; T2 hyperintensity can be observed. These nonspecific and often suspicious imaging features usually merit biopsy. On histologic analysis, AME is characterized by a biphasic proliferation of myoepithelial and epithelial cells. Pathologic diagnosis can be difficult due to the variety of histologic features of AME and heterogeneity in these tumors, especially when sampling is limited, such as in core needle biopsies. Wide local surgical excision of AME is recommended due to potential for recurrence and malignant transformation.

Abstract Purpose: To evaluate the impact of trimodality treatment versus monotherapy or dual therapy for radiation-associated angiosarcoma of the breast (RAASB) after prior breast cancer treatment. Experimental Design: With Institutional Review Board approval, we identified patients diagnosed with RAASB and abstracted data on disease presentation, treatment, and oncologic outcomes. Trimodality therapy included (i) taxane induction, (ii) concurrent taxane/radiation, and then (iii) surgical resection with wide margins. Results: A total of 38 patients (median age 69 years) met inclusion criteria. Sixteen received trimodality therapy and 22 monotherapy/dual therapy. Skin involvement and disease extent were similar in both groups. All trimodality patients required reconstructive procedures for wound closure/coverage, compared with 48% of monotherapy/dual therapy patients (P < 0.001). Twelve of 16 (75%) patients receiving trimodality therapy had a pathologic complete response (pCR). With median follow-up of 5.6 years, none had local recurrence, 1 patient (6%) had distant recurrence, and no patients died. Among 22 patients in the monotherapy/dual therapy group, 10 (45%) had local recurrence, 8 (36%) had distant recurrence, and 7 (32%) died of disease. Trimodality therapy demonstrated significantly better 5-year recurrence-free survival [RFS; 93.8% vs. 42.9%; P = 0.004; HR, 7.6 (95% confidence interval, CI: 1.3–44.2)]. Combining all patients with RAASB regardless of treatment, local recurrence was associated with subsequent distant recurrence (HR, 9.0; P = 0.002); distant recurrence developed in 3 of 28 (11%) patients without local recurrence compared with 6 of 10 (60%) with local recurrence. The trimodality group had more surgical complications that required reoperation or prolonged healing. Conclusions: Trimodality therapy for RAASB was more toxic but is promising, with a high rate of pCR, durable local control, and improved RFS.

Infectious diseases of the breast can demonstrate a wide variety of clinical presentations and imaging appearances. Breast abscesses are often a complication of infectious mastitis of the breast. Puerperal mastitis is the most common cause of breast abscess, typically affecting postpartum females. Often diagnosed clinically, it is usually treated with antibiotics without need for imaging. Non-puerperal mastitis is relatively uncommon and typically subareolar in location. Patients can present with asymmetric breast thickening, a palpable lump, nipple discharge, or axillary adenopathy. These presentations can mimic malignancy. Herein, this pictorial review demonstrates imaging findings of common and uncommon infectious processes of the breast and clinically important mimickers of breast infection.

AbstractBackgroundDual‐energy CT with virtual noncalcium (VNCa) images allows the evaluation of focal intramedullary bone marrow involvement in patients with multiple myeloma. However, current commercial VNCa techniques suffer from excessive image noise and artifacts due to material decomposition used in synthesizing VNCa images.ObjectivesIn this work, we aim to improve VNCa image quality for the assessment of focal multiple myeloma, using an Artificial intelligence based Generalizable Algorithm for mulTi‐Energy CT (AGATE) method.Materials and methodsAGATE method used a custom dual‐task convolutional neural network (CNN) that concurrently carries out material classification and quantification. The material classification task provided an auxiliary regularization to the material quantification task. CNN parameters were optimized using custom loss functions that involved cross‐entropy, physics‐informed constraints, structural redundancy in spectral and material images, and texture information in spectral images. For training data, CT phantoms (diameters 30 to 45 cm) with tissue‐mimicking inserts were scanned on a third generation dual‐source CT system. Scans were performed at routine dose and half of the routine dose. Small image patches (i.e., 40 × 40 pixels) of tissue‐mimicking inserts with known basis material densities were extracted for training samples. Numerically simulated insert materials with various shapes increased diversity of training samples. Generalizability of AGATE was evaluated using CT images from phantoms and patients. In phantoms, material decomposition accuracy was estimated using mean‐absolute‐percent‐error (MAPE), using physical inserts that were not used during the training. Noise power spectrum (NPS) and modulation transfer function (MTF) were compared across phantom sizes and radiation dose levels. Five patients with multiple myeloma underwent dual‐energy CT, with VNCa images generated using a commercial method and AGATE. Two fellowship‐trained musculoskeletal radiologists reviewed the VNCa images (commercial and AGATE) side‐by‐side using a dual‐monitor display, blinded to VNCa type, rating the image quality for focal multiple myeloma lesion visualization using a 5‐level Likert comparison scale (−2 = worse visualization and diagnostic confidence, −1 = worse visualization but equivalent diagnostic confidence, 0 = equivalent visualization and diagnostic confidence, 1 = improved visualization but equivalent diagnostic confidence, 2 = improved visualization and diagnostic confidence). A post hoc assignment of comparison ratings was performed to rank AGATE images in comparison to commercial ones.ResultsAGATE demonstrated consistent material quantification accuracy across phantom sizes and radiation dose levels, with MAPE ranging from 0.7% to 4.4% across all testing materials. Compared to commercial VNCa images, the AGATE‐synthesized VNCa images yielded considerably lower image noise (50–77% noise reduction) without compromising noise texture or spatial resolution across different phantom sizes and two radiation doses. AGATE VNCa images had markedly reduced area under NPS curves and maintained NPS peak frequency (0.7 lp/cm to 1.0 lp/cm), with similar MTF curves (50% MTF at 3.0 lp/cm). In patients, AGATE demonstrated reduced image noise and artifacts with improved delineation of focal multiple myeloma lesions (all readers comparison scores indicating improved overall diagnostic image quality [scores 1 or 2]).ConclusionsAGATE demonstrated reduced noise and artifacts in VNCa images and ability to improve visualization of bone marrow lesions for assessing multiple myeloma.

Abstract Objective. To develop a convolutional neural network (CNN) noise reduction technique for ultra-high-resolution photon-counting detector computed tomography (UHR-PCD-CT) that can be efficiently implemented using only clinically available reconstructed images. The developed technique was demonstrated for skeletal survey, lung screening, and head angiography (CTA). Approach . There were 39 participants enrolled in this study, each received a UHR-PCD and an energy integrating detector (EID) CT scan. The developed CNN noise reduction technique uses image-based noise insertion and UHR-PCD-CT images to train a U-Net via supervised learning. For each application, 13 patient scans were reconstructed using filtered back projection (FBP) and iterative reconstruction (IR) and allocated into training, validation, and testing datasets (9:1:3). The subtraction of FBP and IR images resulted in approximately noise-only images. The 5-slice average of IR produced a thick reference image. The CNN training input consisted of thick reference images with reinsertion of spatially decoupled noise-only images. The training target consisted of the corresponding thick reference images without noise insertion. Performance was evaluated based on difference images, line profiles, noise measurements, nonlinear perturbation assessment, and radiologist visual assessment. UHR-PCD-CT images were compared with EID images (clinical standard). Main results. Up to 89% noise reduction was achieved using the proposed CNN. Nonlinear perturbation assessment indicated reasonable retention of 1 mm radius and 1000 HU contrast signals (>80% for skeletal survey and head CTA, >50% for lung screening). A contour plot indicated reduced retention for small-radius and low contrast perturbations. Radiologists preferred CNN over IR for UHR-PCD-CT noise reduction. Additionally, UHR-PCD-CT with CNN was preferred over standard resolution EID-CT images. Significance. CT images reconstructed with very sharp kernels and/or thin sections suffer from increased image noise. Deep learning noise reduction can be used to offset noise level and increase utility of UHR-PCD-CT images.

Adenosquamous carcinoma of the breast is a rare subtype of metaplastic carcinoma, which accounts for <1% of invasive breast malignancy. Metaplastic carcinoma is usually high grade and aggressive with typically reported benign imaging features when compared to invasive ductal carcinoma. However, the adenosquamous variant is a subtype with a more favorable prognosis. Within the literature, there is limited imaging description with case studies focusing on metaplastic carcinoma. Herein, we report seven cases of the adenosquamous subtype describing the imaging findings with correlation to clinical history and pathology. The majority of patients (n = 6) presented with palpable breast masses. One patient was identified through screening mammography. Mammographically (n = 6), tumors appeared as irregular masses. Sonographically (n = 7), tumors appeared as irregular masses ranging from solid to mixed solid/cystic masses. On MRI (n = 1), one tumor appeared as an irregular rim enhancing mass. FDG PET/CT (n = 2) and whole-body bone scan (n = 1) were also available for review. The majority of tumors were low-grade (n = 6) with only one high-grade tumor. This case series of seven patients demonstrated predominantly suspicious imaging features despite the majority being low-grade tumors.