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1.
Annu Int Conf IEEE Eng Med Biol Soc ; 2022: 3495-3501, 2022 07.
Article in English | MEDLINE | ID: mdl-36086096

ABSTRACT

Segmentation of the thoracic region and breast tissues is crucial for analyzing and diagnosing the presence of breast masses. This paper introduces a medical image segmentation architecture that aggregates two neural networks based on the state-of-the-art nnU-Net. Additionally, this study proposes a polyvinyl alcohol cryogel (PVA-C) breast phantom, based on its automated segmentation approach, to enable planning and navigation experiments for robotic breast surgery. The dataset consists of multimodality breast MRI of T2W and STIR images obtained from 10 patients. A statistical analysis of segmentation tasks emphasizes the Dice Similarity Coefficient (DSC), segmentation accuracy, sensitivity, and specificity. We first use a single class labeling to segment the breast region and then exploit it as an input for three-class labeling to segment fatty, fibroglandular (FGT), and tumorous tissues. The first network has a 0.95 DCS, while the second network has a 0.95, 0.83, and 0.41 for fat, FGT, and tumor classes, respectively. Clinical Relevance-This research is relevant to the breast surgery community as it establishes a deep learning-based (DL) algorithmic and phantomic foundation for surgical planning and navigation that will exploit preoperative multimodal MRI and intraoperative ultrasound to achieve highly cosmetic breast surgery. In addition, the planning and navigation will guide a robot that can cut, resect, bag, and grasp a tissue mass that encapsulates breast tumors and positive tissue margins. This image-guided robotic approach promises to potentiate the accuracy of breast surgeons and improve patient outcomes.


Subject(s)
Breast Neoplasms , Deep Learning , Robotic Surgical Procedures , Robotics , Breast Neoplasms/diagnostic imaging , Breast Neoplasms/surgery , Female , Humans , Magnetic Resonance Imaging/methods
2.
Radiol Case Rep ; 14(12): 1500-1505, 2019 Dec.
Article in English | MEDLINE | ID: mdl-31660096

ABSTRACT

While metastatic disease to the breast has been documented from many primary neoplasms with incidence ranging from 0.2% to approximately 2.7% among reported clinical cases, breast cancer metastases resulting from a primary lung neoplasm is significantly less commonly reported in the literature. Routes of metastatic spread of lung neoplasms include both hematologic and lymphatic routes. We present a case of biopsy proven lymphangitic spread of primary lung neoplasm to the ipsilateral breast and axillary nodes mimicking inflammatory breast cancer. It remains crucial to differentiate between extramammary diseases with metastatic deposits in the breast from a primary breast neoplasm as treatment remains very different between these entities. As in this case, the pathologic, histologic, and immunohistochemistry analyses are critical in determining the origin of the malignant cells and formulating a treatment plan.

3.
AJR Am J Roentgenol ; 212(3): 696-705, 2019 03.
Article in English | MEDLINE | ID: mdl-30620672

ABSTRACT

OBJECTIVE: The purpose of this retrospective study was to evaluate the diagnostic performance of breast-specific gamma imaging (BSGI) and breast MRI in assessing for residual tumor after neoadjuvant chemotherapy (NAC) in patients with breast cancer. MATERIALS AND METHODS: A total of 114 patients underwent BSGI and MRI for initial staging as well as after undergoing NAC. Of those, 112 underwent subsequent definitive breast surgery. Thirty of the 114 patients had a complete pathologic response to NAC. RESULTS: BSGI and MRI had comparable sensitivities in detecting residual tumor after NAC (70% vs 83%). BSGI had a higher specificity than MRI in accurately determining complete response after NAC (90% vs 60%). CONCLUSION: BSGI may be a useful adjunctive tool for predicting a complete pathologic response to NAC.


Subject(s)
Breast Neoplasms/diagnostic imaging , Breast Neoplasms/therapy , Magnetic Resonance Imaging/methods , Radionuclide Imaging/methods , Chemotherapy, Adjuvant , Contrast Media , Female , Humans , Middle Aged , Neoadjuvant Therapy , Radiopharmaceuticals , Retrospective Studies , Technetium Tc 99m Sestamibi
4.
Radiol Case Rep ; 13(5): 933-935, 2018 Oct.
Article in English | MEDLINE | ID: mdl-30093929

ABSTRACT

Hyperdense middle cerebral artery (MCA) is a classic sign of acute thromboembolic disease. Simultaneous bilateral occurrence is uncommon and traditionally attributed to physiological hemoconcentration or attributable to imaging artifact. We present the case of a 71-year-old man whose admission noncontrast computed tomography (CT) demonstrated bilateral hyperdense middle cerebral arteries without other radiographic evidence of acute stroke. CT angiography confirmed bilateral MCA, M1 segment vascular occlusion and follow-up noncontrast CT demonstrated MCA territory infarctions.

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