Purpose: To prospectively evaluate the feasibility of 3-D radioguided occult lesion localization (iROLL) and to compare iROLL with wire-guided localization (WGL) in patients with early-stage breast cancer undergoing breast-conserving surgery and sentinel lymph node biopsy (SLNB).
Methods: WGL (standard procedure) and iROLL in combination with SLNB were performed in 31 women (mean age 65.1 ± 11.2 years) with early-stage breast cancer and clinically negative axillae. Patient comfort in respect of both methods was assessed using a ten point scale. SLNB and iROLL were guided by freehand SPECT (fhSPECT). The results of the novel 3-D image-based method were compared with those of WGL, ultrasound-based lesion localization, and histopathology.
Results: iROLL successfully detected the malignant primary and at least one sentinel lymph node in 97% of patients. In a single patient (3%), only iROLL, and not WGL, enabled lesion localization. The variability between fhSPECT and ultrasound-based depth localization of breast lesions was low (1.2 ± 1.4 mm). Clear margins were achieved in 81% of the patients; however, precise prediction of clear histopathological surgical margins was not feasible using iROLL. Patients rated iROLL as less painful than WGL with a pain score 0.8 ± 1.2 points (p < 0.01) lower than the score for iROLL.
Conclusion: iROLL is a well-tolerated and feasible technique for localizing early-stage breast cancer in the course of breast-conserving surgery, and is a suitable replacement for WGL. As a single image-based procedure for localization of breast lesions and sentinel nodes, iROLL may improve the entire surgical procedure. However, no advantages of the image-guided procedure were found with regard to prediction of complete tumour resection.
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http://dx.doi.org/10.1007/s00259-015-3121-7 | DOI Listing |
Acta Neurol Belg
January 2025
Department of Radiology, CHU UCL Namur site Godinne, Université catholique de Louvain, Avenue G. Thérasse 1, Yvoir, 5530, Belgium.
J Imaging Inform Med
January 2025
Department of Software Convergence, Seoul Women's University, Hwarango 621, Nowongu, Seoul, 01797, Republic of Korea.
In this paper, we propose a method to address the class imbalance learning in the classification of focal liver lesions (FLLs) from abdominal CT images. Class imbalance is a significant challenge in medical image analysis, making it difficult for machine learning models to learn to classify them accurately. To overcome this, we propose a class-wise combination of mixture-based data augmentation (CCDA) method that uses two mixture-based data augmentation techniques, MixUp and AugMix.
View Article and Find Full Text PDFCardiovasc Intervent Radiol
January 2025
Department of Radiology, University Hospital of Saint Etienne, Avenue Albert Raymond, 42055, Saint-Priest-en-Jarez, Saint-Etienne Cedex 2, France.
Introduction: Aneurysmal bone cysts are locally aggressive bone lesions. The aim of this study was to evaluate safety and effectiveness of radio-opaque gelified ethanol sclerotherapy in treating primary aneurysmal bone cyst.
Materials And Methods: In this single-center, retrospective study (January 1st, 2012, to June 30th, 2024), 32 patients with primary aneurysmal bone cysts were treated with percutaneous sclerotherapy using radio-opaque gelified ethanol at various skeletal sites.
BMJ Case Rep
January 2025
Cardiology, AIIMS, New Delhi, India
A young man in his 30s presented to us with multiple episodes of syncope and exertional dyspnoea for the last 2 weeks. He was diagnosed with squamous cell carcinoma of the lower one-third of the oesophagus in 2021 for which he was treated with neoadjuvant chemoradiotherapy, followed by McKeown oesophagectomy. At 2-year follow-up, he had developed a soft tissue swelling in the scalp, which was diagnosed as a tumour recurrence and radiotherapy was initiated.
View Article and Find Full Text PDFBiomed Phys Eng Express
January 2025
Shandong Normal University, Jinan, Jinan, Shandong, 250014, CHINA.
In the medical field, endoscopic video analysis is crucial for disease diagnosis and minimally invasive surgery. The Endoscopic Foundation Models (Endo- FM) utilize large-scale self-supervised pre-training on endoscopic video data and leverage video transformer models to capture long-range spatiotemporal dependencies. However, detecting complex lesions such as gastrointestinal metaplasia (GIM) in endoscopic videos remains challenging due to unclear boundaries and indistinct features, and Endo-FM has not demonstrated good performance.
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