MRI Training Course for Technologists

Apr 24th, 2016May 5th, 2016
Milwaukee, WI
US
https://www.mtmi.net/course/mri-training-course-technologists
You should attend this course if you are a radiologic technologist or if you have experience in the imaging sciences with basic or no previous MR experience and are interested in learning the principles necessary to operate an MR imager.
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Example cases illustrate the double-edged role of large language model (LLM) rationale quality. (A) A 50-year-old female patient with a palpable anterior chest wall mass (correct diagnosis: solitary fibrous tumor of the pleura). The LLM incorrectly suggested synovial sarcoma but provided a persuasive rationale (quality score: 4 of 5), describing a well-defined nodule at axial contrast-enhanced CT spanning the pleura and intercostal space with heterogeneous strong enhancement. Four of five readers (80%) accepted the incorrect suggestion. FDG = fluorodeoxyglucose. (B) A 61-year-old male patient with diabetes presented with cough, sputum, and dyspnea (correct diagnosis: mucormycosis). The LLM correctly suggested mucormycosis with an excellent rationale (quality score: 5 of 5), integrating the reverse halo sign on serial axial CT images and rapidly progressive cavitary lesions. Three of five readers initially selected incorrect diagnoses; after LLM output, all five selected the correct diagnosis (100% acceptance). Blue and orange reader icons denote high- and low-expertise readers, respectively.
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Stepped reminders boost CT lung cancer screening
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Trial findings directly address the current lack of effective lung cancer screening interventions.
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Model confidence, reader expertise affect reader-LLM collaboration
By Amerigo Allegretto
Successful human-LLM collaboration is associated with model confidence and reader expertise in chest imaging.
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Example cases illustrate the double-edged role of large language model (LLM) rationale quality. (A) A 50-year-old female patient with a palpable anterior chest wall mass (correct diagnosis: solitary fibrous tumor of the pleura). The LLM incorrectly suggested synovial sarcoma but provided a persuasive rationale (quality score: 4 of 5), describing a well-defined nodule at axial contrast-enhanced CT spanning the pleura and intercostal space with heterogeneous strong enhancement. Four of five readers (80%) accepted the incorrect suggestion. FDG = fluorodeoxyglucose. (B) A 61-year-old male patient with diabetes presented with cough, sputum, and dyspnea (correct diagnosis: mucormycosis). The LLM correctly suggested mucormycosis with an excellent rationale (quality score: 5 of 5), integrating the reverse halo sign on serial axial CT images and rapidly progressive cavitary lesions. Three of five readers initially selected incorrect diagnoses; after LLM output, all five selected the correct diagnosis (100% acceptance). Blue and orange reader icons denote high- and low-expertise readers, respectively.
PET/CT predicts response to neoadjuvant therapy in breast cancer
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Monitoring neoadjuvant therapy response in HER2-positive breast cancer is challenging with existing tools.
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Ga-68 HER2-PET/CT images before neoadjuvant therapy, at end of second cycle, and before surgery. (A) Baseline scan demonstrated soft-tissue lesion measuring approximately 2.3 × 2.2 cm in upper outer quadrant of left breast, with marked radiotracer uptake and SUVmax of 10.1. (B) At end of second cycle, imaging revealed residual lesion of approximately 2.2 × 1.0 cm in same region, without abnormal radiotracer accumulation. (C) Preoperative imaging demonstrated further reduction in lesion size to approximately 2.0 × 0.6 cm, with no abnormal tracer uptake detected.
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What happened at a Redwood City hospital in California in 2023.
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NME breast lesions have high malignancy rate on MRI-guided biopsy
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Biopsies from women with a known ipsilateral malignancy have a higher frequency of breast cancer.
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Many women interested in AI-based risk assessment for breast cancer
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Survey findings also show that most women at higher risk are interested in additional screening tests.
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CT 5-star quality rating system supports optimization
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The rating framework demonstrated robust reproducibility, with three-reader concordance reaching up to 93% in highly standardized centers.
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READ-DVT model performs well in finding DVT from ultrasound reports
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The AI model accurately identified the presence or absence of deep vein thrombosis on unstructured ultrasound reports.
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Bone scan testing has fallen 35% among Medicare beneficiaries
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Declines in testing were greatest among certain underserved groups.
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MRI-based models may predict atypical brain development in children
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The models could provide a framework for identifying which adolescents are at higher risk of developing psychiatric conditions.
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Avoiding the ED cuts urgent CT turnaround time by half
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