- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
Mallinckrodt files NDA for heart agent
Radiopharmaceutical supplierMallinckrodt Medical is taking the jump into technetium-basedcardiac scintigraphy. The St. Louis-based company said last weekthat it has filed a new drug application (NDA) with the Food andDrug Administration for TechneScan
Radiopharmaceutical supplierMallinckrodt Medical is taking the jump into technetium-basedcardiac scintigraphy. The St. Louis-based company said last weekthat it has filed a new drug application (NDA) with the Food andDrug Administration for TechneScan Q12, a technetium-99m agentfor myocardial perfusion imaging.
Mallinckrodt claims that TechneScan Q12 clears more rapidlyfrom the liver than other agents, reducing the level of hepaticuptake that can interfere with cardiac imaging. This may allownuclear medicine physicians to conduct cardiac imaging proceduresmore quickly by reducing the time between injection and imaging,according to the company.
Clinical studies with TechneScan Q12 also indicate that theagent is retained in the myocardium for extended periods of time,prolonging the availability of clear images.
Mallinckrodt's entry into the market for technetium-based cardiacradiopharmaceuticals will increase the number of competitors challengingDu Pont Merck, which has experienced strong market acceptancefor its Cardiolite agent since the product's introduction in 1991(SCAN 1/16/91). Another company vying for Cardiolite's marketshare is Amersham/Medi-Physics, which is waiting for FDA clearancefor Myoview, also a technetium-based agent.
Could a Deep Learning Model for Mammography Improve Prediction of DCIS and Invasive Breast Cancer?
April 15th 2024Artificial intelligence (AI) assessment of mammography images may significantly enhance the prediction of invasive breast cancer and ductal carcinoma in situ (DCIS) in women with breast cancer, according to new research presented at the Society for Breast Imaging (SBI) conference.
MRI-Based AI Model Shows Promise in Predicting Lymph Node Metastasis with Breast Cancer
April 15th 2024For the prediction of axillary lymph node metastasis in patients with breast cancer, an MRI-based, 4D convolutional neural network model demonstrated an AUC of 87 percent and sensitivity of 89 percent, according to new research.
