Technology | July 08, 2009

Hologic Get PMA for Minimally-Invasive Permanent Contraception

July 7, 2009 - The U.S. Food and Drug Administration (FDA) has approved Hologic Inc.'s premarket approval (PMA) application for the Adiana permanent contraception system.

The Adiana system is designed to provide women a minimally-invasive, non-incision alternative to traditional, surgical means of permanent contraception. In January 2009, Hologic received CE marking approval for the Adiana system and commenced marketing and sales of this product in certain European countries.

During the Adiana procedure, a slender, flexible instrument is passed through the body’s natural openings to deliver a low level of radiofrequency (RF) energy to a small section of each fallopian tube. A tiny, soft insert, about the size of a grain of rice, is then placed in each fallopian tube in the location where the energy was applied. During the three months following the procedure, the patient continues to use
temporary birth control while new tissue grows in and around the Adiana inserts, eventually blocking the fallopian tubes. At three months, a special X-ray test (called a hysterosalpingogram or HSG) is performed
to confirm the fallopian tubes are completely blocked and the patient may begin relying on Adiana for permanent contraception.

The Adiana permanent contraception procedure is minimally invasive, requires no incisions and can be performed in the comfort of the doctor’s office using local anesthesia. Patients are normally able to return to work or resume their daily activities within one day. In contrast, traditional methods of permanent contraception, such as tubal ligation, require more invasive surgical procedures, usually are conducted in a hospital under general anesthesia and typically require four to five days of recovery. As a result, these more invasive surgical procedures can pose serious risk of complications, including anesthesia-related problems and damage to organs or blood vessels. There were approximately 70,000 female transcervical contraception procedures performed in the U.S. last year.1

For more information: www.hologic.com

Related Content

In a demonstration on the exhibit floor of the SBI symposium, Koios software identified suspicious lesions in ultrasound images

In a demonstration on the exhibit floor of the SBI symposium, Koios software identified suspicious lesions in ultrasound images. Photo by Greg Freiherr

Feature | Artificial Intelligence | April 19, 2019 | By Greg Freiherr
Commercial efforts to develop...
Videos | Breast Imaging | April 18, 2019
In a keynote lecture at the Society of Breast Imaging (SBI)/American College of Radiology (ACR) 2019 Symposium, ...
Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer

Fatty tissue and breast density may be considered in the context of many factors that affect the occurrence and detection of breast cancer. Permission to publish provided by DenseBreast-info.org

Feature | Breast Imaging | April 18, 2019 | By Greg Freiherr
When planning a screening program to detect the early signs of breast cancer, age is a major consideration.
Oxipit Introduces Multilingual Support for ChestEye AI Imaging Suite
News | Artificial Intelligence | April 16, 2019
The CE-certified ChestEye artificial intelligence (AI) imaging suite by Oxipit is now available in seven European...
iCAD Appoints Stacey Stevens as President
News | Radiology Business | April 16, 2019
iCAD Inc. recently announced that Stacey Stevens has been named president. As president, Stevens will have expanded...
compressed breast during mammography.
360 Photos | 360 View Photos | April 16, 2019
A 360 view of a simulated breast compression for a...
Check-Cap Initiates U.S. Pilot Study of C-Scan for Colorectal Cancer Screening
News | Colonoscopy Systems | April 15, 2019
Check-Cap Ltd. has initiated its U.S. pilot study of the C-Scan system for prevention of colorectal cancer through...
A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images

A smart algorithm has been trained on a neural network to recognize the appearance of breast cancer in MR images. The algorithm, described at the SBI/ACR Breast Imaging Symposium, used “Deep Learning,“ a form of machine learning, which is a type of artificial intelligence. Graphic courtesy of Sarah Eskreis-Winkler, M.D.

Feature | Artificial Intelligence | April 12, 2019 | By Greg Freiherr
The use of smart algorithms has the potential to make healthcare more efficient.
This image depicts ABUS images with QVCAD results

This image depicts ABUS images with QVCAD results.

Feature | Breast Imaging | April 12, 2019
Imaging Technology News spoke with Bob Foley, vice president of sales and marketing of QView Medical, Inc.,