Feature | Orthopedic Imaging | December 01, 2015

MRI Reveals Weight Loss Protects Knees

Patients who lost more than 10 percent of their body weight had slower degeneration of their knee cartilage

RSNA 2015, MRI study, weight loss, knee cartilage degeneration

Figure 1. Cartilage T2 maps indicating worsening cartilage quality (red) after 48 months in an obese patient without weight loss (top row) compared to a patient with >10 percent weight loss (bottom row) in which only little cartilage degeneration is found.

RSNA 2015, MRI study, weight loss, knee cartilage degeneration, knee joint

Figure 2. Knee joint of patient without weight loss (A) showing severe cartilage defects after 48 months, whereas in the knee joint of a patient with a substantial amount of weight loss (B), cartilage remains intact.

November 30, 2015 — Obese people who lose a substantial amount of weight can significantly slow knee cartilage degeneration, according to a new magnetic resonance imaging (MRI) study presented today at the annual meeting of the Radiological Society of North America (RSNA).

Obesity is a major risk factor for osteoarthritis, a degenerative joint disease that affects more than a third of adults over the age of 60, according to the Centers for Disease Control and Prevention. The knee joint is a common site of osteoarthritis, and in many people the condition progresses until total knee replacement becomes necessary. Aging baby boomers and a rise in obesity have contributed to an increased prevalence of knee osteoarthritis.

"Degenerative joint disease is a major cause of pain and disability in our population, and obesity is a significant risk factor," said the study's lead author, Alexandra Gersing, M.D., from the Department of Radiology and Biomedical Imaging at the University of California, San Francisco. "Once cartilage is lost in osteoarthritis, the disease cannot be reversed."

Gersing and colleagues recently investigated the association between different degrees of weight loss and the progression of knee cartilage degeneration in 506 overweight and obese patients from the Osteoarthritis Initiative, a nationwide research study focused on the prevention and treatment of knee osteoarthritis. The patients either had mild to moderate osteoarthritis or risk factors for the disease. They were divided into three groups: a control group who did not lose weight, a second group who lost a little weight, and a third group who lost more than 10 percent of their body weight. The researchers then used MRI to quantify knee osteoarthritis.

"Through T2 relaxation time measurements from MRI, we can see changes in cartilage quality at a very early stage, even before it breaks down," Gersing said.

When the researchers analyzed differences in the quality of cartilage among the three groups over a four-year time span, they found evidence that weight loss has a protective effect against cartilage degeneration and that a larger amount of weight loss is more beneficial.

"Cartilage degenerated a lot slower in the group that lost more than 10 percent of their body weight, especially in the weight-bearing regions of the knee," Gersing said. "However, those with 5 to 10 percent weight loss had almost no difference in cartilage degeneration compared to those who didn't lose weight."

Substantial weight loss not only slows knee joint degeneration—it also reduces the risk of developing osteoarthritis, Gersing said. Along with moderate exercise, weight loss is one of the primary interventions against the disease.

"It's most helpful if these lifestyle interventions take place as early as possible," Gersing said.

In the future, the researchers are planning to study the role of diabetes, which is closely linked with obesity, in cartilage degeneration. They also plan to do an eight-year follow-up with the patient group and look at what effects weight gain may have on the knee joint.

Co-authors on the study are Martin Solka; Gabby B. Joseph, Ph.D.; Benedikt J. Schwaiger, M.D.; Ursula R. Heilmeier, M.D.; Georg Feuerriegel; John Mbapte Wamba, M.D.; Charles E. McCulloch, Ph.D.; Michael C. Nevitt, Ph.D.; and Thomas M. Link, M.D., Ph.D.

For more information: www.radiologyinfo.org

Related Content

An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal.

An example of Philips’ TrueVue technology, which offers photo-realistic rendering and the ability to change the location of the lighting source on 3-D ultrasound images. In this example of two Amplazer transcatheter septal occluder devices in the heart, the operator demonstrating the product was able to push the lighting source behind the devices into the other chamber of the heart. This illuminated a hole that was still present that the occluders did not seal. Photo by Dave Fornell

Feature | Radiology Imaging | April 02, 2020 | By Katie Caron
A new year — and decade — offers the opportunity to reflect on the advancements and challenges of years gone by and p
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 New studies use SIRD model to forecast COVID-19 spread; examine patient CT scans to correlate clinical features with mortality

Fig 1. A sample scoring on CT images of a 63-year-old woman from mortality group demonstrated a total score of 63. It was calculated as: for upper zone (A), 3 (consolidation) × 3 (50–75% distribution) × 2 (both right and left lungs) + 2 (ground glass opacity) ×1 (< 25% distribution) × 2 (both right and left lungs); for middle zone (B), 3 (consolidation) × 2 (25–50% distribution) × 2 (both right and left lungs) + 2 (ground glass opacity) × 2 (25–50% distribution) × 2 (both right and left lungs); for lower zone (C), 3 (consolidation) × (2 (25–50% distribution of the right lung) + 3 (50–75% distribution of the left lung)) + 2 (ground glass opacity) × (2 (25–50% distribution of the right lung) + 1 (< 25% distribution of the left lung)) Yuan et al, 2020 (CC BY 4.0)

News | Coronavirus (COVID-19) | April 01, 2020
April 1, 2020 — A new study, ...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2 A brief article from Henry Ford Health System in Detroit, published today in Radiology, reports on the first presumptive case of COVID-19–associated acute necrotizing hemorrhagic encephalopathy.

A, Image from noncontrast head CT demonstrates symmetric hypoattenuation within the bilateral medial thalami (arrows). B, Axial CT venogram demonstrates patency of the cerebral venous vasculature, including the internal cerebral veins (arrows). C, Coronal reformat of aCT angiogram demonstrates normal appearance of the basilar artery and proximal posterior cerebral arteries. Image courtesy of the Radiological Society of North America (RSNA)

News | Coronavirus (COVID-19) | March 31, 2020
March 31, 2020 — A brief article fr
RSNA's open data repository will compile images and correlative data to create a comprehensive source for COVID-19 research and education efforts #COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2
News | Coronavirus (COVID-19) | March 30, 2020
March 30, 2020 — The medical imaging community around the world is uniting to help address the...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Typical CT imaging features for COVID-19. Unenhanced, thin-section axial images of the lungs in a 52-year-old man with a positive RT-PCR (A-D) show bilateral, multifocal rounded (asterisks) and peripheral GGO (arrows) with superimposed interlobular septal thickening and visible intralobular lines (“crazy-paving”). Routine screening CT for diagnosis or exclusion of COVID-19 is currently not recommended by most professional organizations or the US Centers for Disease Control and Prevention. Image courtesy of RSNA

News | Coronavirus (COVID-19) | March 26, 2020
March 26, 2020 — The Radiological Society of North America (RSNA
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Representative examples of the attention heatmaps generated using Grad-CAM method for (a) COVID-19, (b) CAP, and (c) Non-Pneumonia. The heatmaps are standard Jet colormap and overlapped on the original image, the red color highlights the activation region associated with the predicted class. COVID-19 = coronavirus disease 2019, CAP = community acquired pneumonia. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — An arti...
#COVID19 #Coronavirus #2019nCoV #Wuhanvirus #SARScov2

Series CT scans in 35-year-old woman with COVID-19 pneumonia. (a) Scan obtained on illness days 1 showed multiple pure ground-glass opacity (GGO) mainly in right lower lobe. (b) Scan obtained on illness days 5 showed increased extent of GGO and early consolidation. (c) Scan obtained on illness days 11 showed multiple consolidation with almost the same extent. (d) Scan obtained on illness days 15 showed a mixed pattern with a slightly smaller extent, and the perilobular consolidation might suggest the presence of organizing pneumonia. The patient was discharged on illness days 17. Image courtesy of the journal Radiology

News | Coronavirus (COVID-19) | March 20, 2020
March 20, 2020 — In a new study pub