's Weekly Scan is your chance to catch up on the latest radiology content, from new research and device news to the latest case quizzes and conference reports. Review the slideshow below to see this week's top content:

Diagnostic Imaging's Weekly Scan: March 5-March 11

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Catch up on the top radiology content of the past week.

The days of inconsistent breast density notification for mammography reporting are coming to an end.

newly issued final rule updates to the Mammography Quality Standards Act (MQSA)

, the Food and Drug Administration (FDA) will require standard breast density notification in mammography reports, beginning on September 10, 2024, for all women in the United States.

In addition to requiring notification in the patient summary of mammography reports as to whether a patient has dense or not dense breasts, the FDA rule requires standard language that will note the limitations of mammography for women with dense breasts and encourage supplemental screening.

For women with dense breasts, the FDA said the standard breast density notification language will be as follows: “Breast tissue can be either dense or not dense. Dense tissue makes it harder to find breast cancer on a mammogram and also raises the risk of developing breast cancer. Your breast tissue is dense. In some people with dense tissue, other imaging tests in addition to a mammogram may help find cancers. Talk to your healthcare provider about breast density, risks for breast cancer, and your individual situation.”

JoAnn Pushkin, the executive director for DenseBreast-info.org, said the national standard for breast density notification is essential. While 38 states and the District of Columbia currently have breast density information laws, Pushkin said the state laws vary considerably and some don’t require specific notification to women that they have dense breasts. Pushkin maintained that the inconsistency of “state-by-state geography-dependent notification has created an inequity of actionable information for women.”

“All U.S. women should receive clear, unambiguous notification if their breasts are dense — and that having dense breasts increases both (their) risk of developing breast cancer and of having that cancer missed on (their) mammogram, and that (they) should talk to (their) health provider about supplemental screening,” emphasized Pushkin.

Mammography News: FDA Says National Breast Density Notification Rule May be Published in Late 2022 or Early 2023

Can AI Improve the Consistency of Breast Density Assessment by Radiologists?

What a New Study Reveals About Breast Density Awareness

In a recent interview (see video clip below), Wendie Berg, M.D., Ph.D., said “it has been a long time coming” for a national standard for breast density notification to help address a common problem and a well-known limitation of mammography. Approximately 40 percent of women have dense breasts and nearly 40 percent of breast cancer is hidden in dense breast tissue, emphasized Dr. Berg, a professor of radiology at the University of Pittsburgh School of Medicine.

Dr. Berg noted magnetic resonance imaging is the best supplemental imaging “by far” and noted that abbreviated MRI is becoming more available and less expensive. She noted there are now over 100 facilities in the U.S. that offer abbreviated MRI.

In addition to changes in the patient summary of mammography reports, Dr. Berg said the new FDA rule will require radiologists to note one of the four breast density categories in the American College of Radiology’s Breast Imaging Reporting and Data System (BI-RADS) when detailing breast density assessments to referring providers. While she noted that many facilities are already doing this, Dr. Berg said it is only a strong recommendation to include this categorization in mammography reports at the present time.

Calling the FDA final rule on breast density notification a reasonable step forward, Dr. Berg also emphasized that more education and awareness of breast density is needed for referring providers in terms of understanding the limitations of mammography in this patient population, supplemental screening options and where breast density fits in with other risk factors for breast cancer.

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As part of updates to the Mammography Quality Standards Act (MQSA) of 1992, the Food and Drug Administration (FDA) has issued a final rule that requires the inclusion of breast density assessment in mammography reports starting on September 10, 2024.

FDA Issues Final Rule on National Breast Density Notification for Mammography Reports

Typical computed tomography (CT) findings for COVID-19 are reportedly less likely for people with the omicron variant of the disease in comparison to those with the delta variant, and multiple vaccination dosing reduces the odds of typical CT findings and high CT severity scores in people with COVID-19, according to a newly published multicenter study.

For the retrospective study, recently published in 

 researchers in France reviewed CT exams for 3,876 patients (median age of 68) who presented to 93 emergency departments in with COVID-19 between July 2021 and March 2022.

In order to gauge the impact and reflect the peak periods of the omicron and delta variants of COVID-19, the study authors labeled CT exams performed prior to November 15, 2021 as “delta-predominant” (1,080 patients, 28 percent); CT exams performed between November 15 and December 31, 2021 as “transition” (790 patients, 20 percent); and CT exams performed after January 1, 2022 as “omicron-predominant” (1,629 patients, 42 percent).

The study authors found the proportion of typical chest CT findings for COVID-19, ranging from ground glass opacities and consolidations to fibrotic bands and reticulations, was 32 percent higher in non-vaccinated patients (76 percent) in comparison to patients who had at least one vaccination dose (44 percent). Forty-three percent of non-vaccinated patients had a high CT severity score in comparison to 25 percent of vaccinated patients, according to the study.

“Regardless of the period, vaccination was associated with diagnostic and severity scores … with lesser extent of disease and lower frequency of typical patterns in vaccinated patients,” wrote study co-author Guillaume Gorincour, MD, who is affiliated with Imadis Teleradiology in Lyon, France, and colleagues.

(Editor’s note: For related content, see “

How Accurate is the CT Severity Score for Predicting COVID-19 Severity?

CT Study Reveals Persistent Lung Abnormalities Two Years After COVID-19

Study Shows Merits of Photon-Counting CT in Detecting Subtle Post-COVID Lung Abnormalities

The researchers found the proportion of the aforementioned typical chest CT findings for COVID-19, during the omicron-predominant period was 25 percent lower (49 percent) in comparison to the delta-predominant period (74 percent). The proportion of high CT severity scores was 10 percent lower (29 percent) in the omicron-predominant period in comparison to the delta-predominant period (39 percent).

“Radiologists should be aware of the influence of vaccination and novel variants on CT findings and adapt their interpretations and conclusions accordingly, especially since full vaccination coverage is increasing and new omicron subvariants can reinfect previously immunized individuals,” maintained Gorincour and colleagues.

A multivariable analysis found that one vaccine dose was not significantly associated with reduced likelihood of typical chest CT patterns and severity scores in comparison to unvaccinated patients, according to the study. However, Gorincour and colleagues noted that patients with two vaccination doses and three vaccination doses had lower odds ratios (ORs) for typical COVID-19 chest CT findings (32 percent and 20 percent respectively) and high CT severity scores (47 percent and 33 percent respectively) in comparison to unvaccinated patients.

In regard to study limitations, the authors acknowledged possible bias due to subjective assessment of CT severity scores during on-call duty in emergency departments, and knowledge of patient RT-PCR and COVID-19 vaccination status prior to radiologist assessment of chest CTs. Gorincour and colleagues also noted that bronchial wall thickening and peribronchovascular predilection, more commonly reported with the omicron variant, were not assessed in this study.

Emerging research from a multicenter study found that COVID-19 vaccination was affiliated with a lower likelihood of high computed tomography (CT) severity scores and typical CT findings for COVID-19 in comparison to unvaccinated patients.

New Chest CT Study Assesses Impact of COVID-19 Variants and Vaccination Status

Could autonomous artificial intelligence (AI) have an emerging role in assessing chest X-rays?

In a new multicenter retrospective study involving a total of 1,529 patients (mean age of 69), researchers compared autonomous AI (ChestLink version 2.6, Oxipit) versus radiologist reporting on 1,100 abnormal posteroanterior chest radiographs, 617 critical abnormal radiographs and 429 normal radiographs.

The study authors reported a 99.1 sensitivity rate for AI on abnormal radiographs in comparison to a 72.3 percent sensitivity for radiologist reports. Autonomous AI also yielded a 6.3 percent higher sensitivity than reporting radiologists for critical abnormal X-rays (99.8 percent vs. 93.5 percent), according to the recently published study in 

“In this consecutive multicenter study, a commercial AI tool intended for autonomous reporting of normal chest radiographs demonstrated a sensitivity of 99.1 percent (1090 of 1100) for abnormal findings, which was significantly higher than that with the clinical radiologic reports, and with only one false-negative “critical” chest radiograph – a subtle pneumonic opacity,” wrote study co-author Michael B. Andersen, M.D., Ph.D., who is affiliated with the Department of Radiology at the Herlev and Gentofte Hospital in Copenhagen, Denmark, and colleagues.

The researchers noted the potential of the AI modality to help alleviate radiologist workload. Andersen and colleagues found that 120 of the 1,529 posteroanterior chest X-rays could have been correctly identified as normal with autonomous AI, accounting for 7.8 percent of the reviewed radiographs. They pointed to an even higher percentage of normal autonomous AI findings in the outpatient group (11.6 percent) in comparison to outpatients and those who had X-rays in the emergency department (6.2 percent).

“These results suggest that an outpatient setting with a high prevalence of normal chest radiographs is a particularly good setting for these AI models,” posited Andersen and colleagues. “Our results showed that there was no statistically significant difference in the automation rate of normal posteroanterior chest radiographs across the four hospitals even though the percentages of outpatients were different.”

Can Deep Learning Assessment of X-Rays Improve Triage of Patients with Acute Chest Pain?

Deep Learning Model Predicts 10-Year Cardiovascular Disease Risk from Chest X-Rays

The study authors noted overall sensitivity rates for autonomous AI at the four hospitals included in the study were above 96 percent and added that the AI tool had 100 percent sensitivity for critical and other remarkable findings among outpatients.

However, Andersen and colleagues also pointed out that radiology reporting had a significantly higher specificity rate for abnormal X-rays (91.8 percent) in comparison to the AL tool (28 percent). Additionally, 190 of the 299 false-negative findings (64 percent) in the radiology reports were noted as “abnormal, unremarkable” findings, according to the study.

“ … It is not meaningful to compare diagnostic accuracy of the AL tool with that of radiologists as radiologists must balance sensitivity and specificity and the deployed AI tool is optimized solely to minimize false-negative findings. Hence, the AI tool and the radiologists are working at entirely different operating points. A radiologist could likely achieve a performance similar to that of the AI tool, but that would not be meaningful in clinical practice,” maintained Andersen and colleagues.

In regard to study limitations, the authors acknowledged the retrospective nature of the study and the lack of actual implementation of the AI modality. Pointing out that unremarkable findings are not routinely reported at the facilities where the study was conducted, the researchers said the sensitivity noted with radiology reports was “probably underestimated.”

In a study of over 1,500 patients, researchers found that an emerging artificial intelligence (AI) modality had significantly higher sensitivity rates for abnormal posteroanterior chest radiographs and critical finding radiographs than radiology reports.

Autonomous AI Shows Nearly 27 Percent Higher Sensitivity than Radiology Reports for Abnormal Chest X-Rays

Figures 1-3

D) Atrial septal defect with paradoxical embolism

Review the case study and test your knowledge to make the correct diagnosis.

Image IQ Quiz: Middle-Aged Male with Chest Pain and Shortness of Breath

The use of adjunctive artificial intelligence (AI) doubled the positive predictive value (PPV) of digital mammography (DM) exams overall and led to greater than 90 percent accuracy for DM and digital breast tomosynthesis (DBT) in detecting breast cancer in women with elevated risk, according to research findings presented recently at the European Congress of Radiology (ECR) conference in Vienna, Austria.

, researchers compared the use of adjunctive AI (Transpara® version 1.7.0, ScreenPoint Medical) in 11,988 women (between the ages of 50 and 74) who had DM or DBT screening exams versus 16,555 women screened with DM or DBT the year before without AI support. In the AI group, 5,049 women had DM screening with the Hologic Selenia device and 6,949 women had DBT screening with the Hologic Selenia Dimensions device, according to the study. For the non-AI cohort, 7,229 women had DM screening and 9,326 women had DBT.

The researchers found the combination of AI and DM had an overall cancer detection rate of 8.1/1000 in comparison to 5.1/1000 for DM alone and had an accuracy rate of 95.1 percent for detecting malignancy in patients with an elevated risk for breast cancer. Adjunctive AI also doubled the overall positive predictive value (PPV) for DM (12.2 percent) in comparison to DM alone (6.1 percent), according to the study authors.

For patients with DBT and AI, the researchers reported a cancer detection rate of 9.6/1000 and a PPV of 16.5 percent in comparison to 5.8/1000 and 13.1 percent, respectively, for DBT alone. For the elevated risk group, the study authors said the combination of DBT and AI correctly diagnosed 92.5 percent of breast cancer.

“Artificial intelligence as support for readings in breast cancer screening practice increases cancer detection rate and positive predictive value for both DM and DBT,” noted Esperanza Elias Cabot, MD, who is affiliated with the Breast Cancer Unit in the Department of Radiology at the Hospital Universitario Reina Sofia in Cordoba, Spain.

Digital Breast Tomosynthesis and Breast Density: What a New Study Reveals

Medicare Mammography Study Shows Black Women Had Less Initial Access to Imaging Advances than White Women

Dr. Cabot also noted a 1.7 percent decrease in the recall rate with adjunctive AI and DM (6.6 percent) in comparison to DM only 8.3 percent). She also pointed out 1.4 percent increase in the recall rate for DBT and AI (5.8 percent) in comparison to DBT alone (4.4 percent).

Of the four lesions missed by AI/DBT but detected by radiologists in the high-risk group, Dr. Cabot said two were invasive carcinomas with architectural distortion and the other two were invasive ductal carcinoma masses. Two lesions missed by AI/DM in the high-risk group included an invasive ductal carcinoma mass and a ductal carcinoma in situ with architectural distortion, according to the study.

1. Cabot EE. Artificial intelligence (AI) improves breast cancer screening performance for both digital mammography and digital breast tomosynthesis. Presented at the European Congress of Radiology, March 1-5, Vienna, Spain. Available at: 

https://connect.myesr.org/course/ai-in-breast-imaging-2/#1

Comparing year-long findings with and without adjunctive artificial intelligence (AI) at a breast cancer screening program in Spain, researchers found the combination of digital breast tomosynthesis and AI had a 92.5 percent accuracy for diagnosing cancer in patients with elevated risk.

Study: AI Improves Cancer Detection Rate for Digital Mammography and Digital Breast Tomosynthesis

Eric Postal, MD, is a diagnostic radiologist with the University of Pittsburgh Medical Center. 

Teleradiology is a polarizing issue for a lot of folks in our field. Mention it to the wrong person and you are liable to get an earful of bellyaching, if not a lecture on the subject.

It doesn't need saying for anybody who has read more than a couple of my blogs, but I am firmly in the pro-telerad camp and have been, even prior to most people hearing of the concept. (However, I did stumble across a historical writeup which identified the first transmission of rad images over phone lines back in 1947, if you can believe that.)

, I mentioned that when I was in med school and thinking about specialties for myself, society was just getting familiar with the Internet. The Web was relatively new, and most connections were dial-up. Compared to what we take for granted today, data moved at a snail's pace, which was way insufficient for modern telerad purposes.

Still, I knew how things progressed and it seemed to me that diagnostic radiology might soon be practiced 

anywhere with a little more technological oomph. I liked the idea of being able to tap into remote job markets without relocation should I happen to be living somewhere with less opportunity. It was one of the reasons I ultimately went for a rad residency.

That benefit of telerad is a two-way street. Rad groups situated in less geographically desirable locations have been able to meet their staffing needs without enticing new recruits to relocate. Even rad groups in densely populated places have turned to telerad to fill skill set gaps. I recall hearing about a hospital in Boston that was having trouble hiring pediatric radiologists. A big-name telerad company obliged by moving one of its peds people to daytime shifts.

Teleradiologist Overcalls and Hedging: We Are What You Make Us

Issues and Answers with Outsourced Teleradiology Night Coverage

During a recent conversation about the pros and cons of telerad, I found myself pointing out another telerad gain which I have always had in mind but never put into words before. Telerad increases competition by putting a lot more rads – and their groups – into play with one another.

I don't just mean competition in terms of dollars and cents, or other movable levers typically found in contracts. That part is obvious or at least it was to me during the first half of med school. I am also talking about competition of ideas and methods, or “best practices," to borrow a phrase.

Wind back the clock a couple of decades and you return to an era when most rads didn't interact much with peers outside of their own group. Maybe there was another rad group or two in the area, but that was usually it. They wouldn't see anybody outside of their little world unless they went to a conference or the like. It was the same deal with local referrers and hospitals. Their view of radiology was the local pool of talent, and maybe an occasional interviewee who considered moving there.

As the rads competed against each other (and other local cogs of the health-care machine competed for their service), there was a microcosm of evolution. Better ideas and methods would gradually replace inferior ones. The area was akin to a petri dish, in which stronger and/or more adaptable elements generally succeeded in the long term.

Fast forward to the current day. Telerad effectively puts all of those previously isolated petri dishes into contact with one another. A good idea that results in increased productivity, efficiency, or diagnostic accuracy can spread across the country (or the world) practically in the blink of an eye, whereas it might otherwise have stayed isolated or been forgotten in some remote locale. Even an idea that is maladaptive in one situation might be recognized by others as perfect for where they are.

Increasingly rapid and widespread dissemination of info is, of course, not exclusive to our field. The news (and tabloid) industry has been even more fundamentally transformed. It used to be that today's events were something you would read about tomorrow if you had a newspaper that was on top of things, or maybe hear about today if the 6 p.m. television broadcast happened to mention it. Now, not only do all serious news outlets have a constantly updated online presence, they are regularly scooped by folks posting on social media, whether or not such postings ultimately pan out to be accurate.

For my pre-telerad jobs, there were a couple of local outpatient imaging centers where I had maybe half a dozen other rads on my team at a time, and perhaps a few referring physicians with a pool of patients numbering at most in the thousands. Contrast those gigs against my first telerad job, where I had hundreds of other rads on my team alone, plus all the onsite rads working in the hundreds of hospitals we covered.

That is a lot more of a talent pool to learn about different ways of doing things both as role models and as cautionary tales. Add to that the even more vastly increased pool of referring clinicians and the exponentially larger patient population, and I would have a hard time not growing as a professional.

It gets even better when you consider that I am far from the only one who is adapting and growing in the mega-petri dish. Put two telerads together, let alone a whole team of them, and you are dealing with a synergistic effect as each of them brings his or her own set of multipliers to the table.

In addition to the advantages of working remotely, this author says teleradiology increases competition, collaboration and growth for radiologists and rad groups alike.

The Adaptive Value of Teleradiology: Enlarging the Petri Dish

Diagnostic Imaging's Weekly Scan: February 27-March 4

Recently published statistics from the American Cancer Society (ACS) reveal concerning trends for colorectal cancer with the prevalence of advanced stage disease increasing to 60 percent in 2019.

 For people under the age of 55, the diagnosis of colorectal cancer has nearly doubled from an 11 percent prevalence in 1995 to 20 percent in 2019, according to the ACS.

Given the importance of timely diagnosis and appropriate staging, researchers recently reviewed pertinent principles in magnetic resonance imaging (MRI) assessment of patients with rectal cancer in a cum laude awarded 

poster presentation at the European Congress of Radiology (ECR)

1. Emphasizing that mesorectal fascia status is a key risk factor for recurrence of rectal cancer, the poster authors said a positive MRI finding would reveal a tumor lying within 1 mm of the mesorectal fascia. They called the circumferential resection margin for total mesorectum excision (TME) or transanal TME a “holy plane,” defined by the virtual space between the parietal fascia and the mesorectal fascia.

2. Tumor location below the peritoneal reflection increases risks for peritoneal dissemination and lateral pelvic node involvement, wrote Roberto Garcia-Figueiras, M.D., who is affiliated with the Department of Radiology at the Complejo Hospitalario de Santiago de Compostela in Spain, and colleagues.

3. For recognition and staging of early tumors, the poster authors suggested assessing the submucosal layer between the tumor and the muscularis propria. When using contrast-enhanced MRI, a submucosal enhancing stripe status can help differentiate between stage T2 tumors and stage T1 or lower rectal tumors, according to the study authors.

4. Pointing out a diverse range of prognosis for stage T3 tumors, Garcia-Figueiras and colleagues recommended careful assessment of tumor characteristics and other prognostic factors, but also maintained that tumor spread depth on MRI provides the most reliable prognostic information.

5. Acknowledging the difficulty of differentiating between early stage T3 tumors and stage T2 tumors, the poster authors caution that spiculated desmoplastic reaction in peritumoral inflammation or perirectal fat can mimic tumor involvement.

6. Garcia-Figueiras and colleagues noted that T2-weighted MRI sequences with fat suppression and dynamic contrast-enhanced MRI can be beneficial in diagnosing mucinous tumors, which are associated with advanced tumor presentation, multiple metastatic sites, and young age. On T2-weighted MRI, the presence of mucin pools can lead to high signal intensity similar to or brighter than mesorectal fat.

7. Staging of T4b tumors include tumors that invade or are adherent to bones, muscles, nerves, blood vessels and ureters. This staging does not apply to tumors that invade or are adjacent to the internal anal sphincter, the anterior peritoneal reflection or the intersphincteric space, according to Garcia-Figueiras and colleagues.

1. American Cancer Society. American Cancer Society releases new colorectal cancer statistics; rapid shifts to more advanced disease and younger people. Cision PR Newswire. Available at: 

https://www.prnewswire.com/news-releases/american-cancer-society-releases-new-colorectal-cancer-statistics-rapid-shifts-to-more-advanced-disease-and-younger-people-301759641.html

 . Published March 1, 2023. Accessed March 3, 2023.

Antelo MC, Calvo AN, Gonzalez MB, Gonzalez SB, Garcia-Figueiras R. Common misconceptions about rectal cancer MRI. Poster presented at the European Congress of Radiology, March 1-5, 2023, Vienna, Austria. Available at 

https://portal.myesr.org/esr/membership/poster/f923bc62-2b51-4de4-876d-7ef029e40baa/show/results#content

In a cum laude awarded presentation at the European Congress of Radiology (ECR), researchers discussed misconceptions and pertinent principles for magnetic resonance imaging (MRI) of patients with rectal cancer, ranging from the diagnosis of mucinous tumors to the impact of mesorectal fascia status for rectal cancer recurrence.

Seven Key Considerations with Rectal Cancer MRI

Is beta blocker administration necessary to ensure heart rate control during coronary computed tomography angiography (CCTA) exams in the emergency department (ED) for patients with acute chest pain?

In a new retrospective study involving 509 patients (mean age of 52.1) who underwent CCTA exams for acute chest pain, researchers compared the use of a 64-detector single-source CT (SSCT) device with heart rate control in 205 patients versus dual-source CT (DSCT) without heart rate control in 304 patients. Oral beta blockers were administered in the SSCT group for patients with a heart rate above 65 beats per minute, according to the study, recently published in the 

The researchers found no significant differences in median emergency department (ED) length of stay between DSCT (505 minutes) and SSCT (457 minutes). They also noted no significant differences in the frequency of emergent cardiology consults, invasive angiography, and coronary revascularization procedures.

However, the use of DSCT did result in a 27.8 percent higher frequency of good or excellent image quality (87.8 percent) in comparison to SSCT (60 percent) and a 4.7 percent lower frequency of non-diagnostic exams (1.6 percent versus 6.3 percent), according to the study. The researchers also found that CCTA exams performed with DSCT were completed in a median time of 95 minutes in comparison to 117 minutes for SSCT.

“Patients undergo coronary CTA in the ED because of their risk for acute coronary syndrome (ACS); thus, these patients are considered to require urgent care and receive priority access to resources in the ED such as beds, monitors, and medical personnel. If ACS can be quickly excluded or diagnosed by shortening the CT completion time, then downstream management processes can likewise be accelerated. Subsequently, resources may be efficiently redistributed among patients, improving overall ED process management,” wrote study co-author Young Joo Suh, M.D., Ph.D., who is affiliated with the Department of Radiology at Severance Hospital and the Center for Clinical Imaging Data Science at Yonsei University College of Medicine in Seoul, Korea, and colleagues.

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Deep Learning Improves CT Guidance for Revascularization of Coronary Total Occlusions

Could an Emerging Deep Learning Modality Enhance CCTA Assessment of Coronary Artery Disease?

The study authors attributed 80 percent of the reduction in CCTA examination time with DSCT to the lack of heart rate control. Suh and colleagues said the use of two X-ray tubes and corresponding detector arrays give DSCT a significant advantage over SSCT in terms of faster temporal resolution and prevention of motion artifact degradation of coronary artery imaging that can occur in patients with high heart rates.

“The present analysis builds upon prior work indicating that the use of a DSCT system has the potential to avoid need for strict (heart rate) control for coronary CTA examinations,” maintained Suh and colleagues.

In regard to study limitations, the authors cautioned about general extrapolation of the study findings as they were drawn from research conducted at a single tertiary facility during the COVID-19 pandemic. The study cohort included patients with low to intermediate risk for acute coronary syndrome (ACS) but the researchers acknowledged that guidelines for the assessment of chest pain that were published during the study noted that routine testing for ACS is not necessary for low-risk patients with chest pain presenting to emergency departments. Other than temporal resolution, the study authors noted they did not evaluate technical parameter differences between DSCT and SSCT.

Recently published research revealed that coronary computed tomography angiography (CCTA) exams performed with dual-source CT were completed 22 minutes faster and had a nearly 28 percent higher frequency of good or excellent image quality in comparison to CCTA exams performed with single-source CT devices.