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While recently published research raised concerns about projections of future radiation-induced cancers from computed tomography (CT) scans, Joseph Cavallo, M.D., maintained in a new 

 that advances in technology may continue to facilitate lower radiation dosing with CT.

“Whether it's the photon-counting CT machines or AI post-processing algorithms, there are multiple avenues to lower dosing … It's not going to be a one size fits all, or a silver bullet. It's going to be a combination of different technologies on the machine side, on the software side, that help us continually make these examinations safer and improve the risk benefit profile moving forward,” noted Dr. Cavallo, an assistant professor of radiology and biomedical imaging at Yale School of Medicine in New Haven, Ct.

Highlighting significant reductions with cardiac CT radiation dosing in recent years, Mahadevappa Mahesh, MS, Ph.D., also challenged perceptions about overuse of CT scans in the emergency room setting.

“Generally, emergency room physicians get the bad rap (with the perception that) they're ordering too many studies. … If we look (at this) closely, emergency room physicians, radiology, everybody (is) working with such a time-compressed timeline, and they're trying to save the patient. … As a medical physicist, I am all for radiation dose reduction, but at the same time, I am also a proponent of never tying anybody's hand because of radiation, even in the cath lab. If you have to do the procedure, do it,” asserted Dr. Mahesh. the president of the American Association of Physicists in Medicine (AAPM), and a professor of radiology and radiological sciences at the Johns Hopkins School of Medicine.

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

The Reading Room Podcast: Current Insights on Recent Research About Radiation-Induced Cancers with CT Scans, Part 1

What New Research Reveals About Computed Tomography and Radiation-Induced Cancer Risk

Nine Takeaways from New Research on CT Scans and Radiation-Induced Cancers

For more insights from Dr. Cavallo and Dr. Mahesh, listen below or 

In a second part of a new podcast episode on recently published research on projected radiation-induced cancers from computed tomography (CT) scans, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., offer current perspectives on cardiac CT dosing, AI advances and the importance of teamwork in ensuring appropriate dosing for CT. 

The Reading Room Podcast: Current Insights on Recent Research About Radiation-Induced Cancers with CT Scans, Part 2

In a recently published study, researchers estimated that out of an estimated 93 million computed tomography (CT) exams performed in 2023, there may be 103,000 future cases of radiation-induced cancers. Based on current CT use and radiation dosing levels, the study authors suggested that radiation-induced cancers from CT exposure may account for 5 percent of all cancer cases.

, Joseph Cavallo, M.D., emphasized appropriate perspective with the aforementioned risk modeling study and taking all the risks into account to optimize patient care.

“I would have liked to see a little more discussion about underlying risk in general. They speak to the risk of CT, but we're really not comparing the risk of a CT versus the risk of doing nothing … Hopefully, in all the cases where we're doing CT or other radiation-based imaging, we should be comparing the risk of CT versus the risk of the underlying disease and the risk of complications from the underlying disease, and ultimately, the risk of missing the diagnosis of some of those diseases,” posited Dr. Cavallo, an assistant professor of radiology and biomedical imaging at Yale School of Medicine in New Haven, Ct.

 suggested that multiphase scanning, occurring in 28.5 percent of CT exams, is commonly overutilized, Mahadevappa Mahesh, MS, Ph.D., emphasized that patient history and disease presentation are key considerations.

“Which patients (had the multiphase scanning)? Was it necessary? Because it's very subjective to say overused. … Did any of them have cancer-related studies? Do they have other underlying diseases? (In these cases), you only (get) answers with a triphasic study. That's important to say. I'm not refuting the numbers, but the justification of these numbers is very important,” added Dr. Mahesh, the president of the American Association of Physicists in Medicine (AAPM), and a professor of radiology and radiological sciences at the Johns Hopkins School of Medicine.

AI Denoising Bolsters Ultra-Low-Dose CT Detection of Pneumonia Findings in Immunocompromised Adults

For more insights from Dr. Cavallo and Dr. Mahesh, listen below or 

In a new podcast, Mahadevappa Mahesh, MS, Ph.D., and Joseph Cavallo, M.D., share their perspectives on recently published research looking at projections for future radiation-induced cancers from computed tomography (CT) scans.

In a study involving over 500 patients, researchers noted that the CT-based AI software led to a 24 percent increase of evaluations for aortic abdominal aneurysms within six months of detection.

Study Suggests Benefits of CT-Based AI in Detecting and Managing Patients with Aortic Abdominal Aneurysm 

The AI-powered Bunkerhill MAC software reportedly facilitates chest CT detection and quantification of mitral annular calcification, which has been linked to higher cardiovascular risk and related mortality.

FDA Clears CT-Based AI For Detection of Mitral Annular Calcification

Based on survey findings and subsequent voting from radiologists at nine facilities, the Society of Abdominal Radiology has issued new consensus recommendations on the use of adult abdominal photon-counting CT.

Nine Takeaways from New Consensus on Abdominal Photon-Counting CT Protocols in Adults

Researchers found comparable 10-year overall survival rates for people who had computed tomography (CT) surveillance (94.7 percent) and those who had surgery for ground-glass nodules (97.6 percent), according to a new prospective study involving over 680 participants.

CT Study Shows No Significant Difference in Long-Term Outcomes Between Surveillance and Surgery for Ground-Glass Nodules

The Planmed XFI full-body weightbearing cone-beam CT scanner reportedly enables upright and supine patient positioning.

Versatile Full-Body Cone-Beam CT Scanner Gets FDA Clearance

’s Weekly Scan, which offers an opportunity to catch up on the most well-viewed radiology content of the past week.

In a new study, published earlier this week in the 

, researchers found that women, subspecialists and radiologists in non-academic settings had 

over a 25 percent higher attrition rate in radiology

 in comparison to men, general radiologists and academic radiologists over an eight-year period.

In a new study recently presented at the 41st Congress of the European Committee for Treatment and Research in Multiple Sclerosis (ECTRIMS), researchers found that for patients with relapsing multiple sclerosis, switching from oral therapies to subcutaneous monthly administration of the anti-CD20 monoclonal antibody ofatumumab led to over 

a 98 percent reduction of Gd+ T1 lesions on MRI at 96 weeks

In comparison to false positives with unassisted radiologist interpretations of DBT exams, 

AI-only false positive assessments were associated with a significantly higher total of false-positive findings

 as well as a 33 percent lower frequency of dense breasts, according to a new study of nearly 3,000 women who had screening DBT exams.

, researchers showed markedly higher sensitivity rates with the use of 

adjunctive AI for ischemic stroke detection on non-contrast CT exams

 but also noted a high degree of bias and lack of external validation in many of the studies.

, Partho Sengupta, M.D., and Davinder Ramsingh, Ph.D., discussed recent research demonstrating the capability of 

point-of-care ultrasound (POCUS) to facilitate reduced length of stay and significant cost savings

 in the management of patients with dyspnea.

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

Diagnostic Imaging’s Weekly Scan: September 28 — October 4

Diagnostic Imaging's Weekly Scan: September 28 — October 4

New research, published earlier this week in 

MRI-based pancreatic risk stratification model (M-PRiSM)

 offers enhanced prognostic insight into postoperative survival for patients being treated for pancreatic ductal adenocarcinoma (PDAC).

In a prospective study, recently published in the 

, researchers found that deep learning image reconstruction (DLIR) may facilitate up to a 

45 percent reduction in radiation dosing with dual-energy computed tomography (DECT)

Speaking of radiation dosing, in a recent interview with 

, Dr. Rebecca Smith-Bindman discussed a new study, published in the 

impact of cumulative radiation exposure from medical imaging upon hematologic cancer risk in children

In a new 67-study meta-analysis published in 

PSMA PET offered significantly higher accuracy in detecting biochemical recurrence (BCR), lymph node metastasis and bone metastasis

 in comparison to multiparametric MRI (mpMRI) and computed tomography (CT).

combination of digital breast tomosynthesis (DBT) and molecular breast imaging (MBI)

 offered more than double the detection of invasive breast cancer with DBT in the first year of screening, according to a prospective study of nearly 3,000 women with dense breasts.

Diagnostic Imaging's Weekly Scan is your chance to catch up on the latest radiology content, from new research and device news to the latest interviews and conference reports. 

Diagnostic Imaging's Weekly Scan: September 21 — September 27

It has been estimated that up to 50 percent of those who have acute dissection in the ascending aorta may die before they get to the hospital. However, for those who survive hospitalization for acute aortic dissection, Alan Braverman, M.D., noted that 90 percent are “alive and well” one year later.

, Dr. Braverman emphasized that the knowledge of common risk factors in concert with imaging findings may facilitate earlier diagnosis of aortic dissection.

In addition to a family history of aortic diseases and genetic conditions, such as Marfan syndrome and Loeys-Dietz syndrome, hypertension is another common risk factor for the development of aortic dissection, according to Dr. Braverman, the head of general cardiology with the John T. Milliken Department of Medicine at the University of Washington School of Medicine.

“About 75 percent of people with an aortic dissection have underlying hypertension and, importantly, they don't have to have severe, uncontrolled hypertension. Just the presence of hypertension, even when controlled, can be a risk factor because it can affect the architecture of the aorta,” pointed out Dr. Braverman.

While noting the limitations of point-of-care ultrasound (POCUS) and chest X-ray, Dr. Braverman said they can serve as useful screening tools for triggering subsequent imaging.

“Sometimes the shadow of the aorta in the mediastinum around the heart will be enlarged because the aorta has stretched because of the dissection, or there'll be other evidence on a chest X-ray that heighten your suspicion,” noted Dr. Braverman.

However, Dr. Braverman said computed tomography (CT) provides a highly sensitive gold standard.

“A contrast CT scan, especially when it's gated so it doesn't have a lot of motion artifacts, has at least 95 to 98 percent ability to detect an aortic dissection, so that is the most commonly performed test,” added Dr. Braverman.

Pertinent Insights into the Imaging of Patients with Marfan Syndrome

Image IQ Quiz: Middle-Aged Female with Chest Pain, Back Pain and Shortness of Breath

AI-Powered Algorithm May Enhance CT Assessment of Aortic Dissection

For more insights from Dr. Braverman, watch the video below.

In a recent interview, Alan Braverman, M.D., discussed challenges with the detection of aortic dissection, reviewed pertinent risk factors and offered insights on imaging that may facilitate earlier diagnosis of the life-threatening condition. 

Keys to Detecting Aortic Dissection: An Interview with Alan Braverman, MD

New research suggests that a computed tomography (CT)-based deep learning model may offer comparable detection of lung cancer while offering a significant reduction of false positive findings in contrast to the Pan-Canadian Early Detection of Lung Cancer (PanCan) risk stratification model.

For the retrospective study, recently published in 

, researchers assessed the deep learning model in a cohort of 4,146 participants with a median smoking history of 38 pack years. The cohort included 7,614 benign nodules and 180 malignant nodules, according to the study authors.

The researchers found that the deep learning model offered an equivalent AUC for predicting cancer at one year (98 percent) and a slightly higher AUC at two years (96 percent vs. 94 percent) in comparison to the PanCan model. For cases involving indeterminate nodules on CT, the study authors noted the deep learning model correctly identified 68.1 percent of benign lesions as low risk at one year in comparison to 47.4 percent with the PanCan model.

“We saw that we could reduce the false positive rate relative to (the) PanCan (model) by 39.4 percent, which is substantial, without missing any of the cancers that required urgent care … cancers that were diagnosed within one year during the initial screening trials,” noted lead study author Noa Antonissen, M.D., who is affiliated with the Department of Medical Imaging at Radboud University Medical Center in Nijmegen, the Netherlands.

“… Having an AI tool that can do an accurate risk stratification at the level of an expert radiologist can really help to manage these screenings better, so that we can reduce the number of false positive screens in the end to the minimum that we need to still detect the cancers that we find in the screening program,” added study co-author Colin Jacobs, Ph.D., an associate professor of artificial intelligence in thoracic oncology at the Radboud University Medical Center in Nijmegen, the Netherlands. “I think that is the ultimate goal that we have with this research: that we can support screening programs with AI tools that improve the effectiveness and the efficiency of our screening programs.”

Can Deep Learning Enhance Low-Dose Chest CT Assessment of Lung Cancer Risk?

Can CT-Based Deep Learning Bolster Prognostic Assessments of Ground-Glass Nodules?

Olympus Launches CT-Based AI Software for Emphysema Screening

For more insights from Drs. Antonissen and Jacobs, watch the video below.

In a recent interview with Diagnostic Imaging, Noa Antonissen, M.D., and Colin Jacobs, Ph.D., discussed new research findings demonstrating robust risk stratification with a CT-based deep learning model for lung nodules as well as a 39.4 percent reduction in false positives in comparison to traditional classification. 

CT-Based Deep Learning Model May Reduce False Positives with Indeterminate Lung Nodules by Nearly 40 Percent

Exposure to a single computed tomography (CT) scan up to four weeks prior to conception was associated with an eight percent higher risk of spontaneous pregnancy loss and a six percent higher risk of congenital anomaly, according to new research published in the 

For the retrospective study, researchers examined the impact of CT-associated radiation with data from 5,142,339 pregnancies and 3,451,968 live births that occurred between 1992 and 2023. The mean maternal age of the cohort was 29, according to the study authors.

Based on adjusted hazard ratios (aHRs), the study authors noted an eight percent higher risk for spontaneous pregnancy loss (including miscarriage, ectopic pregnancy or stillbirth) for one CT scan obtained four weeks prior to pregnancy, a 14 percent higher risk with two CT scans and a 19 percent higher risk for three or more CT scans.

“We found that not only was there a relationship between the use of CT scan and spontaneous pregnancy loss, it was a dose-dependent relationship,” noted lead study author Camille Simard, MD, MSc in a recent interview with 

. “We saw that in individuals who had no CT versus one two or three or more CTs, the risk of spontaneous pregnancy loss, or rather, pregnancy loss, increased.”

Exposure to CT scans within four weeks prior to conception was also associated with increased risks of congenital anomalies, according to Dr. Simard, an assistant professor of medicine in the Department of Medicine within the Division of General Internal Medicine at McGill University in Montreal. Utilizing aHRs, Dr. Simard and her colleagues noted a six percent higher risk with one CT scan, an 11 percent higher risk for two CT scans and 15 percent higher risk for three or more CT scans.

Dr. Simard noted that these results were drawn from a retrospective database study with possible residual bias and that the overall effect of CT radiation was small in proportion to the study cohort.

“We have to be cautious with our interpretation. (These are) very interesting findings that hopefully will generate more questioning and more research around this area,” added Dr. Simard. “ … In no way is this study discouraging the use of CT when indicated to rule out important pathologies but I think it generates a hypothesis that maybe other modalities could be explored in this patient population.”

New Study Examines Impact of Mammography in Detecting Pregnancy-Associated Breast Cancer

FDA Clears AI-Enhanced Portfolio of Ultrasound Systems for Women with High-Risk Pregnancies

Predicting Nipple-Areolar Complex Involvement in Early-Stage Breast Cancer: Can Cone-Beam CT Have an Impact?

For more insights from Dr. Simard, watch the video below.

In a recent interview, Camille Simard, M.D., MSc, discussed findings from a new study assessing elevated risks of spontaneous pregnancy loss and congenital anomalies associated with CT exposure in the month prior to conception.

New Research Examines Radiation Risks with CT Exposure Prior to Pregnancy 

Welcome to Diagnostic Imaging’s Weekly Scan, which offers an opportunity to catch up on the most well-viewed radiology content of the past week.

While there has been a fair amount of hype about whole-body MRI, a 

 found the modality had a pooled cancer detection rate of 1.57 percent in asymptomatic individuals. The meta-analysis authors also noted that many of the reviewed studies had incomplete data with respect to follow-up and diagnostic outcomes.

While maintaining that artificial intelligence (AI) for breast imaging is at an “infancy” stage, Zeeshan Shah, M.D., noted in a recent 

a pathway where AI has increased capability of pinpointing negative mammography exams

, enabling radiologists to spend significantly more time on cases that are more ambiguous and concerning.

In other breast imaging news, a new study published in the 

 compared AI software to radiologist interpretation for digital mammography (DM) and digital breast tomosynthesis (DBT). The researchers found that 

AI offered comparable negative predictive value (NPV) but significantly higher recall rates and false positive results as well

In a cohort of over 8,700 current and former smokers, the authors of a new study in 

found that coronary artery calcium (CAC) scoring derived from non-gated low-dose computed tomography (LDCT) scans demonstrated significant capability for 

predicting long-term cardiovascular disease mortality up to 25 years

, pediatric cardiologist Takeshi Tsuda discussed 

integrated wall stress, a product of peak systolic wall stress (PS-WS) calculated with M-mode echocardiography as well as heart rate

. Citing recently published research, Dr. Tsuda said integrated wall stress could be a key marker of pre-clinical cardiomyopathy in patients with Duchenne muscular dystrophy.

Diagnostic Imaging’s Weekly Scan: August 31 — September 6

Diagnostic Imaging's Weekly Scan: August 31 — September 6

Conventional assessments for possible coronary artery disease based on presenting symptoms and/or risk profiles are inadequate, according to Amir Ahmadi, M.D.

In a recent interview, Dr. Ahmadi noted key research findings —presented at the European Congress of Cardiology in 2024 and currently being evaluated for a peer-reviewed publication — that showed that 67 percent of patients under 65 with a first heart attack had no pain two days prior, 54 percent had no pain until the day of the heart attack, and 47 percent of patients wouldn’t have met criteria for statin initiation two days prior to a heart attack.

“Coronary disease is a plaque in the heart. … We do everything about risk stratification by measuring the LDL (low-density lipoprotein) in the bloodstream, not the heart vessels. Now plaque quantification and looking at a CT can actually tell us … about the quantification of what actually matters at the level of the heart vessel, and that's game changing in my opinion,” emphasized Dr. Ahmadi, an associate professor of medicine and cardiology, and director of inpatient cardiology at the Mount Sinai Fuster Heart Hospital in New York City.

Dr. Ahmadi said use of the AI-powered software PlaqueIQ (Elucid) with computed tomography angiography (CTA) facilitates a shift from “risk factor guesstimation to treating the disease itself.” Not only does PlaqueIQ bolster accuracy with initial assessments, it enables monitoring of treatment as well, according to Dr. Ahmadi, who will be presenting on CT-guided treatment of CAD at the Society of Cardiovascular Computed Tomography (SCCT) conference in Montreal, Canada.

“What you need is an accurate, objective and reproducible measurement of different types of plaque, and specifically the types of plaque that are known to make the person and the lesion more prone to have a plaque rupture and heart attack,” maintained Dr. Ahmadi, the lead scientific advisor for Elucid.

Can Emerging AI Software Offer Detection of CAD on CCTA on Par with Radiologists?

Study Shows Enhanced Diagnosis of Coronary Artery Stenosis with Photon-Counting CTA

Meta-Analysis Shows Merits of AI with CTA Detection of Coronary Artery Stenosis and Calcified Plaque

For more insights from Dr. Ahmadi, watch the video below.

In a recent interview, Amir Ahmadi, M.D., discussed limitations of conventional diagnostic assessments for people with suspected coronary artery disease, and the emergence of AI-enabled plaque quantification to facilitate more timely detection and intervention.

Emerging Concepts in CT-Guided Treatment of Coronary Artery Disease

Emphasizing the preventative benefit of computed tomography angiography (CTA), C. Alberto Morales, M.D., discussed a friend whose father had a heart attack in his mid-30s. Given the family history, the friend had annual stress testing with cardiologists and was told he was in good shape and even had a zero coronary artery calcium (CAC) score.

However, a CTA scan in Dr. Morales’s office revealed that his friend had diffuse coronary artery disease and a 70 to 80 percent blockage in the mid-right coronary artery (RCA). After aggressive management, follow-up CTA imaging at one year showed a 36 percent decrease in the RCA blockage and stabilization in other arteries, according to Dr. Morales, the owner of South Tampa Cardiology and Advanced Imaging Center in Tampa, Fla.

In a recent interview, Dr. Morales said advances in CTA scanning has led to a significant shift in preventive capabilities with CTA. In addition to significantly lower and more consistent radiation dosing (approximately three millisieverts (mSvs) per CTA scan), Dr. Morales cites the enhanced resolution going from a traditional 64-slice CT scanner to the 560-slice SpotLight CT scanner (Arineta).

In a recent interview, C. Alberto Morales, M.D., discussed the impact of advances with CTA imaging and AI, and a shifting emphasis in cardiac risk stratification from stenosis to plaque burden.

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