- AI
- Molecular Imaging
- CT
- X-Ray
- Ultrasound
- MRI
- Facility Management
- Mammography
New SNMMI President Cathy Cutler, PhD Discusses Current Challenges and Goals for Nuclear Medicine
In a recent interview, Cathy Cutler, Ph.D., shared her perspective on a number of topics affecting nuclear medicine, ranging from isotope availability and reimbursement challenges for diagnostic radiopharmaceuticals to increasing patient interest in PET imaging.
A longtime researcher who has over two decades of experience in the development and assessment of radiopharmaceuticals, Cathy Cutler, Ph.D., said she is excited about the increased patient interest in positron emission tomography (PET).
“We’re at a point where patients know so much more about PET and they’re asking for this. They want to ensure their doctors have these tools to better inform their therapies. It’s exciting to see that. When you talk to patients, they’re out there now fighting with us to help make sure they have access to PET imaging, It’s not where I thought we would be about 20 years ago but it’s very exciting to see that is where we are today,” noted Dr. Cutler, the new president of the Society of Nuclear Medicine and Molecular Imaging (SNMMI).
Dr. Cutler said it’s important to build upon that enthusiasm in recruiting talented people into the field. Through recent surveys conducted through the SNMMI’s workforce pipeline, Dr. Cutler noted significant numbers of pending retirees so there is increasing urgency to ramp up recruiting efforts. Noting a visit to a local high school in Toronto by SNMMI leaders during the conference, Dr. Cutler said video testimonials from physicians, scientists, and technologists about the benefits of the field are also being shared with younger audiences to help spark interest.
As the director of the Medical Isotope Research Production and Development Group at Brookhaven National Laboratory in New York. Dr. Cutler said isotope availability is an ongoing challenge with demand likely to increase as more radiopharmaceuticals are utilized in patient treatment. Appropriate reimbursement is another challenge in the field, according to Dr. Cutler.
“Unfortunately, the CMS … looks at diagnostic radiopharmaceuticals as supplies, kind of like gloves so they basically bundle the costs,” posted Dr. Cutler. “It turns out those costs really don’t cover what it takes us to manufacture those drugs.”
(Editor’s note: For related content, see “SNMMI: Study Shows Viability of FAPI PET/CT for Predicting Progressive Pulmonary Fibrosis in Lung Disease Patients,” “Meta-Analysis Assesses Impact of PSMA PET/CT for Staging of Renal Cell Carcinoma” and “Study: PSMA PET/CT May Rule Out csPCa in 93 Percent of PI-RADS 3 Lesions.”)
For more insights from Dr. Cutler, watch the video below.
New Study Shows Non-Radiologists Interpreting 28 Percent of Imaging for Medicare Patients
June 28th 2024While radiologists interpreted approximately 99 percent of all non-cardiac CT, MRI and nuclear medicine studies in hospital and emergency department settings for Medicare beneficiaries, new research shows significantly less radiologist review of cardiac imaging and office-based imaging.
Study Examines Prognostic Value of 68Ga-PSMA-11 PET/CT for Patients at High Risk of PCa
June 21st 2024Initial detection of metastatic prostate cancer via 68Ga-PSMA-11 PET/CT was significantly associated with PSA values > 20 ng/ml, ISUP grade > 3 and MRI T-stage > 3, according to research presented recently at the SNMMI conference.
Study Shows PET/CT is Superior to SPECT/CT in Managing Patients with Primary Hyperparathyroidism
June 21st 2024F18-choline PET/CT imaging guidance for minimally invasive parathyroidectomy (MIP) procedures led to a 29 percent higher percentage of normocalcemia at one month post-op in comparison to imaging guidance with Tc99m-sestaMIBI (MIBI) SPECT/CT, according to new research.
Can Deep Learning Automate Amyloid Positivity Assessment on Brain PET Imaging?
June 14th 2024In validation testing with 205 18F florbetapir PET scans from 95 patients with Alzheimer’s disease, a deep learning model demonstrated a 93.2 percent accuracy rate and a 97 percent AUC for detecting amyloid-β positivity.
