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Ryan McBeth

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#MyRadGirlfriend No. 88: Data is king, but food fills seats
Data is all the rage as healthcare analysts look for quantitative measures of healthcare quality. But how do you get busy attending physicians and residents to fill out surveys? Find out one trick in the next installment of #MyRadGirlfriend.
June 27, 2019
2019 06 27 21 00 5137 2019 06 28 My Rad Girlfriend 88 Food Thumbnail
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#MyRadGirlfriend No. 87: The feminist narrative
Do today's research trials adequately reflect medical outcomes in women? Or are they too focused on men? Ryan starts to wonder in the next installment of #MyRadGirlfriend.
June 13, 2019
2019 06 13 21 30 9977 2019 06 14 My Rad Girlfriend 87 Feminist Thumb
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#MyRadGirlfriend No. 86: Think before you scoot
Electric scooters are everywhere now, and while they can be a lot of fun, they also can have unintended consequences. One of those is more work for radiologists who read imaging studies from the emergency room -- including Andy, who decides to make a statement in the next installment of #MyRadGirlfriend.
May 30, 2019
2019 05 30 20 32 7032 2019 05 31 My Rad Girlfriend 86 Scooter Thumb
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#MyRadGirlfriend No. 85: The magic of Cinco de Mayo
With the Cinco de Mayo holiday approaching, many hospital residents who aren’t working or aren’t on call have the opportunity to blow off a little steam. Priya and Andy are no different, as we discover in the next installment of #MyRadGirlfriend.
May 2, 2019
2019 05 03 00 54 1997 2019 05 03 My Rad Girlfriend 85 Guacamole Thumb
Emergency Radiology
#MyRadGirlfriend No. 84: The most dangerous place
Yes, the emergency room can be a dangerous place for a physician. But even greater danger can be found elsewhere in the hospital, as we learn in the next installment of #MyRadGirlfriend.
April 11, 2019
2019 04 11 21 48 3790 2019 04 12 My Rad Girlfriend 84 Dangerous Thumb
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#MyRadGirlfriend No. 83: Circling the drain
One of the most challenging things about a radiologist's job can be dealing with referring clinicians, especially ones that are particularly obstinate, as Dr. Rankin is in the next installment of #MyRadGirlfriend.
March 21, 2019
2019 03 21 16 29 7667 My Rad Girlfriend Thumb Drain
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#MyRadGirlfriend No. 82: When you hear hoofbeats ...
It's been a late night in the reading room, and Andy encounters a perplexing case that could have a variety of differential diagnoses. Find out how she settles on the correct one in the next installment of #MyRadGirlfriend.
March 7, 2019
2019 03 07 22 01 3228 My Rad Girlfriend Thumb Zebras
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#MyRadGirlfriend No. 81: The price to pay for being antivax
Antivaxxers may think they're doing the right thing for their kids, but there's a price to pay for not getting vaccinated -- and it's mainly paid by their children, as Andy and Ryan find out in the next installment of #MyRadGirlfriend.
February 21, 2019
2019 02 21 19 11 9814 My Rad Girlfriend Thumb Vaccine
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#MyRadGirlfriend No. 80: Anxiety in the reading room
What fears push your anxiety buttons? For some radiologists, it's the board exam, while others have more existential concerns. Andy has to face some of her internal demons during a long night in the reading room in the next installment of #MyRadGirlfriend.
February 7, 2019
2019 02 07 19 36 8884 My Rad Girlfriend Thumb Anxiety
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#MyRadGirlfriend No. 79: How sweet it is
Most folks would agree that the explosion of new coffee varieties is a great thing. But they can have a downside, as Andy and Priya find out in the next installment of #MyRadGirlfriend.
January 24, 2019
2019 01 24 23 01 1287 My Rad Girlfriend Thumb Sugar
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A visual abstract of the study.
SNMMI 2026
SNMMI: Machine learning model predicts RPT dose
Dosimetry plays a central role in optimizing lutetium-177 (Lu-177) PSMA therapy, yet calculating it currently depends on post-therapy imaging.
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Breast
ASCO: Surveillance MRI boosts breast cancer detection for Black women
Kiara Schmidt of Froedtert Health presented a study May 30 at the SNMMI annual meeting.
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SNMMI: Text confirmations cut PET/CT cancellations by 73.5%
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SNMMI 2026
SNMMI: Vaccination misreporting puts FDG PET cancer reads at risk
The Wedding Was Easy. The Marriage Is the Work.
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The Wedding Was Easy. The Marriage Is the Work.
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AI model predicts 10-year breast cancer risk
By Amerigo Allegretto
A mammography-based AI model showed strong performance in predicting 10-year breast cancer risk over clinical and other AI models.
May 20, 2026
Breast Cancer3
AI devices vary widely in lung cancer detection
By Will Morton
Three devices helped detect more cancerous tumors, whereas the other four devices helped detect fewer tumors.
May 19, 2026
Cropped secondary capture examples. These are illustrative and not intended to imply superiority or inferiority of any device. (A) Posteroanterior radiograph in a 46-year-old female patient. The device correctly identified a right lower lobe nodule projected below the right hemidiaphragm and hilar lymphadenopathy. (B) Posteroanterior radiograph in an 86-year-old female patient with a classic Golden S sign highly suggestive of cancer. Three devices did not identify any findings. (C) The output from one device for the same radiograph as in B. The device placed a contour around the area of abnormality but mislabeled it as segmental collapse, and there are no other elements in the output to raise suspicion of cancer. (D) Posteroanterior radiograph in a 60-year-old male patient -- a case of confirmed lung cancer that was not deemed visible in retrospect. The device identified multiple false-positive abnormalities. (E) Posteroanterior radiograph in a 77-year-old female patient with two right lower lobe nodules. The device mislabeled the abnormality as infection -- a diagnostic term that could incorrectly influence clinical management. (F) Posteroanterior radiograph in a 77-year-old female patient with a right hilar tumor. Most of the lungs have been labeled by the device, with excessive overlap of the abnormality that pragmatically represents an incorrect result. All annotations shown were produced by the devices. LL = lung lesion, LO = lung opacity, PO = pleural other, TBC = tuberculosis.
MRI-based ML model shows promise in colorectal cancer subtyping
By Amerigo Allegretto
A machine-learning model based on MRI radiomics achieved high performance in predicting colorectal cancer subtypes.
May 19, 2026
Overview of the study design, including data collection, radiomics model construction, and biologic interpretation. (A) The primary cohort for model development and evaluation in the training and internal test sets includes 168 patients with colorectal cancer (CRC) from center 1 (Fudan University Shanghai Cancer Center), whereas external testing was performed using data from 85 patients from centers 2 (Huashan Hospital, Fudan University) and 3 (Zhongshan Hospital, Fudan University). For model interpretation, RNA sequencing (RNA-seq) data from 18 patients with CRC in center 1 and single-cell data from 35 patients from the Gene Expression Omnibus (GEO) database are incorporated. Mismatch repair (MMR) protein expression, obtained from pathologic reports in electronic medical records (EMRs), was used to identify patients with consensus molecular subtype 1 (CMS1) CRC. Tissue microarrays (TMAs) from surgically obtained CRC tissues were analyzed for immunohistochemical staining of caudal-type homeobox 2 (CDX2), 5-hydroxytryptamine receptor 2B (HTR2B), FERM domain containing 6 (FRMD6), and zinc finger E-box binding homeobox 1 (ZEB1), and the results were subsequently entered into an online classification tool that assigned patients to CMS2, 3, or 4 subtypes. (B) Radiomics workflow for CMS4 prediction. Lesions were manually delineated on T2-weighted imaging (T2WI) and contrast-enhanced (CE) T1-weighted imaging (T1WI), followed by radiomics feature extraction. Feature selection and model development were performed in the training set using machine-learning algorithms with fivefold cross-validation for model selection, and the final model was evaluated in the internal and external test sets using receiver operating characteristic (ROC) curve analysis. (C) Transcriptomic interpretation workflow. Using the radiomics-predicted CMS4 classification, bulk RNA sequencing (RNA-seq) data were used to perform differential expression analysis between predicted CMS4 and non-CMS4 groups, followed by pathway enrichment analyses to assess biologic relevance. Public single-cell RNA sequencing data from the Gene Expression Omnibus database were then used for cell-type–level interrogation to support interpretation of the associated pathways.
Podcast: Expert witness hats come out to begin closing investigation
By Liz Carey
The episode the hosts have eagerly anticipated.
May 19, 2026
The Invisible Force Podcast Album Cover Auntminnie Jan 2026 Thumbnail sra O0 D Ij Z6
Almost half of families face financial hardship from kids' scans
By Kate Madden Yee
These families are more than three times as likely to delay or skip recommended scans because of cost.
May 19, 2026
Mri Scanner Kid
Combined fluoride and lead exposure reduces bone health in youth
By Will Morton
Co-exposure to fluoride and lead exacerbates changes in BMD more than single exposure, suggesting synergistic effects on bone impairment.
May 18, 2026
A graphical abstract of the study.
Medical societies applaud proposed CEUS training recommendations
By Amerigo Allegretto
Ultrasound societies are voicing support for new proposed training standards by CAAHEP for CEUS education.
May 18, 2026
Contrast Injector 400
Cochrane updates 2013 prostate cancer screening review
By Kate Madden Yee
Standard PSA screening has a well-known weakness: it catches many slow-growing cancers that would never have caused harm, Cochrane said.
May 18, 2026
Prostate
ISMRM: fMRI flags brain network failures in fibromyalgia, long COVID
By Kate Madden Yee
While both conditions demonstrate reduced brain network flexibility, the underlying mechanisms differ.
May 18, 2026
Muscle Trigger Points Sized
ISMRM: PET/MRI highly effective in patients with atherosclerosis
By Will Morton
PET/MRI distinguished symptomatic from asymptomatic carotid plaques among 145 patients.
May 15, 2026
Multimodality imaging (MRI, PET, and fused PET/MRI) of carotid artery plaques in asymptomatic and symptomatic subjects, illustrating distinct features of surface ulceration, plaque enhancement, metabolic uptake, and SUVmax.
ISMRM: Researchers eye fibrosis patterns in the body's organs
By Liz Carey
Quantitative measures obtained from MRIs enable fibrotic scoring system, according to group.
May 15, 2026
Fibrotic Buckets Disease Inclusion Uk Biobank Population Ismrm2026
ISMRM: PET/MRI-guided treatment reduces low back pain
By Will Morton
This study is the first to acquire follow-up FDG-PET/MRI scans after treatment to assess the correlation between clinical outcome and FDG uptake.
May 15, 2026
A 70-year-old female patient with chronic low back pain. History of radicular syndrome which led to targeted nerve block with positive effect. However, lower back pain persisted. FDG-PET/MRI showed increased FDG uptake in a disc herniation at L5-S1 (SUVmax 1.6) convincing the treating physician to proceed to discectomy. After discectomy, the patient is now mostly pain free.
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