United States

Background:
Magnetic Resonance Imaging (MRI) has been a large component of the evaluation of breast lesions in high-risk women for the last decade. Many of these imaging tools have been developed to assist physicians in risk stratifying patients. Specifically, Time Activity Curves (TAC) have been utilized to incorporate contrast uptake patterns into decision making. In the years since its inception, new tools have been developed to more efficiently and accurately classify different TACs, such as DynaCAD. Previous studies on the use of TAC curves have indicated their accuracy is not sufficient to be utilized without morphological and historical data being incorporated, but it is unclear how the improvements noted in these tools affects these results. Therefore, we re-evaluate TACs within a broad patient population and treatment landscape.
Methods:
We performed a retrospective chart review of 48 patients who received both an MRI with DynaCAD TAC analysis followed by a diagnostic biopsy. Of the 48 patients evaluated, 18 were malignant and 30 were benign. We performed statistical analysis for sensitivity, specificity, negative predictive value (NPV) and positive predictive value (PPV) on this set of patient results, stratifying by the individual kinetic classification as well as the generally accepted associations of each type with malignancy (Type 1 classically benign, Type 2 and 3, concerning for malignancy). We performed a literature search for previously reported TAC statistics.
Results:
From the 48 patients evaluated, washout curves utilized alone as a marker of malignancy status resulted in a sensitivity of 64.3%, specificity of 73.5% and PPV of 50% and NPV of 83%. When stratified by individual TAC curve type, persistent was calculated to have 50% and 81.1% sensitivity and specificity, respectively. Plateau was calculated to have a 72% and 94% sensitivity and specificity, respectively. Washout was calculated to have a 78.3% and 76.9% sensitivity and specificity, respectively.
Conclusion:
For years, TAC curves have been utilized to enhance radiologists’ ability to classify breast lesions as likely benign or malignant in high-risk patients. In our study we evaluated the accuracy of TACs with the new improvements provided by more advanced commercial tools. We have found TAC curves have improved in their accuracy with the rapid improvement of analysis tools. However, their primary benefit lies in being an ancillary tool for determining benignlesions along with morphological data and they still struggle in accurately predicting malignancy on biopsy. The study is limited due to its lower total patient population.

2023 AMA Research Challenge

Revisiting Time Activity Curves in Breast MRI: Has it kept up with the times?

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Join the AMA Research Challenge poster symposium and semifinals to explore top research posters, score posters in the semifinals (an AMA member exclusive opportunity) and attend education sessions with experienced physicians to learn tips to advance your research and career. 

Background: Prostate cancer (PCa) is the second most commonly diagnosed malignancy and the second leading cause of cancer death in men in the United States. Traditional screening for PCa has included monitoring of prostate specific antigen (PSA) levels and systematic transrectal ultrasound-guided (TRUS) prostate biopsy. Recommendations for PCa screening are evolving with recent advances in multi-parametric MRI (mp-MRI) of the prostate. However, negative findings on mp-MRI of the prostate in patients with suspicion of PCa can lead to uncertainties regarding clinical management. This study therefore aims to evaluate the detection rate of PCa by TRUS biopsy in patients with negative mp-MRI.

Methods: The records of 253 patients without evidence of PCa on mp-MRI performed at the Virginia Commonwealth University Health System between 2018 and 2023 who also underwent TRUS prostate biopsies were retrospectively reviewed. Clinical information including age at mp- MRI, PSA levels, and prostate volume, as well as surgical pathology results, namely presence of malignancy, Gleason score (GS), and percentage of positive cores on biopsy, were recorded for these patients. Ultimately, the incidence of clinically significant PCa (GS ≥ 7) and clinically insignificant PCa (GS 6) detected on TRUS-guided biopsy was determined.

Results: Of 253 patients with negative mp-MRI findings, 126 (49.8%) had PCa at TRUS biopsy. Among these 126 patients, 37 had clinically significant PCa with GS 7-9 (14.6% of patients with negative mp-MRI, 29.4% of those with biopsy-proven PCa), and 89 had clinically insignificant PCa with GS 6 (35.2% of patients with negative mp-MRI, 70.6% of those with biopsy-proven PCa). Of the patients with clinically significant PCa, 89.2% (33 patients) had PCa up to GS 7, 5.41% (2 patients) had PCa up to GS 8, and 5.41% (2 patients) had PCa up to GS 9 on TRUS-
guided biopsy. The remaining 127 patients (50.2% of total patients with negative mp-MRI) had no evidence of PCa on TRUS biopsy. There was no statistically significant difference in age, PSA level, or prostate volume between patients with PCa and without PCa at biopsy.

Conclusion: This retrospective study confirms that a percentage of patients without evidence of PCa at mp-MRI of the prostate may still have clinically significant PCa and may benefit from further screening, including TRUS biopsy. Further research may be of benefit to determine optimal screening for PCa.

Detection Rate of Prostate Cancer at Systematic Prostate Biopsy in Patients with Negative mp-MRI of the Prostate: A Retrospective Study

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**Abstract:**



Comparison of Phased-Array 3.0T and Endorectal 1.5 T Magnetic Resonance Imaging in Detection of Seminal Vesicle Involvement and Extracapsular Extension in Prostate Cancer; Using Pathological Findings at Prostatectomy as a Gold Standard

Abbreviated Breast MRI Protocol: A Feasible Alternative for Breast Screening

OBJECTIVE
Despite rising popularity and performance, studies evaluating the use of LLMs for clinical decision support are lacking. Here, we evaluate ChatGPT 3.5 and 4’s capacity for clinical decision support in radiology via the identification of appropriate imaging services for two important clinical presentations: breast cancer screening and breast pain.
METHODS
We compared ChatGPT's responses to the American College of Radiology (ACR) Appropriateness Criteria for breast pain and breast cancer screening. Our prompt formats included an open-ended (OE) and a select all that apply (SATA) format. Scoring criteria evaluated whether proposed imaging modalities were in accordance with ACR guidelines. Three replicate entries were conducted for each prompt, and the average of these was used to determine final scores.
RESULTS
Both ChatGPT 3.5 and 4 achieved an average OE score of 1.830 (out of 2) for breast cancer screening prompts. ChatGPT 3.5 achieved a SATA average percentage correct of 88.9%, compared to ChatGPT 4’s average percentage correct of 98.4% for breast cancer screening prompts. For breast pain, ChatGPT 3.5 achieved an average OE score of 1.125 (out of 2) and a SATA average percentage correct of 58.3%, as compared to an average OE score of 1.666 (out of 2) and a SATA average percentage correct of 77.7%. 
DISCUSSION
Our results demonstrate the eventual feasibility of using LLMs like ChatGPT for radiologic decision making, with the potential to improve clinical workflow and responsible use of radiology services. More use cases and greater accuracy are necessary to evaluate and implement such tools.


Evaluating GPT as an Adjunct for Radiologic Decision Making: GPT-4 Versus GPT-3.5 in a Breast Imaging Pilot

Background: The EMBARK trial is a phase 3, randomized, study evaluating use of enzalutamide with or without concomitant leuprolide in non-metastatic castrate sensitive prostate cancer patients. Trial enrollment relied upon conventional imaging which under detects metastatic disease in comparison to PSMA-PET imaging. The aim of this post-hoc retrospective analysis was to describe the PSMA-PET findings and survival outcomes in a patient population representative of the EMBARK trial. 

Methods: This was a post-hoc, retrospective analysis of 5 prospective studies of PSMA-PET conducted at UCLA from 2016 to 2021 that included patients with recurrent PCa. Patients were included if they met eligibility EMBARK trial enrollment at the time of their PSMA scan as per the following: Rising PSA above 1.0ng/mL (post RP and SRT) or 2.0ng/mL >nadir (post-RT), PSA doubling time ≤9 months, Serum testosterone ≥150 ng/dL. PSMA PET findings (PROMISE miTNM stage, number of lesions) and survival outcomes were collected from clinical reports. Descriptive statistics (median, range) and Kaplan-Meier modeling (median, Confidence intervals) were used.

Results: From 2002 patients screened, 146 patients were included in the analysis. Median pre-scan PSA levels and PSA doubling time in patients who underwent RP (n=85), dRT (n=22), post-RP SRT (n=39) and overall (n=146) were 2.4 ng/mL (1-72.1), 8.3 ng/mL (2.37-202), 2.58 ng/ml (1.1-32.3), 2.7 ng/mL (1-202), and 3.5 months (1-9), 3.3 months (1-9), 4.4 months (1-9), 3.7 (1-9) months, respectively. PSMA-PET was positive in 80%, 41%, 85%, 83% of RP, dRT, RP + SRT and overall populations, respectively. Poly-metastatic disease (≥5 lesions) was found in 19%, 32%, 21% and 21% of cases, respectively. PSMA-PET detected disease only localized to the prostate fossa (miT+N0M0) in 7%, 32%, 0% and 9%. PSMA-PET detected any distant metastatic disease (miTxNxM1) in 33%, 41% 56% and 40% respectively. PSMA-PET detected metastatic nodal disease (N1 and/or M1a) in 58% 32% 74% and 39% and osseous disease (M1b) in 19% 23% 31% and 23% cases. Twenty-eight patients received androgen receptor-axis therapy (ARSi) or androgen deprivation therapy (ADT) following PSMA-PET had available outcome data. Recurrence free survival in ARSi compared to the ADT cohort was 53 months vs 22 months (p=0.008).
Conclusion: In this “EMBARK-like” cohort of patients with high-risk nmCSPCa and PSA DT<9 months, PSMA-PET detected M1 disease in 40% of patients, over one-fifth of cases presented with 5 or more lesions and those receiving ARSi had significantly improved recurrence free survival. Further studies are needed to assess its independent prognostic value and use for treatment guidance.

PSMA PET findings in an “EMBARK-like” cohort of patients with high-risk non-metastatic hormone-sensitive prostate cancer: A single center post-hoc retrospective analysis

BACKGROUND:
Rheumatoid arthritis (RA) is a chronic autoimmune disease impacting about 1.3 million Americans, with women much more likely to be affected than men. The development of this systemic inflammatory disease is influenced by both genetic and environmental factors. Certain environmental factors, such as diet, can be more readily controlled by individuals, and therefore may serve as more attainable therapeutic targets for preventing and mitigating RA and its symptoms. 

Various foods and nutrients are associated with inflammatory biomarkers1,2,3,17, and thus have been linked with increased or decreased risk of RA. However, these associations have been inconsistent across studies likely due to overall systematic bias, measurement error associated with individual food groups and nutrients, and limited investigations evaluating the relationship between overall dietary patterns and RA in larger sample sizes4,5,6,12. Furthermore, few studies that have examined the impact of overall dietary patterns on RA but have had conflicting results and/or generally involved smaller sample sizes. 

OBJECTIVE:
Our objective is to evaluate the association between dietary quality, as measured by the 2015 Healthy Eating Index (HEI-2015), and risk of incident rheumatoid arthritis (RA) in postmenopausal women.

METHODS: 
109,591 postmenopausal women without baseline RA were prospectively followed as part of the Women’s Health Initiative (WHI) for an average of 8.1 years. Baseline diet was measured using a food frequency questionnaire (FFQ) and diet quality was evaluated using the HEI-2015. Multivariable Cox proportional regression analysis was performed evaluating the association of diet quality with self-reported physician diagnosed RA after adjusting for age, race, education status, income, and body mass index (BMI). 

RESULTS:
During 1,241,532 person-years of follow-up, 5,823 incident RA cases were identified. Compared to quartile 1, quartiles 2, 3, and 4 of the HEI-2015 scores were associated with a reduced RA risk of 3%, 13%, and 18%, respectively (p-trend <0.001). A higher score for total fruits (p-trend=.006), whole fruits (p-trend<.001), total vegetables (p-trend=.004), dark green vegetables (p-trend<.001), whole grain (p-trend=.004), total dairy (p-trend=.004), and seafood/plant protein (p-trend=.015) consumption was significantly associated with lower rates of incident RA independent of age and confounders. Conversely, a higher score for consumption of percent saturated fat (p-trend=.001) was significantly associated with higher rates of incident RA (Table 3).

CONCLUSIONS:
A higher quality diet rich in fruits, vegetables, whole grain, dairy, and seafood/plant protein, is associated with a lower risk of developing RA in postmenopausal women. Meanwhile, a less healthy diet with higher intake of percent saturated fat is associated with higher risk of RA.

Association of Diet Quality with Risk of Incident Rheumatoid Arthritis in the Women’s Health Initiative

Background/Purpose: The purpose of this study was to investigate factors associated with objective cognitive impairment in patients diagnosed with Systemic Lupus Erythematous (SLE). The prevalence of subjective complaints are common, and previous studies have showed a general decline in immediate memory and total memory. 
Methods: This study was conducted using baseline data from ClearMEMory (Clearing Lupus Fog with Memantine). Seventy-nine participants who reported neuropsychiatric symptoms and came for screening were included. The dependent variable was the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS), a brief, age-normalized, individually administered battery to measure cognitive decline or improvement. Potential predictive variables were sex, race, ethnicity, age, ESR, anti-dsDNA antibodies, the polysymptomatic distress scale (PSD) and the hospital anxiety and depression scales (HADS-A, HADS-D). Regression models were run to determine covariates that effect the RBANS total and the RBANS immediate memory. The models examined HADS scores between 6-12 to determine if there was a statistically significant difference when the scores went from normal to depressed. The models used PSD values 12-16 which are values that cross the threshold for diagnosis of fibromyalgia.
Results: Participant’s median age was 51 years, and they were predominantly female (96%), non-Hispanic (94%) and White (70%) (Table 1). We used linear regression to model the RBANS total score. A model including HADS-D, PSD, and race was the most significant (p = 0.0004) (Table 2). As the HADS depression score increased from 6 to 12, the RBANS total decreased by 3.95 points and as the PSD total increased from 12 to 16, the RBANS total decreased by 2.35 points on average. Non-Whites, when compared to Whites had a decrease in the RBANS total by 7.77 points. The most significant model for RBANS immediate memory included the same factors (p = 0.0004, Table 3). 
Conclusion: Results support race, depression, and polysymptomatic distress as significant contributors to the risk of cognitive impairment in patients with SLE. Disease activity did not appreciably affect cognition in this participant sample. As participant scores crossed thresholds for depression or fibromyalgia diagnosis, measurable declines in cognition, particularly immediate memory, were observed. Further studies with different measures of cognition are necessary to understand the impact of race in these models.

Predictors of Cognitive Impairment in Individuals with Systemic Lupus Erythematosus

Risk of Lupus Death According to Rural Urban Residence

VEGF, Neuregulin, and Postoperative Vasoplegia Following Cardiopulmonary Bypass Surgery

Background
Lung cancer is the leading cause of cancer deaths worldwide. The increasing use of minimally invasive surgical approaches has expanded the scope of treatment options for patients with lung cancer. However, these operations are not risk-free as there have been several reported cases of intraoperative catastrophes, with major hemorrhage from the pulmonary artery being the most common. The objective of this study was to develop a computer vision-based approach to reliably identify the pulmonary artery during robotic right lower lobectomies. 

Methods
Twelve patients with biopsy-proven Stage I non-small-cell lung cancer of the right lower lobe underwent robotic lobectomy with mediastinal lymph node dissection. Complete videos of each operation were obtained, and video fragments of the pulmonary artery were identified by two board-certified thoracic surgeons. Annotation masks of the pulmonary artery were then created using Computer Vision Annotation Tool, an open-source web-based annotation tool. The labeled data was next used to train a state-of-the-art instance segmentation algorithm called Mask Regional-Convolutional Neural Network (Mask R-CNN) using an 80:20 random sample split from ten cases for training and validation, respectively. Two cases were utilized for generalization testing. Three custom performance metrics commonly utilized in deep learning-based instance segmentation were used to evaluate our approach: Intersection over Union (IoU), Average Precision at IoU threshold of 50% (AP50) and at 75% (AP75). 

Results
Annotation masks of the pulmonary artery were created in 4,139 images across twelve cases of robotic right lower lobectomy. 2,893 and 684 annotated images across ten (83.3%) cases were used for training and validation, respectively; and 261 and 301 annotated images from two (16.7%) cases were used for generalization testing. A mean IoU of 87.7% was achieved in the validation dataset. The AP50 attained by our model was 96.7% and AP75 was 82.3%. In generalizability testing, when the model was tested on data never exposed to it, it was able to partially generalize with a mean IoU of 86.0%. 

Conclusion
Our study shows that our Mask R-CNN model was able to identify surgical anatomy during robotic lobectomy with high accuracy in the validation dataset. While still at an early stage, more variable labeled data and collaborative efforts are needed to improve the generalizability of our model. We envision such a computer vision system to be valuable in early surgeon training and incorporate future real-time augmentation of video feedback to improve outcomes.






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Revisiting Time Activity Curves in Breast MRI: Has it kept up with the times?

Next from 2023 AMA Research Challenge

Detection Rate of Prostate Cancer at Systematic Prostate Biopsy in Patients with Negative mp-MRI of the Prostate: A Retrospective Study