Imaging Reporting Research Articles

Thyroid imaging reporting and data system with MRI morphological features for thyroid nodules: diagnostic performance and unnecessary biopsy rate

BackgroundTo assess MRI-based morphological features in improving the American College of Radiology Thyroid Imaging Reporting and Data System (ACR-TIRADS) for categorizing thyroid nodules.MethodsA retrospective analysis was performed on 728 thyroid nodules (453 benign and 275 malignant) that postoperative pathology confirmed. Univariate and multivariate logistic regression analyses were used to find independent predictors of MRI morphological features in benign and malignant thyroid nodules. The improved method involved increasing the ACR-TIRADS level by one when there are independent predictors of MRI-based morphological features, whether individually or in combination, and conversely decreasing it by one. The study compared the performance of conventional ACR-TIRADS and different improved versions.ResultsAmong the various MRI morphological features analyzed, restricted diffusion and reversed halo sign were determined to be significant independent risk factors for malignant thyroid nodules (OR = 45.1, 95% CI = 23.2–87.5, P < 0.001; OR = 38.0, 95% CI = 20.4–70.7, P < 0.001) and were subsequently included in the final assessment of performance. The areas under the receiver operating characteristic curves (AUCs) for both the conventional and four improved ACR-TIRADSs were 0.887 (95% CI: 0.861–0.909), 0.945 (95% CI: 0.926–0.961), 0.947 (95% CI: 0.928–0.962), 0.945 (95% CI: 0.926–0.961) and 0.951 (95% CI: 0.932–0.965), respectively. The unnecessary biopsy rates for the conventional and four improved ACR-TIRADSs were 62.8%, 30.0%, 27.1%, 26.8% and 29.1%, respectively, while the malignant missed diagnosis rates were 1.1%, 2.8%, 3.7%, 5.4% and 1.2%.ConclusionsMRI morphological features with ACR-TIRADS has improved diagnostic performance and reduce unnecessary biopsy rate while maintaining a low malignant missed diagnosis rate.

KPC-luciferase-expressing cells elicit an anti-tumor immune response in a mouse model of pancreatic cancer

Mouse models for the study of pancreatic ductal adenocarcinoma (PDAC) are well-established and representative of many key features observed in human PDAC. To monitor tumor growth, cancer cells that are implanted in mice are often transfected with reporter genes, such as firefly luciferase (Luc), enabling in vivo optical imaging over time. Since Luc can induce an immune response, we aimed to evaluate whether the expression of Luc could affect the growth of KPC tumors in mice by inducing immunogenicity. Although both cell lines, KPC and Luc transduced KPC (KPC-Luc), had the same proliferation rate, KPC-Luc tumors had significantly smaller sizes or were absent 13 days after orthotopic cell implantation, compared to KPC tumors. This coincided with the loss of bioluminescence signal over the tumor region. Immunophenotyping of blood and spleen from KPC-Luc tumor-bearing mice showed a decreased number of macrophages and CD4+ T cells, and an increased accumulation of natural killer (NK) cells in comparison to KPC tumor mice. Higher infiltration of CD8+ T cells was found in KPC-Luc tumors than in their controls. Moreover, the immune response against Luc peptide was stronger in splenocytes from mice implanted with KPC-Luc cells compared to those isolated from KPC wild-type mice, indicating increased immunogenicity elicited by the presence of Luc in the PDAC tumor cells. These results must be considered when evaluating the efficacy of anti-cancer therapies including immunotherapies in immunocompetent PDAC or other cancer mouse models that use Luc as a reporter for bioluminescence imaging.

Case Report: Sebaceous carcinoma of the eyelid

Sebaceous carcinoma is an extremely rare malignant disease and it is more aggressive when it occurs in the eyelids and orbit. It can mimic several benign lesions, resulting in diagnostic delay. We present a case of sebaceous carcinoma in a 50-year-old male who presented with complaints of swelling of the upper eyelid, which was followed by appearance of an ulcerative growth over the eyelid. Magnetic resonance imaging (MRI) reports showed an ulcerated mass in the left periorbital and orbital region appearing heterogeneously hyperintense. Fine needle aspiration cytology (FNAC) showed malignant epithelial differentiation which was followed by exenteration of the eyeball. Histopathology showed the rare diagnosis of sebaceous carcinoma. The disease has a poor prognosis as the entity is associated with increased morbidity and if not detected early it can metastasize to other organs which may be fatal sometimes.

Diagnosis of post-thrombotic syndrome: International union of phlebology (UIP) survey of medical specialists.

To review the current approaches to the diagnosis of Post-Thrombotic Syndrome (PTS) and to evaluate the potential need for a diagnostic tool. Medical specialists were invited to participate in an online survey of their current approaches to the diagnosis and management of PTS, including the use of scoring systems, diagnostic imaging techniques and the extent the practitioner reviews the patient's venous history. 502 participants completed the survey. Over 80% obtained imaging reports to confirm a history of deep vein thrombosis (DVT). 72% of participants always obtained an up-to-date duplex ultrasound for PTS diagnosis. Over 50% did not use a scoring system for either PTS diagnosis or management. 65% of the participants agreed that a new system for PTS diagnosis should be devised. Heterogeneity was observed in methods of diagnosing PTS by medical practitioners with frequent use of medical imaging studies and moderate use of scoring systems. Development of a new diagnostic tool for PTS should be considered for future studies.

Clinical impact of CEUS on non-characterizable observations and observations with intermediate probability of malignancy on CT/MRI in patients at risk for HCC

BackgroundHepatocellular carcinoma (HCC) is a unique cancer allowing tumor diagnosis with identification of definitive patterns of enhancement on contrast-enhanced imaging, avoiding invasive biopsy. However, it is still unclear to what extent Contrast-Enhanced Ultrasound (CEUS) is a clinically useful additional step when Computed tomography (CT) or Magnetic resonance imaging (MRI) are inconclusive.MethodsA prospective international multicenter validation study for CEUS Liver Imaging Reporting and Data System (LI-RADS) was conducted between January 2018 and August 2021. 646 patients at risk for HCC with focal liver lesions were enrolled. CEUS was performed using an intravenous ultrasound contrast agent within 4 weeks of CT/MRI. Liver nodules were categorized based on LI-RADS (LR) criteria. Histology or one-year follow-up CT/MRI imaging results were used as the reference standard. The diagnostic performance of CEUS was evaluated for inconclusive CT/MRI scan in two scenarios for which the AASLD recommends repeat imaging or imaging follow-up: observations deemed non-characterizable (LR-NC) or with indeterminate probability of malignancy (LR-3).Results75 observations on CT or MRI were categorized as LR-3 (n = 54) or LR-NC (n = 21) CEUS recategorization of such observations into a different LR category (namely, into one among LR-1, LR-2, LR-5, LR-M, or LR-TIV) resulted in management recommendation changes in 33.3% (25/75) and in all but one (96.0%, 24/25) observation, the new management recommendations were correct.ConclusionCEUS LI-RADS resulted in management recommendations change in substantial number of liver observations with initial indeterminate CT/MRI characterization, identifying both non-malignant lesions and HCC, potentially accelerating the diagnostic process and alleviating the need for biopsy or follow-up imaging.ClinicalTrials.gov number, NCT03318380.

Evaluation of DNA minicircles for delivery of adenine and cytosine base editors using activatable gene on “GO” reporter imaging systems

Over 30,000 point mutations are associated with debilitating diseases, including many cancer types, underscoring a critical need for targeted genomic solutions. CRISPR base editors, like adenine base editors (ABEs) and cytosine base editors (CBEs), enable precise modifications by converting adenine to guanine and cytosine to thymine, respectively. Challenges in efficiency and safety concerns regarding viral vectors used in delivery limit the scope of base editing. This study introduces non-viral minicircles, bacterial-backbone-free plasmids, as a delivery vehicle for ABEs and CBEs. The research uses cells engineered with the "Gene On" (GO) reporter gene systems for tracking minicircle-delivered ABEs, CBEs, or Cas9 nickase (control), using green fluorescent protein (GFPGO), bioluminescence reporter firefly luciferase (LUCGO), or a highly sensitive Akaluciferase (AkalucGO) designed in this study. The results show that transfection of minicircles expressing CBE or ABE resulted in significantly higher GFP expression and luminescence signals over controls, with minicircles demonstrating the most substantial editing. This study presents minicircles as a new strategy for base editor delivery and develops anenhanced bioluminescence imaging reporter system for tracking ABE activity. Future studies aim to evaluate the use of minicircles in preclinical cancer models, facilitating potential clinical applications.

Prediction of Follicular Thyroid Neoplasm and Malignancy of Follicular Thyroid Neoplasm Using Multiparametric MRI.

The study aims to evaluate multiparametric magnetic resonance imaging (MRI) for differentiating Follicular thyroid neoplasm (FTN) from non-FTN and malignant FTN (MFTN) from benign FTN (BFTN). We retrospectively analyzed 702 postoperatively confirmed thyroid nodules, and divided them into training (n = 482) and validation (n = 220) cohorts. The 133 FTNs were further split into BFTN (n = 116) and MFTN (n = 17) groups. Employing univariate and multivariate logistic regression, we identified independent predictors of FTN and MFTN, and subsequently develop a nomogram for FTN and a risk score system (RSS) for MFTN prediction. We assessed performance of nomogram through its discrimination, calibration, and clinical utility. The diagnostic performance of the RSS for MFTN was further compared with the performance of the Thyroid Imaging Reporting and Data System (TIRADS). The nomogram, integrating independent predictors, demonstrated robust discrimination and calibration in differentiating FTN from non-FTN in both training cohort (AUC = 0.947, Hosmer-Lemeshow P = 0.698) and validation cohort (AUC = 0.927, Hosmer-Lemeshow P = 0.088). Key risk factors for differentiating MFTN from BFTN included tumor size, restricted diffusion, and cystic degeneration. The AUC of the RSS for MFTN prediction was 0.902 (95% CI 0.798-0.971), outperforming five TIRADS with a sensitivity of 73.3%, specificity of 95.1%, accuracy of 92.4%, and positive and negative predictive values of 68.8% and 96.1%, respectively, at the optimal cutoff. MRI-based models demonstrate excellent diagnostic performance for preoperative predicting of FTN and MFTN, potentially guiding clinicians in optimizing therapeutic decision-making.

Biparametric versus multiparametric MRI for the detection of clinically significant prostate cancer in a diverse, multiethnic population

PurposeThere is not yet satisfactory performance data comparing multiparametric MRI (mpMRI) versus biparametric MRI (bpMRI) for detecting prostate cancer (PCa), particularly in high-risk populations. We compared both protocols for detecting overall PCa and clinically significant PCa (CS-PCa; defined as Grade Group ≥ 2) in a multiethnic urban population.MethodsWe retrospectively reviewed electronic medical record data from men who underwent image-guided fusion prostate biopsy (FB) between 2016 and 2021 at our institution. Patient characteristics, Prostate Imaging Reporting and Data System (PI-RADS) scores, and FB outcomes were analyzed based on MRI protocol. Multivariate mixed-effects logistic regression models were used to examine associations of bpMRI versus mpMRI for detecting overall PCa and CS-PCa in targeted lesions, among all patients and stratified by race/ethnicity.ResultsOverall, 566 men (44.0% Non-Hispanic Black [NHB]; 27.0% Hispanic) with 975 PI-RADS 3–5 lesions on MRI underwent FB. Of these, 312 (55%) men with 497 lesions underwent mpMRI and 254 (45%) men with 478 lesions underwent bpMRI. On multivariate analyses among all men, the odds of detecting overall PCa (OR = 1.18, 95% CI: 1.05–3.11, p = 0.031) and CS-PCa (OR = 2.15, 95% CI: 1.16–4.00, p = 0.014) on FB were higher for lesions identified on bpMRI than mpMRI. When stratified by race/ethnicity, the odds of detecting overall PCa (OR = 1.86; p = 0.15) and CS-PCa (OR = 2.20; p = 0.06) were not statistically different between lesions detected on bpMRI or mpMRI.ConclusionBpMRI has similar diagnostic performance to mpMRI in detecting overall and CS-PCa within a racially/ethnically diverse population. BpMRI can be utilized for evaluating suspected CS-PCa among NHB and Hispanic men.

Lifetime Health and Economic Outcomes of Biparametric Magnetic Resonance Imaging as First-Line Screening for Prostate Cancer : A Decision Model Analysis.

Contemporary prostate cancer (PCa) screening uses first-line prostate-specific antigen (PSA) testing, possibly followed by multiparametric magnetic resonance imaging (mpMRI) for men with elevated PSA levels. First-line biparametric MRI (bpMRI) screening has been proposed as an alternative. To evaluate the comparative effectiveness and cost-effectiveness of first-line bpMRI versus PSA-based screening. Decision analysis using a microsimulation model. Surveillance, Epidemiology, and End Results database; randomized trials. U.S. men aged 55 years with no prior screening or PCa diagnosis. Lifetime. U.S. health care system. Biennial screening to age 69 years using first-line PSA testing (test-positive threshold, 4 µg/L) with or without second-line mpMRI or first-line bpMRI (test-positive threshold, PI-RADS [Prostate Imaging Reporting and Data System] 3 to 5 or 4 to 5), followed by biopsy guided by MRI or MRI plus transrectal ultrasonography. Screening tests, biopsies, diagnoses, overdiagnoses, treatments, PCa deaths, quality-adjusted and unadjusted life-years saved, and costs. For 1000 men, first-line bpMRI versus first-line PSA testing prevented 2 to 3 PCa deaths and added 10 to 30 life-years (4 to 11 days per person) but increased the number of biopsies by 1506 to 4174 and the number of overdiagnoses by 38 to 124 depending on the biopsy imaging scheme. At conventional cost-effectiveness thresholds, first-line PSA testing with mpMRI followed by either biopsy approach for PI-RADS 4 to 5 produced the greatest net monetary benefits. First-line PSA testing remained more cost-effective even if bpMRI was free, all men with low-risk PCa underwent surveillance, or screening was quadrennial. Performance of first-line bpMRI was based on second-line mpMRI data. Decision analysis suggests that comparative effectiveness and cost-effectiveness of PCa screening are driven by false-positive results and overdiagnoses, favoring first-line PSA testing with mpMRI over first-line bpMRI. National Cancer Institute.

Prostate health index density aids the diagnosis of prostate cancer detected using magnetic resonance imaging targeted prostate biopsy in Taiwanese multicenter study.

Multiparametric magnetic resonance imaging (mpMRI) followed by MRI-targeted prostate biopsy is the current standard for diagnosing prostate cancer (PCa). However, studies evaluating the value of biomarkers, including prostate health index (PHI) and its derivatives using this method are limited. We aimed to investigate the efficacy of PHI density (PHID) in guiding MRI-targeted prostate biopsies to identify clinically significant PCas (csPCa). The multicenter prospectively registered prostate biopsy database from three medical centers in Taiwan included patients with PHI and MRI-targeted and/or systematic prostate biopsies. We assessed the required values of prostate-specific antigen (PSA), prostate volume, PHI, PHID, and Prostate Imaging Reporting & Data System (PI-RADS) score using multivariable analyses, receiver operating characteristic curve analysis, and decision curve analyses (DCA). csPCa was defined as the International Society of Urological Pathology Gleason group ≥2 PCa, with an emphasis on reducing unwarranted biopsies. The study cohort comprised 420 individuals. Diagnoses of PCa and csPCa were confirmed in 62.4% and 47.9% of the participants, respectively. The csPCa diagnosis rates were increased with increasing PI-RADS scores (20.5%, 44.2%, and 73.1% for scores 3, 4, and 5, respectively). Independent predictors for csPCa detection included PHI, prostate volume, and PI-RADS scores of 4 and 5 in multivariable analyses. The area under the curve (AUC) for csPCa of PHID (0.815) or PHI (0.788) was superior to that of PSA density (0.746) and PSA (0.635) in the entire cohort, and the superiority of PHID (0.758) was observed in PI-RADS 3 lesions. DCA revealed that PHID achieved the best net clinical benefit in PI-RADS 3-5 and 4/5 cases. Among PI-RADS 3 lesions, cutoff values of PHID 0.70 and 0.43 could eliminate 51.8% and 30.4% of omitted biopsies, respectively. PHI-derived biomarkers, including PHID, performed better than other PSA-derived biomarkers in diagnosing PCa in MRI-detected lesions.

Research

The June 2024 Research Roundup360 looks at: Do the associations of daily steps with mortality and incident cardiovascular disease differ by sedentary time levels?; Large-scale assessment of ChatGPT in benign and malignant bone tumours imaging report diagnosis and its potential for clinical applications; Long-term effects of diffuse idiopathic skeletal hyperostosis on physical function: a longitudinal analysis; Effect of intramuscular fat in the thigh muscles on muscle architecture and physical performance in the middle-aged females with knee osteoarthritis; Preoperative package of care for osteoarthritis an opportunity not to be missed?; Superiority of kinematic alignment over mechanical alignment in total knee arthroplasty during medium- to long-term follow-up: a meta-analysis and trial sequential analysis.

Shareable artificial intelligence to extract cancer outcomes from electronic health records.

11000 Background: Clinical outcomes such as response, progression, and metastasis represent crucial data for observational cancer research, but outside of clinical trials, such outcomes are usually recorded only in unstructured notes in electronic health records (EHRs). Manual EHR annotation is too resource-intensive to scale to large datasets. Individual cancer centers have trained artificial intelligence natural language processing (AI/NLP) models to extract outcomes from their EHRs. However, due to concerns that models trained on protected health information (PHI) might encode private data, such models usually cannot be exported to other centers. Methods: EHR data from Dana-Farber Cancer Institute (DFCI) and Memorial-Sloan Kettering (MSK) collected through the AACR Project GENIE Biopharma Collaborative were used to train and evaluate Bidirectional Encoder Representations from Transformers (BERT)-based NLP models to extract outcomes from imaging reports and oncologist notes annotated with the Pathology, Radiology/Imaging, Signs/Symptoms, Medical oncologist, and bioMarkers (PRISSMM) framework. Document-level outcomes included the presence of active cancer; response; progression; and metastatic sites. ‘Teacher’ models trained on DFCI EHR data were used to label imaging reports and discharge summaries from the public MIMIC-IV dataset. ‘Student’ models trained to use MIMIC documents to predict teacher labels were transferred to MSK for evaluation. Results: Teacher models were trained at DFCI on 30,332 imaging reports for 2609 patients and 32,173 oncologist notes for 2917 patients with non-small cell lung, colorectal, breast, prostate, pancreatic, or urothelial cancer. The models were used to label 217,642 imaging reports and 141,377 discharge summaries from MIMIC for student model training. These DFCI-trained student models were evaluated at MSK, demonstrating high discrimination (AUROC &gt; 0.90) across outcomes. Conclusions: This privacy-preserving “teacher-student” AI/NLP framework could expedite linkage of genomic data to clinical outcomes across institutions, accelerating precision cancer research. [Table: see text]

A rapid assessment tool for systemic treatment outcomes in colorectal cancer with deep bidirectional transformers.

e15567 Background: Retrospective investigations involving cancer treatment encounter the challenge of manually reviewing voluminous imaging reports to identify the best responses and the timing of disease progression. Here, we employed natural language processing, specifically deep bidirectional transformers, to automate the extraction of treatment response data. Methods: Data were sourced from the Yonsei Cancer Data Library database, focusing on patients with stage II-IV colorectal cancer at the Yonsei Cancer Center from Jan 1, 2010, to Dec 31, 2020. Imaging reports from 6,574 patients were gathered, amounting to 97,119 CT readings. Among these, 9,000 CT reports corresponding to 2,859 patients were randomly subjected to multilabel manual labeling by four radiology experts, based on the RECIST version 1.1 classification (CR/NED, PR, SD, PD). The pretrained BERT-base-uncased model was employed and fine-tuned for the downstream tasks of multilabel classification. 6,765 reports were used for training, while the remaining 1,000 reports were divided equally between the validation and test sets. Additionally, an algorithm for integrating and extracting treatment response data was also implemented. Clinical data were meticulously collected for 47 patients with stage IV early-onset colorectal cancer (EOCRC) receiving palliative first-line chemotherapy. The primary objective was to evaluate the model’s accuracy in predicting the timing of disease progression events within a ±30-day window. Secondary objectives focused on the model’s ability to identify the best response and its timing within a ±45-day window. Results: The evaluation of the classification accuracy across 1,000 individual CT reports, categorized as CR/NED (319), PR (86), SD (272), and PD (298), revealed accuracy with an AUROC of 0.956 and an F1 score of 0.823. All EOCRC patients were initially diagnosed with stage IV disease, and 45 out of 47 (95.7%) underwent metastasectomy either before initiating chemotherapy or during the first-line chemotherapy treatment. In clinical evaluation, the model demonstrated 72.3% (95% Confidence Interval [CI], 59.5-85.1) accuracy in predicting the day of disease progression within a ±30-day window. It achieved 55.3% (95% CI, 41.1-69.5) accuracy in predicting the best response category and its timing within ±45-days. Notably, the model was more accurate in predicting CR/NED at 72% compared to SD and PR, which had accuracy of 27.3% and 15.4%, respectively. Conclusions: Our model demonstrated high performance in classifying CT reports, which is expected to provide rapid insights into patient progress and improve clinical decision-making. However, the complexity involved in integrating and extracting data result in slight constraints in performance. This emphasizes the need for further research into multimodal large language models that can integrate a wider variety of clinical data.

Novel approach to implementing natural language processing for clinical staging of non-small-cell lung cancer.

e13624 Background: Cancer staging is instrumental in driving clinical management and trial enrollment, but staging data are generally unreliable and unstructured in the electronic health record (EHR). Advances in natural language processing (NLP) may facilitate clinical staging and documentation [1], but challenges to real-world implementation include (1) automatically identifying appropriate patients and reports from the EHR and (2) developing an unbiased dataset for training and validation [2]. We describe our institution’s novel approach to overcome these barriers while building an in-house NLP pipeline for clinical tumor staging of non-small-cell lung cancer (NSCLC). Methods: We identified patients by searching our EHR (Epic) for a molecular analysis test ordered specifically for pathological diagnoses of NSCLC at our institution. We used the test order date as the diagnosis proxy date (DPD). For each patient, we extracted imaging reports up to 16 weeks before and 6 weeks after the DPD. To derive primary tumor size, we analyzed the CT Chest or PET/CT report closest to the DPD using an oncology-trained NLP text extraction and labeling tool (John Snow Labs). We cleaned all extracted tumor size entities and identified the largest measurement linked to the lungs. We compared primary tumor measurements from the NLP pipeline to those in a preexisting, manually compiled cancer registry (CNEXT). We manually analyzed discrepancies through chart review. Results: 542 patients with a DPD between 11/2016 - 9/2023 were processed through the NLP pipeline. Of 443 patients with valid values in both the pipeline and CNEXT, 53% (234) were exact matches, and 20% (90) had a close match (within 0-5mm), yielding a 73% accuracy rate for values within 5mm. When mismatched values were manually reviewed, several cases in CNEXT were found to have a DPD differing by more than 3 months and tumor sizes derived from external reports. When these cases were excluded, 320 of the remaining 349 patients had valid values in both the pipeline and the updated manual review. In this refined population, 66% (213) were exact matches, and 15% (48) had a close match, yielding an 82% accuracy rate for values within 5mm. Conclusions: To our knowledge, this is the first report of a pathology-based method to automatically and reliably identify patients with NSCLC and their relevant imaging reports directly from the EHR. We used a prebuilt NLP tool to derive primary tumor sizes with relatively high accuracy and found that adding flags for timeline discrepancies and external reports can further improve validity. As we near completion of analogous pipelines for node and metastasis staging, we will develop methodology to identify subgroups of patients that can be clinically staged with near-perfect accuracy, ultimately aiming to substantially limit manual staging of uncomplicated cases. 1. Puts 2023. 2. Wang 2022.

Immune checkpoint inhibitor-associated gastrointestinal adverse events in patients with colorectal cancer.

e14708 Background: Immune checkpoint inhibitors (ICI) are successfully used to treat microsatellite instability-high (MSI-H) tumors. While immune checkpoint inhibitor related colitis is a frequent and devastating immune related adverse event (irAE) of these agents, the incidence and characteristics of this inflammatory toxicity in patients with MSI-H colorectal cancers has not been examined. We aimed to describe the characteristics and clinical profile of patients diagnosed with luminal gastrointestinal irAE in patients treated with ICI for colorectal cancer in a tertiary cancer care center. Methods: This is a retrospective analysis that included adult cancer patients diagnosed with colorectal cancer that received ICI between 6/1/2014 and 12/31/2022. We report data on those that developed colitis as an irAE up to 3 months after the last dose of ICI confirmed by laboratory and/or imaging report. We included patients’ demographic characteristics, oncologic profile and outcomes as well as clinical course, endoscopic features as well as treatment and outcomes in terms of luminal gastrointestinal irAEs. Results: Out of 474 patients with colorectal cancer on ICI in our study period, only 18 developed a gastrointestinal irAE with an incidence of 3.8%. Patients were primarily Caucasian (88.8%) males (61.1%) with a median age of 69.5 years. The majority of these patients received combination therapy with anti-PD1/L1 and CTLA-4 (50%). 66.6 % received ICI for MSI-H colorectal cancer. 11.1% of our sample were noted to have a second cancer-melanoma. The major-ity of patients had grade 1-2 colitis (61.2%) and grade 1-2 diarrhea (88.8%). Only 5 patients underwent endoscopic evaluation of whom, 2 had ulcerative inflammation necessitating use of selective immunosuppressive therapy with biologics. 61.1% had to withhold cancer treatment due toxicity. With regards to other gastrointestinal irAEs among this population, 41.4% and 5.8% were noted to have liver and pancreas toxicity respectively, with a median CTCAE grade of severity 2. The most common treatment for these toxicities were steroids. Conclusions: Luminal gastrointestinal irAEs seem to occur less frequently and at a lower severity among patients with MSI-H colorectal cancer after checkpoint inhibitors exposure compared to the overall incidence of the same among other cancers reported in literature. Larger prospective studies are necessary to determine the role of tumor biology and the gut microbiome in the disease profile and severity of immune related adverse events of the GI organ system. [Table: see text]

Disrupting how we recruit to cancer clinical trials.

11072 Background: Traditional methods to identify eligible patients for cancer clinical trials rely heavily on manual review, a time-consuming bottle neck limiting access to novel treatments, particularly for underserved populations. This study presents an automated informatics platform designed to simplify and streamline patient identification and trial matching. Methods: Our platform leverages three tools: 1. Parser:Extracts and categorizes trial data based on cancer type, stage, and receptor status from the National Cancer Institute's ClinicalTrials.gov database, storing it in a structured JSON format; 2. Screener: Utilizes Epic Clarity electronic health record data to identify upcoming patients approaching treatment decision points, times when clinical trials are more relevant. Patients are classified as "newly diagnosed" or "potentially progressed" based on progress notes and imaging reports. Eligibility criteria, including stage and receptor status, are assessed using regular expressions; 3. Matcher: Pairs eligible patients with relevant trials based on compatible cancer stage and receptor status. One Cancer Center (CC) is prospectively using the platform to identify patients. The 2nd CC is refining the code using retrospective data. Accuracy was measured comparing automated to manual review by experienced trained abstractors. Results: Implementation across two cancer centers yielded: 1. Reduced manual review burden: Between June 2023 – Jan 2024, of 674 breast cancer patients seen at CC #1, 371 were new patients (N=371) and thus, at a treatment decision point; 3 did not undergo imaging. Of the 300 established patients undergoing imaging studies, the algorithm identified 50/300 (17%) scans as “positive,” and 61 (20%) with mixed disease progression/ regression, requiring manual review and trial matching. 189 scans were read as “negative”: 96% True Negatives; 4% were False Negatives. Automated screening reduced manual review from 300 to 111 patients, significantly alleviating workload on healthcare personnel. 2. Variable staging accuracy: While receptor status classification proved effective, stage accuracy varied between centers, highlighting a need for further refinement in this area. 3. Accurate receptor status classification: The system achieved high accuracy in demonstrating reliable assessment of this vital factor. Conclusions: This automated informatics platform demonstrates significant potential to streamline case identification for cancer clinical trials and thus, foster broader access to novel therapies. Its adaptability makes it suitable for implementation across diverse healthcare settings, empowering wider participation in advancements in cancer care. Ongoing efforts to refine the staging module are underway. Clinical trial information: NCT05146297 . [Table: see text]

Comparison of Positive Predictive Values of Biparametric MRI and Multiparametric MRI-directed Transrectal US-guided Targeted Prostate Biopsy.

Background Biparametric MRI (bpMRI) of the prostate is an alternative to multiparametric MRI (mpMRI), with lower cost and increased accessibility. Studies investigating the positive predictive value (PPV) of bpMRI-directed compared with mpMRI-directed targeted biopsy are lacking in the literature. Purpose To compare the PPVs of bpMRI-directed and mpMRI-directed targeted prostate biopsies. Materials and Methods This retrospective cross-sectional study evaluated men who underwent bpMRI-directed or mpMRI-directed transrectal US (TRUS)-guided targeted prostate biopsy at a single institution from January 2015 to December 2022. The PPVs for any prostate cancer (PCa) and clinically significant PCa (International Society of Urological Pathology grade ≥2) were calculated for bpMRI and mpMRI using mixed-effects logistic regression modeling. Results A total of 1538 patients (mean age, 67 years ± 8 [SD]) with 1860 lesions underwent bpMRI-directed (55%, 849 of 1538) or mpMRI-directed (45%, 689 of 1538) prostate biopsy. When adjusted for the number of lesions and Prostate Imaging Reporting and Data System (PI-RADS) score, there was no difference in PPVs for any PCa or clinically significant PCa (P = .61 and .97, respectively) with bpMRI-directed (55% [95% CI: 51, 59] and 34% [95% CI: 30, 38], respectively) or mpMRI-directed (56% [95% CI: 52, 61] and 34% [95% CI: 30, 39], respectively) TRUS-guided targeted biopsy. PPVs for any PCa and clinically significant PCa stratified according to clinical indication were as follows: biopsy-naive men, 64% (95% CI: 59, 69) and 43% (95% CI: 39, 48) for bpMRI, 67% (95% CI: 59, 75) and 51% (95% CI: 43, 59) for mpMRI (P = .65 and .26, respectively); and active surveillance, 59% (95% CI: 49, 69) and 30% (95% CI: 22, 39) for bpMRI, 73% (95% CI: 65, 89) and 38% (95% CI: 31, 47) for mpMRI (P = .04 and .23, respectively). Conclusion There was no evidence of a difference in PPV for clinically significant PCa between bpMRI- and mpMRI-directed TRUS-guided targeted biopsy. © RSNA, 2024 Supplemental material is available for this article.

PT29 A Methodologic Solution to Missing Deauville Scores Using Imaging Report Data to Classify Lymphoma Treatment Response in Real-World Data

PT29 A Methodologic Solution to Missing Deauville Scores Using Imaging Report Data to Classify Lymphoma Treatment Response in Real-World Data

Opportunities for change and levelling up: a trust wide retrospective analysis of 8 years of laparoscopic and abdominal myomectomy.

Laparoscopic myomectomy is increasingly considered the gold standard uterine preserving procedure and has well documented benefits over the open approach. Barriers that women have in accessing the most appropriate treatment need to be addressed to ensure optimal patient care and outcomes. To analyse rates of open and laparoscopic myomectomy at a large NHS trust and identify how many cases could potentially have been performed laparoscopically, and any variation between sites. A retrospective review of preoperative imaging reports and a surgical database containing information for all myomectomies performed between 1st January 2015 and 31st December 2022. Number of procedures suitable for alternative surgical approach; length of hospital stay; estimated blood loss; cost differences. 846 myomectomies were performed; 656 by laparotomy and 190 by laparoscopy. 194/591 (32.8%) open myomectomies could have been performed laparoscopically and 26/172 (15.1%) laparoscopic myomectomies may have been better performed via an open approach. Length of hospital stay, and estimated blood loss were significantly higher in the open group. Had cases been performed as indicated by pre-operative imaging, the cost differences ranged from -£115,752 to £251,832. There is disparity in access to the gold standard care of laparoscopic myomectomy. Due to multifactorial reasons, even at sites where the rate of laparoscopic myomectomy is high, there is still underutilisation of this approach. It is clear that there is scope for change and "levelling up" of this imbalance. Robust pathways and guidelines must be developed, and more laparoscopic surgeons should be trained to optimise care for women with fibroids.

Molecular Breast Imaging Biopsy with a Dual-Detector System.

Purpose To develop a molecular breast imaging (MBI)-guided biopsy system using dual-detector MBI and to perform initial testing in participants. Materials and Methods The Stereo Navigator MBI Accessory biopsy system comprises a lower detector, upper fenestrated compression paddle, and upper detector. The upper detector retracts, allowing craniocaudal, oblique, or medial or lateral biopsy approaches. The compression paddle allows insertion of a needle guide and needle. Lesion depth is calculated by triangulation of lesion location on the upper detector at 0° and 15° and relative lesion activity on upper and lower detectors. In a prospective study (July 2022-June 2023), participants with Breast Imaging Reporting and Data System category 2, 3, 4, or 5 breast lesions underwent MBI-guided biopsy. After injection of 740 MBq technetium 99m sestamibi, craniocaudal and mediolateral oblique MBI (2-minute acquisition per view) confirmed lesion visualization. A region of interest over the lesion permitted depth calculation in the system software. Upper detector retraction allowed biopsy device placement. Specimen images were obtained on the retracted upper detector, confirming sampling of the target. Results Of 21 participants enrolled (mean age, 50.6 years ± 10.1 [SD]; 21 [100%] women), 17 underwent MBI-guided biopsy with concordant pathology. No lesion was observed at the time of biopsy in four participants. Average lesion size was 17 mm (range, 6-38 mm). Average procedure time, including preprocedure imaging, was 55 minutes ± 13 (range, 38-90 minutes). Pathology results included invasive ductal carcinoma (n = 1), fibroadenoma (n = 4), pseudoangiomatous stromal hyperplasia (n = 6), and fibrocystic changes (n = 6). Conclusion MBI-guided biopsy using a dual-head system with retractable upper detector head was feasible, well tolerated, and efficient. Keywords: Breast Biopsy, Molecular Breast Imaging, Image-guided Biopsy, Molecular Breast Imaging-guided Biopsy, Breast Cancer Clinical trial registration no. NCT06058650 © RSNA, 2024.