The VIGOR study was designed to evaluate the pathologic response of soft tissue ablated with pulsed electric fields (PEFs) in non-small cell lung cancer (NSCLC) patients who are candidates for surgical resection following standard of care (SOC) neoadjuvant use of checkpoint inhibitor treatment plus platinum doublet chemotherapy (NCT05583188). The safety of adding PEF to this pathway of care was also evaluated. The primary endpoint was the pathologic response. Secondary endpoints included the rate of R0 (complete) resection, as well as the frequency, duration, and causes of any surgery cancellations or delays. Exploratory endpoints included the profiling of circulating immunocytes post ablation by flow cytometry. The study enrolled 5 patients and PEF energy was successfully delivered to targeted lesions in the lung. No issues were observed when accessing the tumor for delivery of PEF energy, and no device-related serious adverse events (SAEs) were observed. All patients initiated neoadjuvant therapy as planned. Four of five patients underwent surgical resection. Pathological assessment was performed on resected tumors and revealed that out of the four surgical patients three were pathologic complete response (pCR) and one had major pathologic response (MPR). In summary, this study supports the safety and feasibility of PEF ablation in NSCLC patients prior to neoadjuvant treatment with immune checkpoint blockade plus platinum doublet chemotherapy and planned surgical resection.

Integration of AI-enabled algorithms into the radiology workflow presents a complex array of challenges that span operational, technical, clinical, and regulatory domains. Successfully overcoming these hurdles requires a multifaceted approach, including strategic planning, educational initiatives, and careful consideration of the practical implications for radiologists' workloads. Institutions must navigate these challenges with a clear understanding of the potential benefits and limitations of both vended and in-house developed AI tools.

This study aimed to perform temperature mapping during clinical ablations by leveraging the known relationship between computed tomography (CT) signal and temperature. First, the spectral CT signal was characterized as a function of temperature for soft tissue-mimicking and fat-mimicking materials across a wide range of temperatures in both frozen and heated states. Spectral CT images were acquired while fiber optic thermal sensors continuously recorded local temperatures, which were correlated with electron density changes. Substantially different material-specific thermal expansion coefficients and temperature dependencies were measured and well matched reported values. In patient images, effective atomic number images were used to segment soft tissue, fat, and bone. Electron density-temperature relationships for fat and soft tissue were used to generate temperature maps during microwave ablations and cryoablations. In vivo temperature maps correlated well with interventional radiologist expectations and demonstrated smooth transitions at fat/soft tissue interfaces.

BackgroundComputed tomography (CT) is routinely used to guide cryoablation procedures. Notably, CT-guidance provides 3D localization of cryoprobes and can be used to delineate frozen tissue during ablation. However, metal-induced artifacts from ablation probes can make accurate probe placement challenging and degrade the ice ball conspicuity, which in combination could lead to undertreatment of potentially curable lesions. PurposeIn this work, we propose an image-based neural network (CNN) model for metal artifact reduction for CT-guided interventional procedures. MethodsAn image domain metal artifact simulation framework was developed and validated for deep-learning-based metal artifact reduction for interventional oncology (MARIO). CT scans were acquired for 19 different cryoablation probe configurations. The probe configurations varied in the number of probes and the relative orientations. A combination of intensity thresholding and masking based on maximum intensity projections (MIPs) was used to segment both the probes only and probes + artifact in each phantom image. Each of the probe and probe + artifact images were then inserted into 19 unique patient exams, in the image domain, to simulate metal artifact appearance for CT-guided interventional oncology procedures. The resulting 361 pairs of simulated image volumes were partitioned into disjoint training and test datasets of 304 and 57 volumes, respectively. From the training partition, 116 600 image patches with a shape of 128 x 128 x 5 pixels were randomly extracted to be used for training data. The input images consisted of a superposition of the patient and probe + artifact images. The target images consisted of a superposition of the patient and probe only images. This dataset was used to optimize a U-Net type model. The trained model was then applied to 50 independent, previously unseen CT images obtained during renal cryoablations. Three board-certified radiologists with experience in CT-guided ablations performed a blinded review of the MARIO images. A total of 100 images (50 original, 50 MARIO processed) were assessed across different aspects of image quality on a 4-point likert-type item. Statistical analyses were performed using Wilcoxon signed-rank test for paired samples. ResultsReader scores were significantly higher for MARIO processed images compared to the original images across all metrics (all p < 0.001). The average scores of the overall image quality, iceball conspicuity, overall metal artifact, needle tip visualization, target region confidence, and worst metal artifact, needle tip visualization, iceball conspicuity, and target region confidence improved by 34.91%, 36.29%, 39.94%, 34.17%, 35.13%, and 45.70%, respectively. ConclusionsThe proposed method of image-based metal artifact simulation can be used to train a MARIO algorithm to effectively reduce probe-related metal artifacts in CT-guided cryoablation procedures.

Automated segmentation tools often encounter accuracy and adaptability issues when applied to images of different pathology. The purpose of this study is to explore the feasibility of building a workflow to efficiently route images to specifically trained segmentation models. By implementing a deep learning classifier to automatically classify the images and route them to appropriate segmentation models, we hope that our workflow can segment the images with different pathology accurately. The data we used in this study are 350 CT images from patients affected by polycystic liver disease and 350 CT images from patients presenting with liver metastases from colorectal cancer. All images had the liver manually segmented by trained imaging analysts. Our proposed adaptive segmentation workflow achieved a statistically significant improvement for the task of total liver segmentation compared to the generic single-segmentation model (non-parametric Wilcoxon signed rank test, n = 100, p-value << 0.001). This approach is applicable in a wide range of scenarios and should prove useful in clinical implementations of segmentation pipelines.

OBJECTIVES:Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent liver disorder in Western countries, with approximately 20%-30% of the MASLD patients progressing to severe stages. There is an urgent need for noninvasive, cost-effective, widely accessible, and precise biomarkers to evaluate liver steatosis. This study aims to assess and compare the diagnostic performance of a novel reference frequency method-based ultrasound attenuation coefficient estimation (ACE) in both fundamental (RFM-ACE-FI) and harmonic (RFM-ACE-HI) imaging for detecting and grading liver steatosis. METHODS:An Institutional Review Board-approved prospective study was carried out between December 2018 and October 2022. A total number of 130 subjects were enrolled in the study. The correlation between RFM-ACE-HI values and magnetic resonance imaging proton density fat fraction (MRI-PDFF), as well as between RFM-ACE-FI values and MRI-PDFF were calculated. The diagnostic performance of RFM-ACE-FI and RFM-ACE-HI was evaluated using receiver operating characteristic (ROC) curve analysis, as compared to MRI-PDFF. The reproducibility of RFM-ACE-HI was assessed by interobserver agreement between two sonographers. RESULTS:A strong correlation was observed between RFM-ACE-HI and MRI-PDFF, with R = 0.88 (95% confidence interval [CI]: 0.83-0.92; P < .001), while the correlation between RFM-ACE-FI and MRI-PDFF was R = 0.65 (95% CI: 0.50-0.76; P < .001). The area under the ROC (AUROC) curve for RFM-ACE-HI in staging liver steatosis grades of S ≥ 1 and S ≥ 2 was 0.97 (95% CI: 0.91-0.99; P < .001) and 0.98 (95% CI: 0.93-1.00; P < .001), respectively, and 0.76 (95% CI: 0.65-0.85) and 0.80 (95% CI: 0.70-0.88) for RFM-ACE-FI, respectively. Great reproducibility was achieved for RFM-ACE-HI, with an interobserver agreement of R = 0.97 (95% CI: 0.94-0.99; P < .001). CONCLUSIONS:The novel RFM-ACE-HI method offered high liver steatosis diagnostic accuracy and reproducibility, which has important clinical implications for early disease intervention and treatment evaluation.

Laboratory findings and timeline of treatments. Day 0 is the day of the initial consult at our institution. CRP, C-reactive protein; IgG, immunoglobulin G.

Computed tomography (CT) is routinely used to guide cryoablation procedures. Notably, CT-guidance provides 3D localization of cryoprobes and can be used to delineate frozen tissue during ablation. However, metal-induced artifacts from ablation probes can make accurate probe placement challenging and degrade the ice ball conspicuity, which in combination could lead to undertreatment of potentially curable lesions. An image domain metal artifact simulation framework was developed and validated for deep-learning-based metal artifact reduction for interventional oncology (MARIO). Metal probes and resulting artifacts were segmented from 19 phantom image sets and inserted into 19 different sets of patient CT images to simulate artifacts. This dataset was used to optimize a U-Net type model. Due to unique traits of probe artifacts, we employed custom augmentation techniques and loss functions for model optimization. An ablation study compared performance with and without these additional factors. The combined strategies improved quantitative metrics by 40.95% over baseline training. Augmentations also increased generalizability. Patient cases showed MARIO substantially reduced artifacts while preserving anatomical details. In a reader study, scores from three board-certified radiologists were significantly higher for MARIO processed images compared to the original images across all metrics (all p<0.0001).

BACKGROUND: Prolonged survival of patients with metastatic disease has furthered interest in metastasis-directed therapy (MDT). RESEARCH QUESTION: There is a paucity of data comparing lung MDT modalities. Do outcomes among sublobar resection (SLR), stereotactic body radiation therapy (SBRT), and percutaneous ablation (PA) for lung metastases vary in terms of local control and survival? STUDY DESIGN AND METHODS: Medical records of patients undergoing lung MDT at a single cancer center between January 2015 and December 2020 were reviewed. Overall survival, local progression, and toxicity outcomes were collected. Patient and lesion characteristics were used to generate multivariable models with propensity weighted analysis. RESULTS: Lung MDT courses (644 total: 243 SLR, 274 SBRT, 127 PA) delivered to 511 patients were included with a median follow-up of 22 months. There were 47 local progression events in 45 patients, and 159 patients died. Two-year overall survival and local progression were 80.3% and 63.3%, 83.8% and 9.6%, and 4.1% and 11.7% for SLR, SBRT, and PA, respectively. Lesion size per 1 cm was associated with worse overall survival (hazard ratio, 1.24; P = .003) and LP (hazard ratio, 1.50; P < .001). There was no difference in overall survival by modality. Relative to SLR, there was no difference in risk of local progression with PA; however, SBRT was associated with a decreased risk (hazard ratio, 0.26; P = .023). Rates of severe toxicity were low (2.1%-2.6%) and not different among groups. INTERPRETATION: This study performs a propensity weighted analysis of SLR, SBRT, and PA and shows no impact of lung MDT modality on overall survival. Given excellent local control across MDT options, a multidisciplinary approach is beneficial for patient triage and longitudinal management.

Background: Autonomously functioning thyroid nodules (AFTNs) constitute 5% to 7% of thyroid nodules and represent the second most common cause of hyperthyroidism following Graves' disease. Currently, radioactive iodine (RAI) and surgery are the standard treatment options, and both incur a risk of postprocedural hypothyroidism and other surgery and radiation-related complications. Methods: This work aimed at assessing the efficacy of radiofrequency ablation (RFA) as an alternative treatment option for resolving hyperthyroidism and the nodule volume rate reduction (VRR) and its associated adverse events. Results: A total of 22 patients underwent RFA for a solitary AFTN. Seventy-two percent (n = 16) had subclinical hyperthyroidism, 9% (n = 2) had overt hyperthyroidism, and 18% (n = 4) were biochemically euthyroid on antithyroid medication. Average pretreatment TSH was 0.41 mIU/L (SD = 0.98) and free T4 1.29 ng/dL (SD = 0.33). Following a single RFA session, hyperthyroidism resolved in 90.9% (n = 20) and average VRR (61.13%) was achieved within 3 to 6 months following the ablation. Except for 1 nodule, none of the nodules grew during the follow-up period (16.5 months). Two patients (9%) developed transient tachycardia requiring short-term beta-blocker therapy, and 2 developed mild hypothyroidism requiring levothyroxine therapy. Two patients developed recurrent hyperthyroidism and elected to undergo lobectomy and repeat RFA respectively. No serious adverse effects were noted in this cohort. Conclusion: RAI and/or surgery represent the standard of care for toxic adenomas, but RFA shows excellent efficacy and safety profile. Therefore, at centers with RFA expertise, it should be considered an alternative treatment strategy, avoiding radiation and surgery-related complications.

Abstract Disclosure: M. Dhanasekaran: None. A.A. Rajwani: None. M.R. Castro: None. J.C. Morris: None. J. Schmitz: None. R.A. Lee: None. M. Callstrom: None. M. Stan: None. Context: Autonomously functioning thyroid nodules (AFTNs) constitutes 5% of thyroid nodules and is the second most common cause of hyperthyroidism following Graves’ Disease. Untreated hyperthyroidism is associated with adverse cardiovascular and skeletal complications. Currently, radioactive iodine (RAI) and surgery are the standard treatment options for AFTNs, and both incur a risk of post-procedural hypothyroidism. To overcome this and other surgery/radiation-related complications, radiofrequency ablation (RFA) has been utilized in multiple countries (for both toxic and non-toxic thyroid nodules). It has been shown to induce significant nodule volume reduction along with restoration of normal thyroid function in many AFTNs. Methods: We present a single-center experience using RFA as an alternative treatment modality for AFTNs. The study's primary aim was to assess the efficacy of RFA in normalizing thyroid hormone concentration and restoring the euthyroid state. In addition, we analyzed the efficacy of RFA in nodule volume rate reduction (VRR) and its associated adverse events. Results: A total of 22 consecutive patients (17 F and 5 M) underwent RFA for a solitary AFTN (hot nodule in thyroid uptake and scan) under variable degrees of general anesthesia. 72% (n=16) had subclinical hyperthyroidism, 9% (n=2) had overt hyperthyroidism, and 18% (n=4) were biochemically euthyroid on anti-thyroid drugs (ATD). The mean age at the time of ablation was 52.09 years (SD= 14.6), with a mean BMI of 27.36 kg/m2 (SD= 4.67). Average pre-treatment TSH was 0.41 mIU/L (SD= 0.980) and free T4 1.29 ng/dl (SD= 0.33). The thyroid function was assessed after a single RFA session. TSH normalized in all patients within 3-6 months following the ablation. All four patients on ATD pre-treatment discontinued therapy within three months following the procedure. The average VRR (62.54%) was achieved within 3-6 months following the RFA, and importantly, none of the nodules grew back during the follow-up period (up to 24 months). Two patients (9%) developed transient tachycardia requiring short-term beta-blocker therapy, and two (9%) developed mild hypothyroidism requiring levothyroxine therapy. One patient, euthyroid post RFA, developed recurrent hyperthyroidism 45 months later and elected to undergo lobectomy. No serious adverse effects were noted in this cohort. Conclusions - RAI and/or surgery represent the standard of care for toxic adenomas but RFA shows excellent efficacy along with an excellent safety profile. Therefore at centers with RFA expertise it should be considered an alternative treatment strategy, avoiding radiation and surgery-related complications. Presentation Date: Saturday, June 17, 2023

OBJECTIVE:To evaluate the performance of an internally developed and previously validated artificial intelligence (AI) algorithm for magnetic resonance (MR)-derived total kidney volume (TKV) in autosomal dominant polycystic kidney disease (ADPKD) when implemented in clinical practice. PATIENTS AND METHODS:The study included adult patients with ADPKD seen by a nephrologist at our institution between November 2019 and January 2021 and undergoing an MR imaging examination as part of standard clinical care. Thirty-three nephrologists ordered MR imaging, requesting AI-based TKV calculation for 170 cases in these 161 unique patients. We tracked implementation and performance of the algorithm over 1 year. A radiologist and a radiology technologist reviewed all cases (N=170) for quality and accuracy. Manual editing of algorithm output occurred at radiology or radiology technologist discretion. Performance was assessed by comparing AI-based and manually edited segmentations via measures of similarity and dissimilarity to ensure expected performance. We analyzed ADPKD severity class assignment of algorithm-derived vs manually edited TKV to assess impact. RESULTS:Clinical implementation was successful. Artificial intelligence algorithm-based segmentation showed high levels of agreement and was noninferior to interobserver variability and other methods for determining TKV. Of manually edited cases (n=84), the AI-algorithm TKV output showed a small mean volume difference of -3.3%. Agreement for disease class between AI-based and manually edited segmentation was high (five cases differed). CONCLUSION:Performance of an AI algorithm in real-life clinical practice can be preserved if there is careful development and validation and if the implementation environment closely matches the development conditions.

PURPOSE:To evaluate the oncologic outcomes and adverse events associated with cryoablation of plasmacytomas.MATERIALS AND METHODS:Retrospective review of an institutional percutaneous ablation database showed that 43 patients underwent 46 percutaneous cryoablation procedures for treatment of 44 plasmacytomas between May 2004 and March 2021. The treatment of 25 (25 of 44, 56.8%) tumors was augmented with bone consolidation/cementoplasty. The median patient age was 64 years (interquartile range [IQR], 54-69), and 30 of 43 (69.8%) patients were men. The median maximum plasmacytoma diameter was 5.0 cm (IQR, 3.1-7.0). Thirty of 44 (68.2%) tumors were periacetabular, vertebral, or located in the iliac wing. Twenty-nine of 44 (65.9%) cryoablated plasmacytomas were recurrent tumors after prior external beam radiation therapy (EBRT). Survival analyses were performed using the Kaplan-Meier method. Adverse events were graded using Society of Interventional Radiology criteria.RESULTS:The 5-year estimated local tumor recurrence-free survival was 85.3% (95% CI, 74.1%-98.1%), the 5-year estimated new plasmacytoma-free survival was 49.9% (95% CI, 33.9%-73.4%), and the 5-year estimated overall survival was 70.4% (95% CI, 56.9%-87.1%). Nine of 46 (19.6%) major adverse events occurred in 8 patients, including 3 of 46 (6.5%) new or progressive pathologic fractures at the ablation site requiring surgical intervention, 3 of 46 (6.5%) nerve injuries, 1 of 46 (2.2%) avascular necrosis and femoral head collapse, 1 of 46 (2.2%) septic arthritis, and 1 of 46 (2.2%) acute renal failure caused by rhabdomyolysis.CONCLUSIONS:Percutaneous cryoablation is a viable treatment option for patients with plasmacytomas, including those with recurrent plasmacytomas after EBRT. Postcryoablation adverse events are relatively common.

This article aims to disclose a consensus on the rationale, approaches, and the outcomes of bone ablations in the peripheral skeleton. Despite less numerous prospective studies about peripheral metastasis, interventional radiology has a role in this setting. Scrupulous attention for selection criteria, ablation technique, procedural steps, and clinical and imaging follow-up are required to provide optimal multidisciplinary care for oncologic patients.

Background: Percutaneous ablation is an alternative treatment for lung cancer in non-operable patients. This is a prospective clinical trial for percutaneous microwave ablation (pMWA) of biopsy-proven lung cancer to demonstrate safety and efficacy. Methods: A prospective trial from 6-1-2016 to 1-1-2019 enrolled patients with biopsy-proven primary or metastatic lung cancer <3 cm in size and 1 cm away from the pleura for pMWA with the Emprint Ablation System with Thermosphere Technology for Phase I analysis, (Clinicaltrials.gov ; #NCT0267302). Patients were followed for 1 year with PET/CT and PET/MR to determine patterns of recurrence and efficacy of ablation. Results: After 12 patients consented for biopsy, 6 patients underwent treatment of 7 lesions, 3/6 women, median age of 67 (IQR, 65-70) years, BMI: 27.8 (IQR, 21.4-32.1) kg/m(2), lesion distance to pleura 24.4 (IQR, 13-38) mm, lesion size of 10.7 (IQR, 6-14) mm, and ablation duration time 5.9 (IQR, 3-10) minutes. pMWA were completed at 75 W. Twelve adverse events were reported (1 Grade 3, 3 Grade 2, and 8 Grade 1 events) with Grade 4 or 5 events. Mean % change after ablation in FEVI was -2% and DI,CO was -1%. After 2-3 months, the lesions would decrease in size, rim thickness, FDG activity, and T2 signal. FDG activity after 6 months was below blood pool in all cases. The ablation zones stabilized by 6-12 months. One patient expired during the study from pneumonia unrelated to ablation without local recurrence. Of the seven ablations during the 1 year followup, there was local tumor recurrence at 271 days following ablation at the apex of the ablation zone, subsequently successfully treated with percutaneous ayoablation (Cryo). Conclusions: pMWA appears to be a safe and effective mechanism for treatment of primary and secondary tumors of the lung, with possible preservation of pulmonary function.