Detection Of Liver Metastases Research Articles

Clinical performance of a simulated abbreviated liver MRI in combination with contrast enhanced CT for the baseline evaluation of the liver in patients with colorectal cancer

ObjectivesTo assess the diagnostic accuracy and inter-reader agreement of a simulated abbreviated gadoxetate liver MRI protocol together with CE-CT against a standard gadoxetate MRI for the detection of colorectal liver metastases at baseline. MethodsThree readers independently evaluated two sets of images per patient, recording number and location of metastases and benign lesions. Set 1 comprised T1w, T2w, DWI, multiphase CE-T1w and HPB images (standard). Set 2 included T2w, HBP, DWI (from Set 1) and CE-CT (simulated abbreviated). Diagnostic performance was compared using McNemar’s test. Level of agreement between sets 1 and 2 was determined with Cohen kappa. For agreement in the number of benign lesions and metastases, we applied ICC. Results75 patients (245 metastases, 122 benign lesions) were evaluated. There was no significant difference in diagnostic accuracy between set 1 and 2 for each reader (mean P=0.74). The total number of metastases and benign lesions showed high agreement between reading set 1 and 2 (κ = 0.81, 0.78). The total number of metastases showed substantial agreement between readers for set 1 and 2 (ICC = 0.99, 0.99). Good agreement was seen for metastatic segmental involvement (κ = 0.84–0.99). ConclusionsAt baseline, using a simulated abbreviated liver MRI together with CE-CT showed excellent agreement with standard MRI protocol for liver metastasis detection.

Head-to-Head Comparison of the Diagnostic Performance of FDG PET/CT and FDG PET/MRI in Patients With Cancer: A Systematic Review and Meta-Analysis.

BACKGROUND. The available evidence on the use of FDG PET/MRI performed using an integrated system in patients with cancer has grown substantially. OBJECTIVE. The purpose of this study was to perform a systematic review and meta-analysis comparing the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer. EVIDENCE ACQUISITION. MEDLINE, Embase, and the Cochrane Database of Systematic Reviews were searched for studies reporting a head-to-head comparison of the diagnostic performance of FDG PET/CT and FDG PET/MRI in patients with cancer from July 1, 2015, to January 25, 2023. The two modalities' diagnostic performance was summarized, stratified by performance end point. For end points with sufficient data, a meta-analysis was performed using bivariate modeling to produce summary estimates of pooled sensitivity and specificity. For the remaining end points, reported performance in individual studies was recorded. EVIDENCE SYNTHESIS. The systematic review included 29 studies with a total of 1656 patients. For patient-level detection of regional nodal metastases (five studies), pooled sensitivity and specificity for PET/MRI were 88% (95% CI, 74-95%) and 92% (95% CI, 71-98%), respectively, and for PET/CT were 86% (95% CI, 70-94%) and 86% (95% CI, 68-95%). For lesion-level detection of recurrence and/or metastases (five studies), pooled sensitivity and specificity for PET/MRI were 94% (95% CI, 78-99%) and 83% (95% CI, 76-88%), respectively, and for PET/CT were 91% (95% CI, 77-96%) and 81% (95% CI, 72-88%). In individual studies not included in the meta-analysis, PET/MRI in comparison with PET/CT showed staging accuracy in breast cancer of 98.0% versus 74.5% and in colorectal cancer of 96.2% versus 69.2%; sensitivity for primary tumor detection in cervical cancer of 93.2% versus 66.2%; and sensitivity, specificity, and accuracy for lesion-level liver metastasis detection of 91.1-98.0% versus 42.3-71.1%, 100.0% versus 83.3-98.6%, and 96.5-98.2% versus 44.7-86.7%, respectively. In three studies, management was more commonly impacted by information from PET/MRI (5.2-11.1%) than PET/CT (0.0-2.6%). CONCLUSION. PET/MRI showed comparable or superior diagnostic performance versus PET/CT across a range of cancers and end points. CLINICAL IMPACT. The findings help to identify clinical settings where PET/MRI may provide clinical benefit for oncologic evaluation. TRIAL REGISTRATION. Prospective Register of Systematic Reviews CRD42023433857.

Detection of liver metastases in patients with pancreatic adenocarcinoma: MRI versus CT

Introduction. Detection of liver metastases is important to guide therapeutic management of pancreatic cancer. Data suggest that magnetic resonance imaging (MRI) is more sensitive than computed tomography (CT) for the diagnosis of liver metastases from pancreatic cancer. However, MRI is currently not recommended in several guidelines. Purpose. To compare the performance of CT vs MRI in detection of liver metastases in patients with pancreatic adenocarcinoma. Methods. This was a retrospective single-center study over 24 months from January 2020 to December 2021 of patients suspected of having PDAC. All patients underwent contrast-enhanced triple phase CT and contrast-enhanced MRI/MRCP. The CT and MRI assessment of resectability and detection of metastases were performed according to NCCN version 1.2024 criteria by one observer based on clinical report. Composite reference standard based on decision of operability (based on multidisciplinary tumor board decision), surgical findings (delay of 2 to 3 weeks after imaging) and histopathologic findings. Results. 117 patients (M/F 52/65, mean age 62±11y) were included. The mean tumor size was 43.6±15.2mm (add range). 42/46 patients (34.2%/39.3%) were diagnosed with metastatic disease on CT/MRI, 40/36 patients (34.2%/30.8%) were resectable, 20/16 patients (17.1%/13.7%) were borderline resectable and 15/19 patients (12.8%/16.2%) were locally advanced. The detection of liver metastases on CT and MRI was compared with surgical findings in 45 patients (38.5%). The analysis showed that MRI had superior performance to CT, with sensitivity at 100% vs 60% and specificity at 97.1% vs 97.1%, PPV at 90.9% vs 85.7% and NPV 100% vs 89.5% (MRI/CT). Conclusion. MRI is more sensitive than CT in detection of liver metastases in patients with pancreatic adenocarcinoma.

A novel model for predicting postoperative liver metastasis in R0 resected pancreatic neuroendocrine tumors: integrating computational pathology and deep learning-radiomics

BackgroundPostoperative liver metastasis significantly impacts the prognosis of pancreatic neuroendocrine tumor (panNET) patients after R0 resection. Combining computational pathology and deep learning radiomics can enhance the detection of postoperative liver metastasis in panNET patients.MethodsClinical data, pathology slides, and radiographic images were collected from 163 panNET patients post-R0 resection at Fudan University Shanghai Cancer Center (FUSCC) and FUSCC Pathology Consultation Center. Digital image analysis and deep learning identified liver metastasis-related features in Ki67-stained whole slide images (WSIs) and enhanced CT scans to create a nomogram. The model’s performance was validated in both internal and external test cohorts.ResultsMultivariate logistic regression identified nerve infiltration as an independent risk factor for liver metastasis (p < 0.05). The Pathomics score, which was based on a hotspot and the heterogeneous distribution of Ki67 staining, showed improved predictive accuracy for liver metastasis (AUC = 0.799). The deep learning-radiomics (DLR) score achieved an AUC of 0.875. The integrated nomogram, which combines clinical, pathological, and imaging features, demonstrated outstanding performance, with an AUC of 0.985 in the training cohort and 0.961 in the validation cohort. High-risk group had a median recurrence-free survival of 28.5 months compared to 34.7 months for the low-risk group, showing significant correlation with prognosis (p < 0.05).ConclusionA new predictive model that integrates computational pathologic scores and deep learning-radiomics can better predict postoperative liver metastasis in panNET patients, aiding clinicians in developing personalized treatments.

The combined detection of carcinoembryonic antigen, carcinogenic antigen 125, and carcinogenic antigen 19-9 in colorectal cancer patients.

Hepatic metastases are common and difficult to treat after colorectal cancer (CRC) surgery. The predictive value of carcinoembryonic antigen (CEA), cancer antigen (CA) 125 and CA19-9 combined tests for liver metastasis is unclear. To evaluate predictive value of combined tests for CEA, CA125, and CA19-9 levels in patients with liver metastases of CRC. The retrospective study included patients with CRC alone (50 cases) and patients with CRC combined with liver metastases (50 cases) who were hospitalized between January 2021 and January 2023. Serum CEA, CA125 and CA19-9 levels were compared between the two groups, and binary logistic regression was used to analyze the predictive value of the combination of these tumor markers in liver metastasis. In addition, we performed receiver operating characteristic (ROC) curve analysis to assess its diagnostic accuracy. The results showed that the serum CEA, CA125 and CA19-9 levels in the CRC with liver metastasis group were significantly higher than those in the CRC alone group. Specifically, the average serum CEA level in the CRC with liver metastasis group was 162.03 ± 810.01 ng/mL, while that in the CRC alone group was 5.71 ± 9.76 ng/mL; the average serum CA125 levels were 43.47 ± 83.52 U/mL respectively. and 13.5 ± 19.68 U/mL; the average serum CA19-9 levels were 184.46 ± 473.13 U/mL and 26.55 ± 43.96 U/mL respectively. In addition, binary logistic regression analysis showed that CA125 was significant in predicting CRC liver metastasis (P < 0.05). ROC curve analysis results showed that the areas under the ROC curves of CEA, CA125 and CA19-9 were 0.607, 0.692 and 0.586. These results suggest that combined detection of these tumor markers may help early detection and intervention of CRC liver metastasis, thereby improving patient prognosis.

Deep learning CT reconstruction improves liver metastases detection

ObjectivesDetection of liver metastases is crucial for guiding oncological management. Computed tomography through iterative reconstructions is widely used in this indication but has certain limitations. Deep learning image reconstructions (DLIR) use deep neural networks to achieve a significant noise reduction compared to iterative reconstructions. While reports have demonstrated improvements in image quality, their impact on liver metastases detection remains unclear. Our main objective was to determine whether DLIR affects the number of detected liver metastasis. Our secondary objective was to compare metastases conspicuity between the two reconstruction methods.MethodsCT images of 121 patients with liver metastases were reconstructed using a 50% adaptive statistical iterative reconstruction (50%-ASiR-V), and three levels of DLIR (DLIR-low, DLIR-medium, and DLIR-high). For each reconstruction, two double-blinded radiologists counted up to a maximum of ten metastases. Visibility and contour definitions were also assessed. Comparisons between methods for continuous parameters were performed using mixed models.ResultsA higher number of metastases was detected by one reader with DLIR-high: 7 (2–10) (median (Q₁–Q₃); total 733) versus 5 (2–10), respectively for DLIR-medium, DLIR-low, and ASiR-V (p < 0.001). Ten patents were detected with more metastases with DLIR-high simultaneously by both readers and a third reader for confirmation. Metastases visibility and contour definition were better with DLIR than ASiR-V.ConclusionDLIR-high enhanced the detection and visibility of liver metastases compared to ASiR-V, and also increased the number of liver metastases detected.Critical relevance statementDeep learning-based reconstruction at high strength allowed an increase in liver metastases detection compared to hybrid iterative reconstruction and can be used in clinical oncology imaging to help overcome the limitations of CT.Key PointsDetection of liver metastases is crucial but limited with standard CT reconstructions.More liver metastases were detected with deep-learning CT reconstruction compared to iterative reconstruction.Deep learning reconstructions are suitable for hepatic metastases staging and follow-up.Graphical

Impact of pre-operative abdominal MRI on survival for patients with resected pancreatic carcinoma: a population-based study

This study determined the impact of pre-operative abdominal MRI on all-cause mortality for patients with resected PDAC. All adult (≥18 years) PDAC patients who underwent pancreatectomy between January 2011 and December 2022 in Ontario, Canada, were identified for this population-based cohort study (ICD-O-3 codes: C250, C251, C252, C253, C257, C258). Patient demographics, comorbidities, PDAC stage, medical and surgical management, and survival data were sourced from multiple linked provincial administrative databases at ICES. All-cause mortality was compared between patients with and without a pre-operative abdominal MRI after controlling for multiple covariates. A cohort of 4579 patients consisted of 2432 men (53.1%) and 2147 women (46.9%) with a mean age of 65.2 years (standard deviation: 11.2 years); 2998 (65.5%) died while 1581 (34.5%) survived. Median follow-up duration post-resection was 22.4 months (interquartile range: 10.8-48.8 months), and median survival post-pancreatectomy was 25.9 months (95% confidence interval [95% CI]: 24.8, 27.5). Patients who underwent a pre-operative abdominal MRI had a median survival of 33.1 months (95% CI: 30.7, 37.2) compared to 21.1 months (95% CI: 19.8, 22.6) for all others. A total of 2354/4579 (51.4%) patients underwent a pre-operative abdominal MRI, which was associated with a 17.2% (95% CI: 11.0, 23.1) decrease in the rate of all-cause mortality, with an adjusted hazard ratio (aHR) of 0.828 (95% CI: 0.769, 0.890). Pre-operative abdominal MRI was associated with improved overall survival for PDAC patients who underwent pancreatectomy, possibly due to better detection of liver metastases than CT. Northern Ontario Academic Medicine Association (NOAMA) Clinical Innovation Fund.

Abstract PO3-06-13: A novel stable 6-aryl-2-benzoyl-pyridine colchicine-binding site inhibitor targeting microtubules (60c) is effective against taxane-resistant, metastatic breast cancer

Abstract Background: Improving survival for patients diagnosed with metastatic disease and treating spontaneous chemoresistance remain major clinical challenges in treating breast cancer. Triple negative breast cancer (TNBC), characterized by a lack of therapeutically targetable receptors (ER/PR/HER2), is an aggressive subtype of breast cancer. TNBC therapy relies on a combination of systemically administered chemotherapies, including microtubule-targeting agents (MTAs) like paclitaxel (taxane class) or eribulin (vinca class); however, there are currently no FDA approved MTAs that bind to the colchicine-binding site. Approximately 70% of patients who initially respond to paclitaxel, a first-line MTA, will develop taxane resistance (TxR) within 6 months. We have previously reported that an orally bioavailable colchicine-binding site inhibitor (CBSI), sabizabulin (formerly known as Veru-111), not only inhibits TNBC tumor progression but also treats pre-established metastatic disease in a taxane-refractory PDX model, HCI-10-Luc2. Sabizabulin is currently in phase II/III trials for advanced prostate cancer. To further improve potency and metabolic stability, we created next-generation derivatives of the sabizabulin scaffold, including 60c. Results: 60c shows improved potency compared to sabizabulin against taxane-sensitive and TxR TNBC models, inhibiting proliferation and clonogenicity at low nanomolar concentrations, and inducing apoptosis in a dose-dependent manner. In vivo, 60c therapy significantly suppressed primary tumor growth and lung metastasis in an orthotopic MDA-MB-231-TxR xenograft model without gross toxicity, and with equivalent efficacy to combrestatin A4 phosphate (CA-4P), another CBSI in clinical trials. In the taxane-refractory HCI-10-Luc2 PDX model, 60c significantly suppressed both the growth of the primary tumor (by ~3.5 fold) and the expansion of pre-established axillary metastases (by ~26 fold) whereas paclitaxel had no effect. Analysis of total photon flux of organs excised at study endpoint showed that 60c had distinct anti-metastatic tropism as compared to sabizabulin. Whereas 60c completely suppressed metastases to the spleen (0/9 mice had signal), and significantly reduced metastatic burden in the leg bones (only 3/9 mice had signal) and in the kidney (only 2/9 mice had signal), 60c had no statistically significant effect on liver metastases. In contrast, we had previously reported that sabizabulin strongly repressed liver metastases in the same PDX model (0 mice with detectable liver metastases), with less potent effects on bone. Unlike 60c, sabizabulin showed no improvement relative to the vehicle control for spleen and kidney metastases. Together, our data positions 60c as a promising candidate for TNBC therapy, particularly for patients with TxR disease. Our results also suggest that different CBSI scaffolds may preferentially inhibit metastasis to specific organs, which requires further investigation. Citation Format: Damilola Oluwalana, Kelli Hartman, Raisa Krutilina, Hao Chen, Hilaire Playa, Shanshan Deng, Deanna Parke, Duane Miller, Tiffany Seagroves, Wei Li. A novel stable 6-aryl-2-benzoyl-pyridine colchicine-binding site inhibitor targeting microtubules (60c) is effective against taxane-resistant, metastatic breast cancer [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PO3-06-13.

Improving the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm using DenseNet

IntroductionThinner slices are more susceptible in detecting small lesions but suffer from higher statistical fluctuation. This work aimed to reduce image noise in multiphase contrast-enhanced CT reconstructed with slice thickness thinner than the clinical setting (i.e., 5 mm) using convolutional neural network (CNN) for enabling better detection of hypo-vascular liver metastasis. MethodsA DenseNet model was used to generate noise map for multiphase CT reconstructed with slice thickness of 2.5 mm and 1.25 mm. Image denoising was conducted by subtracting the CNN-generated noise map from CT images with reduced photon flux due to thinner slice thickness. The performance of DenseNet was evaluated on CT scans of electron density phantoms and patients with hypovascular liver metastases less than 1.5 cm in terms of Hounsfield Unit (HU) variation, statistical fluctuation, and contrast-to-noise ratio (CNR). ResultsThe phantom study demonstrated that the CNN-based denoising method was able to reduce statistical fluctuation in CT images reconstructed with slice thickness of 2.5 mm and 1.25 mm without causing significant edge blurring or variation in HU values. With regards to patient study, it was found that the denoised 2.5-mm and 1.25-mm slices had higher CNR than the conventional 5-mm slices for hypo-vascular liver metastases in all 4 phases of multiphase CT. ConclusionOur results demonstrated that the detection of hypo-vascular liver metastases in multiphase contrast-enhanced CT with slice thickness less than 5 mm could be improved by using the CNN-based denoising method. Implications for practiceReconstruction slice thickness has a strong influence on the image quality of CT imaging. A CNN-based denoising method was used in this work to reduce the image noise in multiphase contrast-enhanced CT reconstructed with slice thickness less than 5 mm.

High serum alpha-fetoprotein and positive immunohistochemistry of alpha-fetoprotein are related to poor prognosis of gastric cancer with liver metastasis

Liver metastasis in gastric cancer is incurable. Alpha-fetoprotein-producing gastric cancer has a poor prognosis and is prone to liver metastasis. We investigated the association between preoperative serum alpha-fetoprotein levels, liver metastasis, and expression of primitive enterocyte phenotype markers. We reviewed the medical records of 401 patients with gastric cancer who underwent curative surgical resection and immunohistochemically evaluated the primitive phenotype markers. The preoperative serum alpha-fetoprotein levels were elevated and normal in 8 and 393 patients, respectively. Liver metastasis was more frequent in patients with higher preoperative alpha-fetoprotein levels. The 5-year postoperative recurrence-free survival and overall survival rates were significantly worse in patients with higher preoperative serum alpha-fetoprotein levels. Although alpha-fetoprotein and Glypican3 and Spalt-like transcription factor 4 tended to be stained with high preoperative serum alpha-fetoprotein levels, these markers were also positive in some patients with normal alpha-fetoprotein levels. In summary, patients with gastric cancer and high preoperative serum alpha-fetoprotein levels have a poor prognosis and high incidence of liver metastasis. Alpha-fetoprotein can help detect liver metastasis relating to the primitive enterocyte phenotype.

Multiomic analysis for minimal residual disease detection: Addressing challenges in stage II-III colon cancer from COSMOS-CRC-01.

180 Background: A considerable number of patients with stage II-III colon cancer experience disease recurrence following definitive treatment while others may receive unnecessary toxicity from adjuvant chemotherapy. Minimal residual disease (MRD) detection through ctDNA analysis can be evaluated without reliance on tissue which comes with logistic advantages and may be the only option for patients with limited tumor specimens. Methods: COSMOS-CRC-01 is an ongoing biomarker study that enrolled patients with resectable stage 0-III colorectal cancer between January 2020 and April 2021. Plasma samples and clinical data were collected 28 days post-operatively and every 3-6 months for up to 5 years alongside radiographic imaging. Samples were tested on the Guardant Reveal Infinity Oncology Platform for MRD detection. This analytically validated multiomic NGS assay interrogates &gt;700 genes and ~15Mb of methylated regions. A bioinformatics algorithm trained for CRC detection classifies each sample as ctDNA detectable or undetectable based on a predefined statistical likelihood threshold and returns quantitative tumor fraction. The primary endpoint was time to recurrence (TTR) based on ctDNA detection status. Results: This subgroup analysis evaluated 801 post-surgical plasma samples (4mL each, median input 19ng, 96% passed QC) from 136 patients with R0 resected stage II-III colon cancer with a median follow-up of 28 months. ctDNA detection at Day 28 post-surgery and following adjuvant chemotherapy were both associated with significantly shorter TTR (p&lt;0.0001; Table). Sensitivity with serial measurement was 80% (95% CI, 56.3-94.3%), with a median lead time of 5.3 months. Sensitivity was highest for detection of locoregional (2/2), brain (1/1), liver (7/7), or multiple (3/3) metastasis compared to isolated lung (2/4) or peritoneal (1/3) metastasis. Tumor fraction increased as expected in samples collected closer to the time of radiographic detection. Three recurred patients had KRAS G12C variants detected in ctDNA prior to recurrence, suggesting the potential of early intervention with targeted agents. Among 553 post-treatment samples from 114 non-recurred patients, sample specificity was 97.3% (95% CI 95.6-98.5%). Conclusions: We show a plasma-only genomic- and methylation-based assay to have sensitive and specific detection of MRD in stage II-III colon cancer. Serial measurement provides superior performance versus one-time measurement at Day 28 post-surgery and detects targetable variants prior to recurrence. [Table: see text]

Detection of Liver Lesions in Colorectal Cancer Patients Using 18F-FDG PET/CT Dual-Time-Point Scan Imaging.

The aim of this study was to evaluate the diagnostic performance of dual-time-point fluorine-18-fluorodeoxyglucose positron emission computed tomography/computed tomography (18F-FDG PET/CT) compared to conventional early imaging for detecting colorectal liver metastases (CRLM) in colorectal cancer (CRC) patients. One hundred twenty-four consecutive CRC patients underwent dual-time-point imaging scans on a retrospective basis. Histopathological confirmation and/or clinical follow-up were accepted as the gold standard. Standard uptake values (SUV), signal-to-noise ratio (SNR), retention index (RI), tumor-to-normal liver ratio (TNR), and lesion sizes were measured for early and delayed PET scans. The diagnostic performance of early and delayed images was calculated on a per-patient basis and compared using McNemar's test. Among the 124 patients, 57 (46%) had CRLM, 6 (4.8%) had benign lesions, and 61 (49.2%) had no concerning lesions detected. Smaller CRLM lesions (<5 cm3) showed significantly higher uptake in the delayed scans relative to early imaging (p < 0.001). The SUV and TNR increased significantly in delayed imaging of all metastatic lesions (p < 0.001). The retention index of all CRLM was high (40.8%), especially for small lesions (54.8%). A total of 177 lesions in delayed images and 124 in standard early images were identified. In a per-patient analysis, delayed imaging had significantly higher sensitivity (100% vs. 87.7%) and specificity (91.0% vs. 94.0%) compared to early imaging (p-value = 0.04). The detection of liver lesions using dual-time-point PET/CT scan improves the sensitivity and specificity for the detection of colorectal liver metastasis.

Accuracy of liver metastasis detection and characterization: Dual-energy CT versus single-energy CT with deep learning reconstruction

PurposeTo assess whether image quality differences between SECT (single-energy CT) and DECT (dual-energy CT 70 keV) with equivalent radiation doses result in altered detection and characterization accuracy of liver metastases when using deep learning image reconstruction (DLIR), and whether DECT spectral curve usage improves accuracy of indeterminate lesion characterization. MethodsIn this prospective Health Insurance Portability and Accountability Act–compliant study (March through August 2022), adult men and non-pregnant adult women with biopsy-proven colorectal cancer and liver metastases underwent SECT (120 kVp) and a DECT (70 keV) portovenous abdominal CT scan using DLIR in the same breath-hold (Revolution CT ES; GE Healthcare). Participants were excluded if consent could not be obtained, if there were nonequivalent radiation doses between the two scans, or if the examination was cancelled/rescheduled. Three radiologists independently performed lesion detection and characterization during two separate sessions (SECT DLIRmedium and DECT DLIRhigh) as well as reported lesion confidence and overall image quality. Hounsfield units were measured. Spectral HU curves were provided for any lesions rated as indeterminate. McNemar’s test was used to test the marginal homogeneity in terms of diagnostic sensitivity, accuracy and lesion detection. A generalized estimating equation method was used for categorical outcomes. Results30 participants (mean age, 58 years ± 11, 21 men) were evaluated. Mean CTDIvol was 34 mGy for both scans. 141 lesions (124 metastases, 17 benign) with a mean size of 0.8 cm ± 0.3 cm were identified. High scores for image quality (scores of 4 or 5) were not significantly different between DECT (N = 71 out of 90 total scores from the three readers) and SECT (N = 62) (OR, 2.01; 95% CI:0.89, 4.57; P = 0.093). Equivalent image noise to SECT DLIRmed (HU SD 10 ± 2) was obtained with DECT DLIRhigh (HU SD 10 ± 3) (P = 1). There was no significant difference in lesion detection between DECT and SECT (140/141 lesions) (99.3%; 95% CI:96.1%, 100%).The mean lesion confidence scores by each reader were 4.2 ± 1.3, 3.9 ± 1.0, and 4.8 ± 0.8 for SECT and 4.1 ± 1.4, 4.0 ± 1.0, and 4.7 ± 0.8 for DECT (odds ratio [OR], 0.83; 95% CI: 0.62, 1.11; P = 0.21). Small lesion (≤5mm) characterization accuracy on SECT and DECT was 89.1% (95% CI:76.4%, 96.4%; 41/46) and 84.8% (71.1%, 93.7%; 39/46), respectively (P = 0.41). Use of spectral HU lesion curves resulted in 34 correct changes in characterizations and no mischaracterizations. ConclusionDECT required a higher strength of DLIR to obtain equivalent noise compared to SECT DLIR. At equivalent radiation doses and image noise, there was no significant difference in subjective image quality or observer lesion performance between DECT (70 keV) and SECT. However, DECT spectral HU curves of indeterminate lesions improved characterization.

MRI with DWI improves detection of liver metastasis and selection of surgical candidates with pancreatic cancer: a systematic review and meta-analysis.

To perform a systematic review and meta-analysis to evaluate if magnetic resonance imaging (MRI) with diffusion weighted imaging (DWI) adds value compared to contrast-enhanced computed tomography (CECT) alone in the preoperative evaluation of pancreatic cancer. MEDLINE, EMBASE, and Cochrane databases were searched for relevant published studies through October 2022. Studies met eligibility criteria if they evaluated the per-patient diagnostic performance of MRI with DWI in the preoperative evaluation of newly diagnosed pancreatic cancer compared to CECT. Our primary outcome was the number needed to treat (NNT) to prevent one futile surgery using MRI with DWI, defined as those in which CECT was negative and MRI with DWI was positive for liver metastasis (i.e., surgical intervention in metastatic disease missed by CECT). The secondary outcomes were to determine the diagnostic performance and the NNT of MRI with DWI to change management in pancreatic cancer. Nine studies met the inclusion criteria with a total of 1121 patients, of whom 172 had liver metastasis (15.3%). The proportion of futile surgeries reduced by MRI with DWI was 6.0% (95% CI, 3.0-11.6%), yielding an NNT of 16.6. The proportion of cases that MRI with DWI changed management was 18.1% (95% CI, 9.9-30.7), corresponding to an NNT of 5.5. The per-patient sensitivity and specificity of MRI were 92.4% (95% CI, 87.4-95.6%) and 97.3% (95% CI, 96.0-98.1). MRI with DWI may prevent futile surgeries in pancreatic cancer by improving the detection of occult liver metastasis on preoperative CECT with an NNT of 16.6. MRI with DWI complements the standard preoperative CECT evaluation for liver metastasis in pancreatic cancer, improving the selection of surgical candidates and preventing unnecessary surgeries. • The NNT of MRI with DWI to prevent potential futile surgeries due to occult liver metastasis on CECT, defined as those in which CECT was negative and MRI with DWI was positive for liver metastasis, in patients with pancreatic cancer was 16.6. • The higher performance of MRI with DWI to detect liver metastasis occult on CECT can be attributed to an increased detection of subcentimeter liver metastasis.

Contrast-enhanced ultrasound with microbubbles containing sulfur hexafluoride and perfluorobutane with Kupffer phase for the detection of colorectal liver metastases.

To compare contrast-enhanced ultrasound (CEUS) with microbubbles containing sulfur hexafluoride (SHF) and perfluorobutane (PFB) for the detection of colorectal liver metastasis (CRLM). In this prospective study, conducted from September to November 2021, patients with colorectal cancer were consecutively recruited and underwent same-day ultrasound, SHF-CEUS, and PFB-CEUS. The reference standard was contrast-enhanced MRI and follow-up imaging. The size, depth, echogenicity, and calcification of each focal liver lesion were recorded. The number and conspicuity of CRLMs, based on washout appearance during the late phase (LP) (> 120 s)/Kupffer phase (KP), were evaluated offsite by two blinded readers. Overall, 230 lesions (CRLMs, n= 219; benign lesions, n= 11) in 78 patients were evaluated. Lesion conspicuity (p= 0.344) and accuracy in the detection of CRLM were comparable for SHF- and PFB-CEUS (0.877 for SHF vs. 0.770 for PFB, p= 0.087). More CRLMs ≥ 10 mm were identified by LP contrast washout in SHF-CEUS than in KP PFB-CEUS (p< 0.001). More CRLMs < 10 mm were identified by KP washout in PFB-CEUS than in LP SHF-CEUS (p< 0.001). Conspicuity was better on PFB-CEUS than on SHF-CEUS (p= 0.027). In hyperechoic lesions, lesions located deeper than 80 mm, and calcified lesions, CRLM conspicuity on PFB-CEUS was inferior to that on SHF-CEUS (p< 0.05). The overall accuracy of detection and conspicuity of washout in CRLMs were comparable between SHF and PFB-CEUS. PFB-CEUS has the advantage of identifying washout in small CRLMs. However, larger, hyperechogenic, deep-seated, or calcified lesions were better identified using SHF-CEUS. Accuracy of detection and conspicuity of washout in CRLMs were comparable between SHF- and PFB-CEUS. PFB-CEUS has the advantage in detecting small CRLMs, whereas SHF-CEUS is better for detecting larger, hyperechogenic, deep-seated, or calcified lesions. Contrast-enhanced ultrasound with sulfur hexafluoride in the late phase and perfluorobutane microbubbles in the Kupffer phase were comparable in terms of accuracy in the detection and conspicuity of colorectal liver metastases. Small colorectal liver metastases (< 10 mm) were more often identified in the Kupffer phase contrast-enhanced ultrasound imaging when using perfluorobutane microbubbles. Larger, hyperechogenic, deep-seated, or calcified lesions were better identified in the late phase contrast-enhanced ultrasound imaging (> 120 s) when using sulfur hexafluoride microbubbles.

Deep learning reconstruction CT for liver metastases: low-dose dual-energy vs standard-dose single-energy.

To assess image quality and liver metastasis detection of reduced-dose dual-energy CT (DECT) with deep learning image reconstruction (DLIR) compared to standard-dose single-energy CT (SECT) with DLIR or iterative reconstruction (IR). In this prospective study, two groups of 40 participants each underwent abdominal contrast-enhanced scans with full-dose SECT (120-kVp images, DLIR and IR algorithms) or reduced-dose DECT (40- to 60-keV virtual monochromatic images [VMIs], DLIR algorithm), with 122 and 106 metastases, respectively. Groups were matched by age, sex ratio, body mass index, and cross-sectional area. Noise power spectrum of liver images and task-based transfer function of metastases were calculated to assess the noise texture and low-contrast resolution. The image noise, signal-to-noise ratios (SNR) of liver and portal vein, liver-to-lesion contrast-to-noise ratio (LLR), lesion conspicuity, lesion detection rate, and the subjective image quality metrics were compared between groups on 1.25-mm reconstructed images. Compared to 120-kVp images with IR, 40- and 50-keV VMIs with DLIR showed similar noise texture and LLR, similar or higher image noise and low-contrast resolution, improved SNR and lesion conspicuity, and similar or better perceptual image quality. When compared to 120-kVp images with DLIR, 50-keV VMIs with DLIR had similar low-contrast resolution, SNR, LLR, lesion conspicuity, and perceptual image quality but lower frequency noise texture and higher image noise. For the detection of hepatic metastases, reduced-dose DECT by 34% maintained observer lesion detection rates. DECT assisted with DLIR enables a 34% dose reduction for detecting hepatic metastases while maintaining comparable perceptual image quality to full-dose SECT. Reduced-dose dual-energy CT with deep learning image reconstruction is as accurate as standard-dose single-energy CT for the detection of liver metastases and saves more than 30% of the radiation dose. • The 40- and 50-keV virtual monochromatic images (VMIs) with deep learning image reconstruction (DLIR) improved lesion conspicuity compared with 120-kVp images with iterative reconstruction while providing similar or better perceptual image quality. • The 50-keV VMIs with DLIR provided comparable perceptual image quality and lesion conspicuity to 120-kVp images with DLIR. • The reduction of radiation by 34% by DLIR in low-keV VMIs is clinically sufficient for detecting low-contrast hepatic metastases.

Performance of 18F-FDG PET/MR on TNM staging of pancreatic cancer compared with 18F-FDG PET/CT: A retrospective cohort study

PurposeThis study aimed to evaluate the TNM staging accuracy of 18F-FDG PET/MR compared with 18F-FDG PET/CT in patients with pancreatic cancer. Materials and methodsIn this retrospective cohort study, a total of 88 patients (53 men, 35 women, mean age 64.56±10.77 years) with pathologically confirmed pancreatic cancer who underwent 18F-FDG PET/CT and 18F-FDG PET/MR successively on the same day were enrolled. The maximal and peak standardized uptake values (SUVmax and SUVpeak) of pancreatic cancer lesions on PET/MR and PET/CT imaging were measured respectively. According to the 8th edition AJCC staging system of pancreatic adenocarcinoma, two experienced readers reviewed and assessed the PET/CT and PET/MR images independently for TNM staging. Using the diagnosis of enhanced CT, histopathological diagnosis and/or the clinical follow-up as the reference, the diagnostic performance of PET/CT and PET/MR were compared using the McNemar test. ResultsCompared with 18F-FDG PET/CT (63.64%), 18F-FDG PET/MR (85.23%) exhibited significantly higher diagnostic accuracy of T staging (P<0.05). In N staging, the diagnostic accuracy of PET/MR (81.4%) was higher than that of PET/CT (74.42%) but the difference was not statistically significant. In M staging, no significant difference was found between the diagnostic performance of PET/MR (96.59%) and PET/CT (92.05%). However, PET/MR detected more liver metastases in 11/18 patients and the clinical staging was upstaged in four patients compared to PET/CT. Both SUVmax and SUVpeak of pancreatic tumors showed strong correlations between PET/MR and PET/CT imaging (r=0.901 and 0.923, respectively; P<0.05). ConclusionsCompared with 18FFDG PET/CT, 18FFDG PET/MR showed better performance in the TNM staging of pancreatic cancer, especially in T staging and detection of liver metastases.

Super‐stable homogeneous embolic agents advance the treatment of hepatocellular carcinoma

Super‐stable homogeneous embolic agents advance the treatment of hepatocellular carcinoma

Diagnostic performance of PET/CT in the detection of liver metastases in well-differentiated NETs

BackgroundThe aim of this retrospective study was to compare the diagnostic accuracy of somatostatin receptor (SSR)-PET/CT to liver MRI as reference standard in the evaluation of hepatic involvement in neuroendocrine tumors (NET).MethodsAn institutional database was screened for “SSR” imaging studies between 2006 and 2021. 1000 NET Patients (grade 1/2) with 2383 SSR-PET/CT studies and matching liver MRI in an interval of +3 months were identified. Medical reports of SSR-PET/CT and MRI were retrospectively evaluated regarding hepatic involvement and either confirmed by both or observed in MRI but not in SSR-PET/CT (false-negative) or in SSR-PET but not in MRI (false-positive).ResultsMetastatic hepatic involvement was reported in 1650 (69.2%) of the total 2383 SSR-PET/CT imaging studies, whereas MRI detected hepatic involvement in 1685 (70.7%) cases. There were 51 (2.1%) false-negative and 16 (0.7%) false-positive cases. In case of discrepant reports, MRI and PET/CT were reviewed side by side for consensus reading. SSR-PET/CT demonstrated a sensitivity of 97.0% (95%CI: 96.0%, 97.7%), a specificity of 97.7% (95%CI: 96.3%, 98.7%), a PPV of 99.0% (95%CI: 98.4%, 99.4%) and NPV of 93.0% (95%CI: 91.0, 94.8%) in identifying hepatic involvement. The most frequent reason for false-negative results was the small size of lesions with the majority < 0.6 cm.ConclusionThis study confirms the high diagnostic accuracy of SSR-PET/CT in the detection of hepatic involvement in NET patients based on a patient-based analysis of metastatic hepatic involvement with a high sensitivity and specificity using liver MRI imaging as reference standard. However, one should be aware of possible pitfalls when a single imaging method is used in evaluating neuroendocrine liver metastases in patients.

A training program to reduce reader search errors for liver metastasis detection in CT.

Detection of low contrast liver metastases varies between radiologists. Training may improve performance for lower-performing readers and reduce inter-radiologist variability. We recruited 31 radiologists (15 trainees, 8 non-abdominal staff, and 8 abdominal staff) to participate in four separate reading sessions: pre-test, search training, classification training, and post-test. In the pre-test, each radiologist interpreted 40 liver CT exams containing 91 metastases, circumscribed suspected hepatic metastases while under eye tracker observation, and rated confidence. In search training, radiologists interpreted a separate set of 30 liver CT exams while receiving eye tracker feedback and after coaching to increase use of coronal reformations, interpretation time, and use of liver windows. In classification training, radiologists interpreted up to 100 liver CT image patches, most with benign or malignant lesions, and compared their annotations to ground truth. Post-test was identical to pre-test. Between pre- and post-test, sensitivity increased by 2.8% (p = 0.01) but AUC did not change significantly. Missed metastases were classified as search errors (<2 seconds gaze time) or classification errors (>2 seconds gaze time) using the eye tracker. Out of 2775 possible detections, search errors decreased (10.8% to 8.1%; p < 0.01) but classification errors were unchanged (5.7% vs 5.7%). When stratified by difficulty, easier metastases showed larger reductions in search errors: for metastases with average sensitivity of 0-50%, 50-90%, and 90-100%, reductions in search errors were 16%, 35%, and 58%, respectively. The training program studied here may be able to improve radiologist performance by reducing errors but not classification errors.