Radiomics analysis with three-dimensional and two-dimensional segmentation to predict survival outcomes in pancreatic cancer.

BACKGROUND: Radiomics can assess prognostic factors in several types of tumors, but considering its prognostic ability in pancreatic cancer has been lacking. AIM: To evaluate the performance of two different radiomics software in assessing survival outcomes in pancreatic cancer patients. METHODS: We retrospectively reviewed pretreatment contrast-enhanced dual-energy computed tomography images from 48 patients with biopsy-confirmed pancreatic ductal adenocarcinoma who later underwent neoadjuvant chemoradiation and surgery. Tumors were segmented using TexRad software for 2-dimensional (2D) analysis and MIM software for 3D analysis, followed by radiomic feature extraction. Cox proportional hazard modeling correlated texture features with overall survival (OS) and progression-free survival (PFS). Cox regression was used to detect differences in OS related to pretreatment tumor size and residual tumor following treatment. The Wilcoxon test was used to show the relationship between tumor volume and the percent of residual tumor. Kaplan-Meier analysis was used to compare survival in patients with different tumor densities in Hounsfield units for both 2D and 3D analysis. RESULTS: 3D analysis showed that higher mean tumor density [hazard ratio (HR) = 0.971, P = 0.041)] and higher median tumor density (HR = 0.970, P = 0.037) correlated with better OS. 2D analysis showed that higher mean tumor density (HR = 0.963, P = 0.014) and higher mean positive pixels (HR = 0.962, P = 0.014) correlated with better OS; higher skewness (HR = 3.067, P = 0.008) and higher kurtosis (HR = 1.176, P = 0.029) correlated with worse OS. Higher entropy correlated with better PFS (HR = 0.056, P = 0.036). Models determined that patients with increased tumor size greater than 1.35 cm were likely to have a higher percentage of residual tumors of over 10%. CONCLUSION: Several radiomics features can be used as prognostic tools for pancreatic cancer. However, results vary between 2D and 3D analyses. Mean tumor density was the only variable that could reliably predict OS, irrespective of the analysis used.

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

PURPOSE: To 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. METHODS: In 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. RESULTS: 30 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. CONCLUSION: DECT 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.

Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such effects. Purpose To evaluate liver metastases and image quality between reduced-dose deep learning image reconstruction (DLIR) and standard-dose filtered back projection (FBP) contrast-enhanced abdominal CT. Materials and Methods In this prospective Health Insurance Portability and Accountability Act-compliant study (September 2019 through April 2021), participants with biopsy-proven colorectal cancer and liver metastases at baseline CT underwent standard-dose and reduced-dose portal venous abdominal CT in the same breath hold. Three radiologists detected and characterized lesions at standard-dose FBP and reduced-dose DLIR, reported confidence, and scored image quality. Contrast-to-noise ratios for liver metastases were recorded. Summary statistics were reported, and a generalized linear mixed model was used. Results Fifty-one participants (mean age ± standard deviation, 57 years ± 13; 31 men) were evaluated. The mean volume CT dose index was 65.1% lower with reduced-dose CT (12.2 mGy) than with standard-dose CT (34.9 mGy). A total of 161 lesions (127 metastases, 34 benign lesions) with a mean size of 0.7 cm ± 0.3 were identified. Subjective image quality of reduced-dose DLIR was superior to that of standard-dose FBP (P < .001). The mean contrast-to-noise ratio for liver metastases of reduced-dose DLIR (3.9 ± 1.7) was higher than that of standard-dose FBP (3.5 ± 1.4) (P < .001). Differences in detection were identified only for lesions 0.5 cm or smaller: 63 of 65 lesions detected with standard-dose FBP (96.9%; 95% CI: 89.3, 99.6) and 47 lesions with reduced-dose DLIR (72.3%; 95% CI: 59.8, 82.7). Lesion accuracy with standard-dose FBP and reduced-dose DLIR was 80.1% (95% CI: 73.1, 86.0; 129 of 161 lesions) and 67.1% (95% CI: 59.3, 74.3; 108 of 161 lesions), respectively (P = .01). Lower lesion confidence was reported with a reduced dose (P < .001). Conclusion Deep learning image reconstruction (DLIR) improved CT image quality at 65% radiation dose reduction while preserving detection of liver lesions larger than 0.5 cm. Reduced-dose DLIR demonstrated overall inferior characterization of liver lesions and reader confidence. Clinical trial registration no. NCT03151564 © RSNA, 2022 Online supplemental material is available for this article.

Update on quantitative radiomics of pancreatic tumors.

Radiomics is a newer approach for analyzing radiological images obtained from conventional imaging modalities such as computed tomography, magnetic resonance imaging, endoscopic ultrasonography, and positron emission tomography. Radiomics involves extracting quantitative data from the images and assessing them to identify diagnostic or prognostic features such as tumor grade, resectability, tumor response to neoadjuvant therapy, and survival. The purpose of this review is to discuss the basic principles of radiomics and provide an overview of the current clinical applications of radiomics in the field of pancreatic tumors.

Mastocytosis-A Review of Disease Spectrum with Imaging Correlation.

Mastocytosis is a rare disorder due to the abnormal proliferation of clonal mast cells. Mast cells exist in most tissues, mature in situ from hematopoietic stem cells and develop unique characteristics of local effector cells. Mastocytosis develops by activation mutation of the KIT surface receptor which is involved in the proliferation of a number of cell lines such as mast cells, germ cells, melanocytes, and hematopoietic cells. It manifests as two main categories: cutaneous mastocytosis and systemic mastocytosis. Imaging can play an important role in detection and characterization of the disease manifestation, not only by radiography and bone scans, but also magnetic resonance imaging and computed tomography, which can be more sensitive in the assessment of distinctive disease patterns. Radiologists should be aware of various appearances of this disease to better facilitate diagnosis and patient management. Accordingly, this review will discuss the clinical presentation, pathophysiology, and role of imaging in detection and extent estimation of the systemic involvement of the disease, in addition to demonstration of appearance on varying imaging modalities. Familiarity with the potential imaging findings associated with mastocytosis can aid in early disease diagnosis and classification and accordingly can lead directing further work up and better management.

PTEN Hamartoma Tumor Syndrome/Cowden Syndrome: Genomics, Oncogenesis, and Imaging Review for Associated Lesions and Malignancy.

PTEN hamartoma tumor syndrome/Cowden syndrome (CS) is a rare autosomal dominant syndrome containing a germline PTEN mutation that leads to the development of multisystem hamartomas and oncogenesis. Benign tumors such as Lhermitte-Duclos disease and malignant tumors involving the breast, thyroid, kidneys, and uterus are seen in CS. Radiologists have an integral role in the comanagement of CS patients. We present the associated imaging findings and imaging screening recommendations. Knowledge of the types of cancers commonly seen in CS and their imaging findings can aid in early tumor recognition during cancer screening to help ensure near-normal life spans in CS patients.

Imaging and Management of Bladder Cancer.

METHODS: Keyword searches of Medline, PubMed, and the Cochrane Library for manuscripts published in English, and searches of references cited in selected articles to identify additional relevant papers. Abstracts sponsored by various societies including the American Urological Association (AUA), European Association of Urology (EAU), and European Society for Medical Oncology (ESMO) were also searched. BACKGROUND: Bladder cancer is the sixth most common cancer in the United States, and one of the most expensive in terms of cancer care. The overwhelming majority are urothelial carcinomas, more often non-muscle invasive rather than muscle-invasive. Bladder cancer is usually diagnosed after work up for hematuria. While the workup for gross hematuria remains CT urography and cystoscopy, the workup for microscopic hematuria was recently updated in 2020 by the American Urologic Association with a more risk-based approach. Bladder cancer is confirmed and staged by transurethral resection of bladder tumor. One of the main goals in staging is determining the presence or absence of muscle invasion by tumor which has wide implications in regards to management and prognosis. CT urography is the main imaging technique in the workup of bladder cancer. There is growing interest in advanced imaging techniques such as multiparametric MRI for local staging, as well as standardized imaging and reporting system with the recently created Vesicle Imaging Reporting and Data System (VI-RADS). Therapies for bladder cancer are rapidly evolving with immune checkpoint inhibitors, particularly programmed death ligand 1 (PD-L1) and programmed cell death protein 1 (PD-1) inhibitors, as well as another class of immunotherapy called an antibody-drug conjugate which consists of a cytotoxic drug conjugated to monoclonal antibodies against a specific target. CONCLUSION: Bladder cancer is a complex disease, and its management is evolving. Advances in therapy, understanding of the disease, and advanced imaging have ushered in a period of rapid change in the care of bladder cancer patients.

Clinical and Imaging Features of Noncutaneous Melanoma.

OBJECTIVE: The purpose of this article is to summarize the epidemiologic characteristics, clinical aspects, and radiologic appearance of as well as the management considerations and differential diagnoses for noncutaneous primary melanomas occurring at specific anatomic sites. Primary ocular, sinonasal, meningeal, biliary, adrenal, alimentary tract, and genitourinary melanomas are highlighted. CONCLUSION: Noncutaneous primary melanomas are a complex group of malignancies with biologic findings that are unique when compared with findings for cutaneous melanomas. Each noncutaneous primary melanoma has its own specific diagnostic and management challenges, depending on the anatomic location where they arise.

Renal mass biopsy and thermal ablation: should biopsy be performed before or during the ablation procedure?

PURPOSE: To determine if renal mass biopsy should be performed before or during the ablation procedure with emphasis on complications and rate of ablation for renal cell carcinomas (RCC), benign tumors, and small renal masses without a histologic diagnosis. METHODS: This HIPAA-compliant, single-center retrospective study was performed under a waiver of informed consent from the institutional review board. Two hundred eighty-four consecutive patients with a small renal mass (≤4.0 cm) treated with percutaneous thermal ablation between January 2001 and January 2015 were included. Two cohorts were identified based upon the timing of renal mass biopsy: separate session two weeks prior to ablation and same session obtained immediately preceding ablation. Clinical and pathologic data were collected including risk factors for non-diagnostic biopsy. Two-sided t test, χ 2 test or Fischer's exact tests were used to evaluate differences between cohorts. Univariate and multivariate logistic regression models were constructed. RESULTS: A histologic diagnostic was achieved more frequently in the separate session cohort [210/213 (98.6%) vs. 60/71 (84.3%), p < 0.0001]. The rate of ablation of RCC was higher in the separate session group [201/213 (94.4%) vs. 46/61 (64.7%), p = 0.001]. The rate of ablation for benign tumors [14/71 (19.7%) vs. 6/213 (2.8%), p < 0.0001] and small renal masses without a histologic diagnosis [3/213 (1.4%) vs. 11/71 (15.5%), p < 0.0001] was higher in the same session cohort. There were no high-grade complications in either cohort. CONCLUSION: Performing renal mass biopsy prior to the day of ablation is safe, increases the rate of histologic diagnosis, and reduces the rate of ablation for benign tumors and small renal masses without a histologic diagnosis.

(99m)Tc-EC-guanine: synthesis, biodistribution, and tumor imaging in animals.

PURPOSE: DNA markers are useful in assessing cell proliferation. The purpose of this study was to synthesize (99m)Tc-ethylenedicysteine-guanine (EC-Guan) for evaluation of cell proliferation. METHODS: Tumor cells were incubated with (99m)Tc-EC-Guan for cell cycle analysis. Prostate tumor cells that were overexpressing the HSV thymidine kinase gene, or various tumor cells were incubated with (99m)Tc-EC-Guan at 0.5-2 h. Thymidine incorporation assays were performed in lung cancer cells incubated with EC-Guan at 0.1-1 mg/well. Tissue distribution, autoradiography, and planar scintigraphy of (99m)Tc-EC-Guan and (99m)Tc-EC (control) were determined in tumor-bearing rodents at 0.5-4 h. RESULTS: Cell culture assays indicated that EC-Guan was incorporated in DNA, and there was no significant uptake difference between HSVTK overexpressed and normal groups. Biodistribution and scintigraphic imaging studies of (99m)Tc-EC-Guan showed increased tumor/tissue count density ratios as a function of time. CONCLUSIONS: Our results indicate that (99m)Tc-EC-Guan may be useful as a tumor proliferation imaging agent.