Contrast-Enhanced Micro-CT Imaging of Murine Mandibles: A Multi-Method Approach for Simultaneous Hard and Soft Tissue Analysis.

AIM: To develop and evaluate a novel multi-method micro-computed tomography (µCT) imaging protocol for enhanced visualization of both hard and soft tissues in murine mandibles, addressing the limitations of traditional imaging techniques in dental research. MATERIALS AND METHODS: We employed a contrast-enhanced (CE) µCT imaging technique using Lugol's iodine as a contrast agent to visualize the intricate structures of murine mandibles. The protocol involved the combination of conventional µCT imaging as well as CE-µCT, including decalcification with EDTA, allowing for simultaneous assessment of hard and soft tissues. The method is compared with standard imaging modalities, and the ability to visualize detailed anatomical features is discussed. RESULTS: The CE-µCT imaging technique provided superior visualization of murine mandibular structures, including dental pulp, periodontal ligaments and the surrounding soft tissues, along with conventional µCT imaging of alveolar bone and teeth. This method revealed detailed anatomical features with high specificity and contrast, surpassing traditional imaging approaches. CONCLUSION: Our findings demonstrate the potential of CE-µCT imaging with Lugol's iodine as a powerful tool for dental research. This technique offers a comprehensive view of the murine mandible, facilitating advanced studies in tissue engineering, dental pathology and the development of dental materials.

[Possibilities of post-processing of multislice computed tomography results in non-invasive diagnosis of pancreatic fibrosis].

AIM: To evaluate the possibilities of post-processing of multidetector computed tomography (CT) results in the non-invasive diagnosis of pancreatic fibrosis (PF). MATERIALS AND METHODS: The study included 165 patients aged 57.91±13.5 years who underwent preoperative CT during surgical treatment for chronic pancreatitis and pancreatic cancer from April 2022 to February 2024. The normalized contrast ratios of pancreatic tissue in the pancreatic (NCPP) and venous (NCVP) phases, as well as the contrast ratio (CR) were measured. Pathomorphological assessment of PF performed in tissues outside neoplasm or desmoplastic reaction by the Kloppel and Maillet scale. RESULTS: The values of post-processing CT results were compared in groups with different degrees of PF. Mean CR values were significantly higher (p=0.001) in patients with severe PF (CR 1.16±0.65 HU) than in patients with mild PF (CR 0.78±0.31 HU). CR value significant increase (p=0.03) was found in patients with signs of inflammatory changes in the pancreas tissue (CR 1.14±0.6 HU) than in those without them (CR 0.81±0.3 HU). There were no significant differences between the values of NCPP and NCVP, and the degree of PF. CONCLUSION: The CR value increased in patients with severe degree of PF. There was a relationship between CR value increase and the radiological density of pancreatic tissue in non-contrast phase and presence of early signs of pancreatic inflammatory changes. Thus, there was a relationship between CT postprocessing results and morphological signs of PF, which can be used for pancreatic fibrosis non-invasive diagnosis and identification of additional signs of early chronic pancreatitis.

Contrast enhancement after mechanical thrombectomy: clinical correlations and impact on outcomes.

PURPOSE: Contrast enhancement (CE) after mechanical thrombectomy (MT) remains a subject of investigation, with a reported prevalence ranging from 31 to 88%. We examined our patients to identify predictors of CE and its impact on outcomes, an aspect that remains understudied. METHODS: We retrospectively analyzed 106 patients who underwent MT at our hospital between 2018 and 2022. The inclusion criteria involved patients who underwent two head CT scans: one immediately after the procedure and a repeat scan within 24 h. This study compared demographic, clinical, laboratory, neuroimaging, and procedure-related variables between patients with CE and those without hyperdensity. Regression analysis was employed to determine the associations between CEs and significant variables. RESULTS: Among the analyzed patients, 32.1% had CE. Hyperlipidemia was more prevalent in the CE group. CE correlated with an increase in the National Institutes of Health Stroke Scale (NIHSS) score ≥ 4 within 24 h, intracerebral hemorrhage (ICH) incidence, elevated NIHSS score, and a decreased rate of modified Rankin scale (mRS) 0-3 upon discharge. The adjusted model demonstrated a significant association between CE and the incidence of hyperlipidemia and ICH, with an increase in NIHSS score ≥ 4 within 24 h of ICH and a lower mRS score of 0-3 upon discharge. CONCLUSIONS: CE is associated with hyperlipidemia, ICH, early neurological deterioration, and poor functional outcomes upon discharge. However, no similar association was shown for long-term outcomes. Further studies are required to clarify the pathophysiology of CE and its implications for optimizing stroke care.

Reappraisal of prognostic factors in CNS WHO grade 3 oligodendrogliomas IDH-mutant and 1p/19q co-deleted: lessons from the French POLA cohort.

BACKGROUND: In POLA cohort, three pathological groups of CNS WHO grade 3 oligodendroglioma IDH-mutant and 1p/19q co-deleted have been described: group 1 (high mitotic count only), group 2 (microvascular proliferation MVP and no necrosis), and group 3 (MVP and necrosis). METHODS: 494 patients from the POLA cohort, with a median follow up of 96 months were included. To identify the impact of the pathological groups and contrast enhancement in group 1 on overall survival (OS) or progression free survival (PFS), survival curves were obtained (Kaplan-Meier method) and compared (log-rank test). Prognostic value of clinical factors and CDKN2A homozygous deletion HD were also tested. Multivariate analysis was performed. RESULTS: Survival analysis demonstrated that the pathological groups were associated with both progression-free survival (PFS P=0.01) and overall survival (OS P=0.001). In group 1, patients with contrast enhancement (1CE+) had a poorer prognosis compared to those without (OS P=0.028, PFS P=0.006). Further stratification into group 1CE-, group 1CE+, group 2, and group 3 provided clearer prognostic distinctions (OS P=0.002, PFS P<0.0001). Other prognostic factors included age (OS P<0.0001, PFS P=0.002), extent of surgical resection (OS P=0.001, PFS P=0.003), KPS (OS P<0.0001, PFS P=0.002), postoperative treatment (OS P=0.007, PFS P<0.0001), and CDKN2A HD (OS and PFS P<0.0001). The pathological groups remained of prognostic significance for PFS in multivariate analysis. CONCLUSION: Necrosis and CDKN2A HD are adverse prognostic factors of WHO grade 3 oligodendrogliomas, IDH mutant and 1p/19q co-deleted. Besides, in group 1 patients, lack of contrast enhancement is a factor of better prognosis.

Implications of MRI contrast enhancement following focal prostate cancer cryoablation.

INTRODUCTION: Local disease recurrence following focal therapy (FT) for prostate cancer may be due to failure to eradicate focal disease or development of disease in the untreated prostate (in- and out-of-field recurrences). Several studies suggest in-field contrast enhancement (CE) on post-treatment multi-parametric (mp) MRI between 6-12 months following FT indicates residual disease. The present study assesses the incidence and oncologic implications of early CE observed following primary partial gland cryoablation (PPGCA). MATERIAL AND METHODS: The surveillance protocol for men enrolled in our prospective outcomes study following PPGCA included mpMRI at 6-12 months, 2 years, 3.5 years, and 5 years. All cases of in-field early CE were re-reviewed retrospectively and graded using the previously described Prostate Imaging after Focal Ablation scoring system. All patients exhibiting early CE were re-evaluated by a single radiologist at 2-year mpMRI Results: A total of 320 men enrolled in our PPGCA outcomes study had at least 6 months of follow up. Three hundred fifteen (98%) of these men had undergone post-PPGCA mpMRI at 6-12 months. Of these men, 9 were found to have early in-field CE and 8 underwent repeat MRI at 2 years. In all 8 cases, the CE resolved on the 2-year mpMRI. Of these 8 patients, seven underwent repeat protocol biopsy at 2 years and in-field significant disease was detected in only 1 case. CONCLUSIONS: The most compelling evidence that early CE is not indicative of prostate cancer recurrence is that all lesions resolved within 24 months. While incidence of early CE is low, its consistent resolution calls into question the clinical significance of this finding after PPGCA.

Utility of dynamic contrast enhancement for clinically significant prostate cancer detection.

Objective: This study aimed to evaluate the association of dynamic contrast enhancement (DCE) with clinically significant prostate cancer (csPCa, Gleason Grade Group ≥2) and compare biparametric magnetic resonance imaging (bpMRI) and multiparametric MRI (mpMRI) nomograms. Subjects/patients and methods: We identified a retrospective cohort of biopsy naïve patients who underwent pre-biopsy MRI separated by individual MRI series from 2018 to 2022. csPCa detection rates were calculated for patients with peripheral zone (PZ) lesions scored 3-5 on diffusion weighted imaging (DWI) with available DCE (annotated as - or +). bpMRI Prostate Imaging Reporting and Data System (PIRADS) (3 = 3-, 3+; 4 = 4-, 4+; 5 = 5-, 5+) and mpMRI PIRADS (3 = 3-; 4 = 3+, 4-, 4+; 5 = 5-, 5+) approaches were compared in multivariable logistic regression models. Nomograms for detection of csPCa and ≥GG3 PCa incorporating all biopsy naïve patients who underwent prostate MRI were generated based on available serum biomarkers [PHI, % free prostate-specific antigen (PSA), or total PSA] and validated with an independent cohort. Results: Patients (n = 1010) with highest PIRADS lesion in PZ were included in initial analysis with 127 (12.6%) classified as PIRADS 3+ (PIRADS 3 on bpMRI but PIRADS 4 on mpMRI). On multivariable analysis, PIRADS 3+ lesions were associated with higher csPCa rates compared to PIRADS 3- (3+ vs. 3-: OR 1.86, p = 0.024), but lower csPCa rates compared to PIRADS DWI 4 lesions (4 vs. 3+: OR 2.39, p < 0.001). csPCa rates were 19% (3-), 31% (3+), 41.5% (4-), 65.9% (4+), 62.5% (5-), and 92.3% (5+). bpMRI nomograms were non-inferior to mpMRI nomograms in the development (n = 1410) and independent validation (n = 353) cohorts. Risk calculators available at: https://rossnm1.shinyapps.io/MynMRIskCalculator/. Conclusion: While DCE positivity by itself was associated with csPCa among patients with highest PIRADS lesions in the PZ, nomogram comparisons suggest that there is no significant difference in performance of bpMRI and mpMRI. bpMRI may be considered as an alternative to mpMRI for prostate cancer evaluation in many situations.

Cross-site Validation of AI Segmentation and Harmonization in Breast MRI.

This work aims to perform a cross-site validation of automated segmentation for breast cancers in MRI and to compare the performance to radiologists. A three-dimensional (3D) U-Net was trained to segment cancers in dynamic contrast-enhanced axial MRIs using a large dataset from Site 1 (n = 15,266; 449 malignant and 14,817 benign). Performance was validated on site-specific test data from this and two additional sites, and common publicly available testing data. Four radiologists from each of the three clinical sites provided two-dimensional (2D) segmentations as ground truth. Segmentation performance did not differ between the network and radiologists on the test data from Sites 1 and 2 or the common public data (median Dice score Site 1, network 0.86 vs. radiologist 0.85, n = 114; Site 2, 0.91 vs. 0.91, n = 50; common: 0.93 vs. 0.90). For Site 3, an affine input layer was fine-tuned using segmentation labels, resulting in comparable performance between the network and radiologist (0.88 vs. 0.89, n = 42). Radiologist performance differed on the common test data, and the network numerically outperformed 11 of the 12 radiologists (median Dice: 0.85-0.94, n = 20). In conclusion, a deep network with a novel supervised harmonization technique matches radiologists' performance in MRI tumor segmentation across clinical sites. We make code and weights publicly available to promote reproducible AI in radiology.

Perfusion-weighted imaging with dynamic contrast enhancement (PWI/DCE) morphologic, qualitative, semiquantitative, and radiomics features predicting undifferentiated pleomorphic sarcoma (UPS) treatment response.

Undifferentiated pleomorphic sarcoma (UPS) is the largest subgroup of soft tissue sarcomas. This study determined the value of perfusion-weighted imaging with dynamic-contrast-enhancement (PWI/DCE) morphologic, qualitative, and semiquantitative features for predicting UPS pathology-assessed treatment effect (PATE). This retrospective study included 33 surgically excised extremity UPS patients with pre-surgical MRI. Volumetric tumor segmentation from PWI/DCE was obtained at Baseline (BL), Post-Chemotherapy (PC), and Post-Radiation Therapy (PRT). The surgical specimens' PATE separated cases into Responders (R) (≥ 90%, 16 patients), Partial-Responders (PR) (89 - 31%, 10 patients), and Non-Responders (NR) (≤ 30%, seven patients). Seven semiquantitative kinetic parameters and maps were extracted from time-intensity curves (TICs), and 107 radiomic features were derived. Statistical analyses compared R vs. PR/NR. At PRT, 79% of R displayed a "Capsular" morphology (P = 1.49 × 10-7), and 100% demonstrated a TIC-type II (P = 8.32 × 10-7). 80% of PR showed "Unipolar" morphology (P = 1.03 × 10-5), and 60% expressed a TIC-type V (P = 0.06). Semiquantitative wash-in rate (WiR) was able to separate R vs. PR/NR (P = 0.0078). The WiR radiomics displayed significant differences in the first_order_10 percentile (P = 0.0178) comparing R vs. PR/NR at PRT. The PWI/DCE TIC-type II curve, low WiR, and "Capsular" enhancement represent PRT patterns typically observed in successfully treated UPS and demonstrate potential for UPS treatment response assessment.

The role of multiparametric MRI in predicting lymphovascular invasion in breast cancer patients.

Background: This study aims to investigate the efficacy of multifactorial MRI in diagnosing breast cancer, specifically in the context of predicting lymphovascular invasion (LVI).Materials & methods: The patients were stratified into two groups: the primary group (100 patients) and the validation group (100 patients), based on essential characteristics. Multifactorial MRI, encompassing tumor size evaluation, diffusion coefficient assessment and dynamic contrast enhancement, was employed for patient examination.Results: Statistically significant differences were observed in tumor size, diffusion coefficient and dynamic contrast enhancement between groups with LVI (LVI+) and those without (LVI-). Key parameters were identified for predicting the degree of invasion.Conclusion: The results affirm the effectiveness of multifactorial MRI in forecasting LVI.

[Box: see text].

Effect of patient characteristics on aortic attenuation in iodinated contrast-enhanced Abdominopelvic CT: A retrospective study.

INTRODUCTION: Contrast Enhanced Computed Tomography (CECT) abdomen and pelvis is a common imaging procedure. Hospitals typically follow fixed protocols of contrast volume administration for triple-phase CECT abdomen and pelvis scans and have found that patients are either underdosed or overdosed with respect to their body habitus. The aim of the study was to correlate different patient characteristics such as Total body weight (TBW), Lean Body Mass (LBM), Body Mass Index (BMI), Body Surface Area (BSA) and Blood Volume (BV) with aortic enhancement in the arterial and portal venous phases for CECT Abdomen and pelvis. METHODS: A total of 106 patients who underwent triple-phase CECT abdomen & pelvis were retrospectively studied. A circular region-of-interest (ROI) of 100 mm2 was positioned on descending aorta for unenhanced, arterial, and portal venous phases to measure the aortic enhancement in Hounsfield's units. Measure of contrast attenuation (ΔH) was calculated from the difference of CT values on unenhanced images and contrast images. Correlation analysis was performed to evaluate the relation of patient body characteristics with aortic enhancement. RESULTS: Correlation analysis revealed that BMI exhibited the least correlation when compared to the other characteristics in both arterial (r = -0.3; p = 0.002) and portovenous phases (r = -0.35; p < 0.001) whereas TBW, LBW, BSA and BV reported moderate inverse correlations. BV was found to be the strongest of all characteristics under linear regression. CONCLUSION: The study supports the use of protocols that adjust contrast volume to either TBW, LBW, BSA, or BV for CT abdomen and pelvis scan. IMPLICATION OF PRACTICE: The right body parameter ensures optimal contrast enhancement, improving the visualization of anatomical structures and helps in adapting tailored contrast injection protocols.

Value of Dynamic Contrast-Enhanced MRI for Grade Group Prediction in Prostate Cancer: A Radiomics Pilot Study.

RATIONALE AND OBJECTIVES: To determine the role of dynamic contrast-enhanced (DCE) MRI-radiomics in predicting the International Society of Urological Pathology Grade Group (ISUP-GG) in therapy-naïve prostate cancer (PCa) patients. MATERIALS AND METHODS: In this ethics review board-approved retrospective study on two prospective clinical trials between 2017 and 2020, 73 men with suspected/confirmed PCa were included. All participants underwent multiparametric MRI. On MRI, dominant lesions (per PI-RADS) were identified. DCE-MRI radiomic features were extracted from the segmented volumes following the image biomarker standardisation initiative (IBSI) guidelines through 14 time points. Histopathology evaluation on the cognitive-fusion targeted biopsies was set as the reference standard. Univariate regression was done to evaluate potential predictors across all calculated features. Random forest imputation was used for multivariate modelling. RESULTS: 73 index lesions were reviewed. Histopathology revealed 28, 16, 13 and 16 lesions with ISUP-GG-Negative/1/2, ISUP-GG-3, ISUP-GG-4 and ISUP-GG-5, respectively. From the extracted features, total lesion enhancement (TLE), minimum enhancement intensity and Grey-Level Run Length Matrix (GLRLM) were the most significantly different parameters among ISUP-GGs (Neg/1/2 vs 3/4 vs 5). 16 features with significant cross-sectional associations with ISUP-GGs entered the multivariate analysis. The final DCE partitioning model used only four features (lesion sphericity, TLE, GLRLM and Grey-Level Zone Length Matrix). For the binarized diagnosis (ISUP-GG≤2 vs ISUP-GG>2), the accuracy reached 81%. CONCLUSION: DCE-MRI radiomics might be used as a non-invasive tool for aiding pathological grade group prediction in therapy-naïve PCa patients, potentially adding complementary information to PI-RADS for supporting tailored diagnostic pathways and treatment planning.

Diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions in CT and MRI: a systematic review and meta-analysis of diagnostic test accuracy (DTA) studies.

OBJECTIVE: To perform a systematic review and meta-analysis of the diagnostic performance of contrast enhancement to differentiate benign and malignant renal lesions using CT and MRI. MATERIAL AND METHODS: A systematic literature search of databases was performed between January 1, 1980 and September 26, 2022. We included studies reporting the accuracy of CE thresholds on CT and MRI indeterminate renal lesions, with pathologic examination and follow-up as the reference standard. Studies meeting the inclusion criteria underwent quality assessment with the Cochrane recommendation for diagnostic accuracy study Quality Assessment 2. We excluded studies with high risk of bias. Summary estimates of diagnostic performance were obtained with the bivariate Bayesian model for CT and MRI. Effects of different thresholds and index test modalities were investigated through subgroup analysis. RESULTS: Eleven studies (1372 patients) using CT and six studies (218 patients) using MRI were included. Of the eleven studies, 15 parts from 9 studies were considered for the CT meta-analysis, and 6 parts from 3 studies for the MRI meta-analysis. Diagnostic performance meta-analysis on enhancement found a 96% summary sensitivity (95% CI 92, 98) and a 92% summary specificity (95% CI 85, 96) in 2056 renal lesions for CT; and 82% summary sensitivity (95% CI 65, 89) and an 89% summary specificity (95% CI 77, 95) in 634 lesions for MRI. CONCLUSION: CT and MRI have high accuracy to determine enhancement and classify renal lesions, and both modalities can be used with confidence for this purpose. There are still some controversies about the optimal thresholds. Future research should evaluate outcomes and decision-making pathways to determine whether basing clinical decisions on a specific threshold on CT and MRI would do more harm than good.

A Detailed Clinical Case of Localized Prostate Tumors Treated with Nanoparticle-Assisted Sub-Ablative Laser Ablation.

AuroLase® Therapy-a nanoparticle-enabled focal therapy-has the potential to safely and effectively treat localized prostate cancer (PCa), preserving baseline functionality. This article presents a detailed case of localized PCa treated with AuroLase, providing insight on expectations from the diagnosis of PCa to one year post-treatment. AuroLase Therapy is a two-day treatment consisting of a systemic infusion of gold nanoshells (~150-nm hydrodynamic diameter) on Day 1, and sub-ablative laser treatment on Day 2. Multiparametric MRI (mpMRI) was used for tumor visualization, treatment planning, and therapy response assessment. The PCa was targeted with a MR/Ultrasound-fusion (MR/US) transperineal approach. Successful treatment was confirmed at 6 and 12 months post-treatment by the absence of disease in MR/US targeted biopsies. On the mpMRI, confined void space was evident, an indication of necrotic tissues encompassing the treated lesion, which was completely resolved at 12 months, forming a band-like scar with no evidence of recurrent tumor. The patient's urinary and sexual functions were unchanged. During the one-year follow-up, changes on the DCE sequence and in the Ktrans and ADC values assist in qualitatively and quantitatively evaluating tissue changes. The results highlight the potential of gold-nanoparticle-enabled sub-ablative laser treatment to target and control localized PCa, maintain quality of life, and preserve baseline functionality.

Automatic vessel attenuation measurement for quality control of contrast-enhanced CT: Validation on the portal vein.

BACKGROUND: Adequate image enhancement of organs and blood vessels of interest is an important aspect of image quality in contrast-enhanced computed tomography (CT). There is a need for an objective method for evaluation of vessel contrast that can be automatically and systematically applied to large sets of CT exams. PURPOSE: The purpose of this work was to develop a method to automatically segment and measure attenuation Hounsfield Unit (HU) in the portal vein (PV) in contrast-enhanced abdomen CT examinations. METHODS: Input CT images were processed by a vessel enhancing filter to determine candidate PV segmentations. Multiple machine learning (ML) classifiers were evaluated for classifying a segmentation as corresponding to the PV based on segmentation shape, location, and intensity features. A public data set of 82 contrast-enhanced abdomen CT examinations was used to train the method. An optimal ML classifier was selected by training and tuning on 66 out of the 82 exams (80% training split) in the public data set. The method was evaluated in terms of segmentation classification accuracy and PV attenuation measurement accuracy, compared to manually determined ground truth, on a test set of the remaining 16 exams (20% test split) held out from public data set. The method was further evaluated on a separate, independently collected test set of 21 examinations. RESULTS: The best classifier was found to be a random forest, with a precision of 0.892 in the held-out test set to correctly identify the PV from among the input candidate segmentations. The mean absolute error of the measured PV attenuation relative to ground truth manual measurement was 13.4 HU. On the independent test set, the overall precision decreased to 0.684. However, the PV attenuation measurement remained relatively accurate with a mean absolute error of 15.2 HU. CONCLUSIONS: The method was shown to accurately measure PV attenuation over a large range of attenuation values, and was validated in an independently collected dataset. The method did not require time-consuming manual contouring to supervise training. The method may be applied to systematic quality control of contrast-enhanced CT examinations.

Deep learning image reconstruction for low-kiloelectron volt virtual monoenergetic images in abdominal dual-energy CT: medium strength provides higher lesion conspicuity.

BACKGROUND: The best settings of deep learning image reconstruction (DLIR) algorithm for abdominal low-kiloelectron volt (keV) virtual monoenergetic imaging (VMI) have not been determined. PURPOSE: To determine the optimal settings of the DLIR algorithm for abdominal low-keV VMI. MATERIAL AND METHODS: The portal-venous phase computed tomography (CT) scans of 109 participants with 152 lesions were reconstructed into four image series: VMI at 50 keV using adaptive statistical iterative reconstruction (Asir-V) at 50% blending (AV-50); and VMI at 40 keV using AV-50 and DLIR at medium (DLIR-M) and high strength (DLIR-H). The signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of nine anatomical sites were calculated. Noise power spectrum (NPS) using homogenous region of liver, and edge rise slope (ERS) at five edges were measured. Five radiologists rated image quality and diagnostic acceptability, and evaluated the lesion conspicuity. RESULTS: The SNR and CNR values, and noise and noise peak in NPS measurements, were significantly lower in DLIR images than AV-50 images in all anatomical sites (all P < 0.001). The ERS values were significantly higher in 40-keV images than 50-keV images at all edges (all P < 0.001). The differences of the peak and average spatial frequency among the four reconstruction algorithms were significant but relatively small. The 40-keV images were rated higher with DLIR-M than DLIR-H for diagnostic acceptance (P < 0.001) and lesion conspicuity (P = 0.010). CONCLUSION: DLIR provides lower noise, higher sharpness, and more natural texture to allow 40 keV to be a new standard for routine VMI reconstruction for the abdomen and DLIR-M gains higher diagnostic acceptance and lesion conspicuity rating than DLIR-H.

Novel Gd-DTPA-peptide for targeted breast tumor magnetic resonance imaging.

The prevalence of breast cancer underscores the imperative for early diagnosis in guiding treatment decisions. This study introduces a novel contrast agent, Gd-DTPA-VGB3, derived from the peptide VGB3 targeting vascular endothelial growth factor receptor-1 (VEGFR1) and VEGFR2, to enhance the contrast of conventional drug Magnevist in breast tumor MRI. The MRI contrast agent was synthesized on rink amide resin via Fmoc strategy, incorporating amino acids, and coupling to diethylenetriaminepentaacetic acid (DTPA). Gadolinium (Gd)-DTPA-VGB3 displayed specific binding to VEGFR1/2 in a displacement binding assay. Gd-DTPA-VGB3 exhibited minimal cytotoxicity to normal MCF-10 cells while inhibiting 4T1 mammary carcinoma cell proliferation. Compared to Magnevist, Gd-DTPA-VGB3 demonstrated a 2.8-fold increase in contrast-to-noise ratio (CNR) (355 vs. 125). Gd-DTPA-VGB3 exhibited enhanced accumulation in 4T1 tumor-bearing mice, resulting in significant signal intensity improvement. The findings highlight Gd-DTPA-VGB3's specific binding to VEGFRs, substantiating its potential as a candidate for enhancing MRI contrast in breast cancer diagnostics.

A comparative analysis of deep learning and hybrid iterative reconstruction algorithms with contrast-enhancement-boost post-processing on the image quality of indirect computed tomography venography of the lower extremities.

PURPOSE: To examine whether there is a significant difference in image quality between the deep learning reconstruction (DLR [AiCE, Advanced Intelligent Clear-IQ Engine]) and hybrid iterative reconstruction (HIR [AIDR 3D, adaptive iterative dose reduction three dimensional]) algorithms on the conventional enhanced and CE-boost (contrast-enhancement-boost) images of indirect computed tomography venography (CTV) of lower extremities. MATERIALS AND METHODS: In this retrospective study, seventy patients who underwent CTV from June 2021 to October 2022 to assess deep vein thrombosis and varicose veins were included. Unenhanced and enhanced images were reconstructed for AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images were obtained using subtraction software. Objective and subjective image qualities were assessed, and radiation doses were recorded. RESULTS: The CT values of the inferior vena cava (IVC), femoral vein ( FV), and popliteal vein (PV) in the CE-boost images were approximately 1.3 (1.31-1.36) times higher than in those of the enhanced images. There were no significant differences in mean CT values of IVC, FV, and PV between AIDR 3D and AiCE, AIDR 3D-boost and AiCE-boost images. Noise in AiCE, AiCE-boost images was significantly lower than in AIDR 3D and AIDR 3D-boost images ( P < 0.05). The SNR (signal-to-noise ratio), CNR (contrast-to-noise ratio), and subjective scores of AiCE-boost images were the highest among 4 groups, surpassing AiCE, AIDR 3D, and AIDR 3D-boost images (all P < 0.05). CONCLUSION: In indirect CTV of the lower extremities images, DLR with the CE-boost technique could decrease the image noise and improve the CT values, SNR, CNR, and subjective image scores. AiCE-boost images received the highest subjective image quality score and were more readily accepted by radiologists.

Microarray Images Contrast Enhancement and Gridding Using Genetic Algorithm.

Background: Microarray is a sophisticated tool that concurrently analyzes the expression levels of thousands of genes, giving scientists an overview of DNA and RNA study. This procedure is divided into three stages: contact with biological samples, data extraction, and data analysis. Because expression levels are disclosed by the interplay of light with fluorescent markers, the data extraction stage relies on image processing methods. To extract quantitative information from the microarray image (MAI), four steps of preprocessing, gridding, segmentation, and intensity quantification are required. During the generation of MAIs, a large number of error-prone processes occur, leading to structural problems and reduced quality in the resulting data, affecting the identification of expressed genes. Methods: In this article, the first stage has been examined. In the preprocessing stage, the contrast of the images is first enhanced using the genetic algorithm, then the source noises that appear as small artifacts are removed using morphology, and finally, to confirm the effect of the contrast enhancement (CE) on the main stages of microarray data processing, gridding is checked on complementary deoxyribonucleic acid MAIs. Results: The comparison of the obtained results with an adaptive histogram equalization (AHE) and multi-decomposition histogram equalization (M-DHE) methods shows the superiority and efficiency of the proposed method. For example, the image contrast of the Genomic Medicine Research Center Laboratory dataset is 3.24, which is 42.91 with the proposed method and 13.48 and 32.40 with the AHE and M-DHE methods, respectively. Conclusions: The performance of the proposed methods for CE is evaluated on 3 databases and a general conclusion is obtained as to which CE method is more suitable for each dataset.

Contrast enhancement boost improves the image quality of CT angiography derived from 80-kVp cerebral CT perfusion data.

RATIONALE AND OBJECTIVE: To investigate the impact of the contrast enhancement boost (CE-boost) technique on the image quality of CT angiography (CTA) derived from 80-kVp cerebral CT perfusion (CTP) data, and to compare it with conventional CTApeak as well as other currently employed methods for enhancing CTA images, such as CTAtMIP and CTAtAve extracted from CTP. MATERIALS AND METHODS: The data of forty-seven patients who underwent CTP at 80 kVp were retrospectively collected. Four sets of images: CTApeak, CTAtMIP, CTAtAve, and CE-boost images. The CTApeak image represents the arterial phase at its peak value, captured as a single time point. CTAtMIP and CTAtAve are 4D CTA images that provide maximum density projection and average images from the three most prominent time points. CE-boost is a postprocessing technique used to enhance contrast in the arterial phase at its peak value. We compared the average CT value, standard deviation (SD), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) of the internal carotid artery (ICA) and basilar artery (BA) among the four groups. Image quality was evaluated using a 5-point scale. RESULTS: The CE-boost demonstrated and CNR in the ICA and BA (all p < 0.001). Compared with the other three CTA reconstructed images, the CE-boost images had the best subjective image quality, with the highest scores of 4.77 ± 0.43 and 4.87 ± 0.34 for each reader (all p < 0.001). CONCLUSION: Compared with other currently used techniques,CE-boost enhances the image quality of CTA derived from 80-kVp CTP data, leading to improved visualization of intracranial arteries.

Coronary artery wall contrast enhancement imaging impact on disease activity assessment in IgG4-RD: a direct marker of coronary involvement.

BACKGROUND: Coronary artery wall contrast enhancement (CE) has been applied to non-invasive visualization of changes to the coronary artery wall in systemic lupus erythematosus (SLE). This study investigated the feasibility of quantifying CE to detect coronary involvement in IgG4-related disease (IgG4-RD), as well as the influence on disease activity assessment. METHODS: A total of 93 subjects (31 IgG4-RD; 29 SLE; 33 controls) were recruited in the study. Coronary artery wall imaging was performed in a 3.0 T MRI scanner. Serological markers and IgG4-RD Responder Index (IgG4-RD-RI) scores were collected for correlation analysis. RESULTS: Coronary wall CE was observed in 29 (94 %) IgG4-RD patients and 22 (76 %) SLE patients. Contrast-to-noise ratio (CNR) and total CE area were significantly higher in patient groups compared to controls (CNR: 6.1 ± 2.7 [IgG4-RD] v. 4.2 ± 2.3 [SLE] v. 1.9 ± 1.5 [control], P < 0.001; Total CE area: 3.0 [3.0-6.6] v. 1.7 [1.5-2.6] v. 0.3 [0.3-0.9], P < 0.001). In the IgG4-RD group, CNR and total CE area were correlated with the RI (CNR: r = 0.55, P = 0.002; total CE area: r = 0.39, P = 0.031). RI´ scored considering coronary involvement by CE, differed significantly from RI scored without consideration of CE (RI v. RI´: 15 ± 6 v. 16 ± 6, P < 0.001). CONCLUSIONS: Visualization and quantification of CMR coronary CE by CNR and total CE area could be utilized to detect subclinical and clinical coronary wall involvement, which is prevalent in IgG4-RD. The potential inclusion of small and medium-sized vessel involvements in the assessment of disease activity in IgG4-RD is worthy of further investigation.