The discerning influence of dynamic contrast-enhanced MRI in anticipating molecular subtypes of breast cancer through the artistry of artificial intelligence - a narrative review.

Radio genomics is an exciting new area that uses diagnostic imaging to discover genetic features of diseases. In this review, we carefully examined existing literature to evaluate the role of artificial intelligence (AI) and machine learning (ML) on dynamic contrastenhanced MRI (DCE-MRI) data to distinguish molecular subtypes of breast cancer (BC). Implications to noninvasive assessment of molecular subtype include reduction in procedure risks, tailored treatment approaches, ability to examine entire lesion, follow-up of tumour biology in response to treatment and evaluation of treatment resistance and failure secondary to tumour heterogeneity. Recent studies leverage radiomics and AI on DCE-MRI data for reliable, non-invasive breast cancer subtype classification. This review recognizes the potential of AI to predict the molecular subtypes of breast cancer non-invasively.

Enhancing pathological complete response prediction in breast cancer: the role of dynamic characterization of DCE-MRI and its association with tumor heterogeneity.

BACKGROUND: Early prediction of pathological complete response (pCR) is important for deciding appropriate treatment strategies for patients. In this study, we aimed to quantify the dynamic characteristics of dynamic contrast-enhanced magnetic resonance images (DCE-MRI) and investigate its value to improve pCR prediction as well as its association with tumor heterogeneity in breast cancer patients. METHODS: The DCE-MRI, clinicopathologic record, and full transcriptomic data of 785 breast cancer patients receiving neoadjuvant chemotherapy were retrospectively included from a public dataset. Dynamic features of DCE-MRI were computed from extracted phase-varying radiomic feature series using 22 CAnonical Time-sereis CHaracteristics. Dynamic model and radiomic model were developed by logistic regression using dynamic features and traditional radiomic features respectively. Various combined models with clinical factors were also developed to find the optimal combination and the significance of each components was evaluated. All the models were evaluated in independent test set in terms of area under receiver operating characteristic curve (AUC). To explore the potential underlying biological mechanisms, radiogenomic analysis was implemented on patient subgroups stratified by dynamic model to identify differentially expressed genes (DEGs) and enriched pathways. RESULTS: A 10-feature dynamic model and a 4-feature radiomic model were developed (AUC = 0.688, 95%CI: 0.635-0.741 and AUC = 0.650, 95%CI: 0.595-0.705) and tested (AUC = 0.686, 95%CI: 0.594-0.778 and AUC = 0.626, 95%CI: 0.529-0.722), with the dynamic model showing slightly higher AUC (train p = 0.181, test p = 0.222). The combined model of clinical, radiomic, and dynamic achieved the highest AUC in pCR prediction (train: 0.769, 95%CI: 0.722-0.816 and test: 0.762, 95%CI: 0.679-0.845). Compared with clinical-radiomic combined model (train AUC = 0.716, 95%CI: 0.665-0.767 and test AUC = 0.695, 95%CI: 0.656-0.714), adding the dynamic component brought significant improvement in model performance (train p < 0.001 and test p = 0.005). Radiogenomic analysis identified 297 DEGs, including CXCL9, CCL18, and HLA-DPB1 which are known to be associated with breast cancer prognosis or angiogenesis. Gene set enrichment analysis further revealed enrichment of gene ontology terms and pathways related to immune system. CONCLUSION: Dynamic characteristics of DCE-MRI were quantified and used to develop dynamic model for improving pCR prediction in breast cancer patients. The dynamic model was associated with tumor heterogeniety in prognostic-related gene expression and immune-related pathways.

Diagnostic accuracy of contrast-enhanced computed tomography in assessing bone invasion in patients with oral squamous cell carcinoma.

OBJECTIVES: This study aimed to evaluate the diagnostic accuracy of contrast-enhanced computed tomography (CT) in detecting bone invasion in oral squamous cell carcinoma (OSCC) patients and to explore clinicopathological factors associated with its reliability. MATERIALS AND METHODS: 417 patients underwent preoperative contrast-enhanced CT followed by radical surgery. The presence or absence of bone invasion served as the outcome variable, with histopathologic examination of the resection specimen considered the gold standard. Statistical analyses, comprising correlation analyses and the determination of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were conducted. RESULTS: CT exhibited 76.85% sensitivity, 82.20% specificity, 47.14% PPV, and 89.67% NPV. False-positive and false-negative rates were 11.27% and 5.99%, respectively. Artifacts affected assessment in 44 patients, but not in those with bone invasion. Tumor size, depth of invasion (DOI), tumor localization at the upper jaw, lymphatic invasion, and perineural invasion correlated with incorrect identification of bone invasion (Chi-square, p < 0.05). CONCLUSIONS: Despite utilizing thin-section CT, notable false-positive and false-negative results persisted. Patients with T3 tumors, DOI ≥ 10 mm, or upper jaw tumors are at higher risk for misidentification of bone invasion. Combining multiple methods may enhance diagnostic accuracy, and the integration of artificial intelligence or tracking electrolyte disturbances by tumor depth profiling shows promise for further assessment of bone invasion before histopathology. CLINICAL RELEVANCE: Surgeons should consider these insights when planning tumor resection. Supplementary imaging may be warranted in cases with high risk factors for misidentification. Further methodological advancements are crucial for enhancing diagnostic precision.

Deep Learning Assessment of Small Renal Masses at Contrast-enhanced Multiphase CT.

Background Accurate characterization of suspicious small renal masses is crucial for optimized management. Deep learning (DL) algorithms may assist with this effort. Purpose To develop and validate a DL algorithm for identifying benign small renal masses at contrast-enhanced multiphase CT. Materials and Methods Surgically resected renal masses measuring 3 cm or less in diameter at contrast-enhanced CT were included. The DL algorithm was developed by using retrospective data from one hospital between 2009 and 2021, with patients randomly allocated in a training and internal test set ratio of 8:2. Between 2013 and 2021, external testing was performed on data from five independent hospitals. A prospective test set was obtained between 2021 and 2022 from one hospital. Algorithm performance was evaluated by using the area under the receiver operating characteristic curve (AUC) and compared with the results of seven clinicians using the DeLong test. Results A total of 1703 patients (mean age, 56 years ± 12 [SD]; 619 female) with a single renal mass per patient were evaluated. The retrospective data set included 1063 lesions (874 in training set, 189 internal test set); the multicenter external test set included 537 lesions (12.3%, 66 benign) with 89 subcentimeter (≤1 cm) lesions (16.6%); and the prospective test set included 103 lesions (13.6%, 14 benign) with 20 (19.4%) subcentimeter lesions. The DL algorithm performance was comparable with that of urological radiologists: for the external test set, AUC was 0.80 (95% CI: 0.75, 0.85) versus 0.84 (95% CI: 0.78, 0.88) (P = .61); for the prospective test set, AUC was 0.87 (95% CI: 0.79, 0.93) versus 0.92 (95% CI: 0.86, 0.96) (P = .70). For subcentimeter lesions in the external test set, the algorithm and urological radiologists had similar AUC of 0.74 (95% CI: 0.63, 0.83) and 0.81 (95% CI: 0.68, 0.92) (P = .78), respectively. Conclusion The multiphase CT-based DL algorithm showed comparable performance with that of radiologists for identifying benign small renal masses, including lesions of 1 cm or less. Published under a CC BY 4.0 license. Supplemental material is available for this article.

A novel model incorporating quantitative contrast-enhanced ultrasound into PI-RADSv2-based nomogram detecting clinically significant prostate cancer.

The diagnostic accuracy of clinically significant prostate cancer (csPCa) of Prostate Imaging Reporting and Data System version 2 (PI-RADSv2) is limited by subjectivity in result interpretation and the false positive results from certain similar anatomic structures. We aimed to establish a new model combining quantitative contrast-enhanced ultrasound, PI-RADSv2, clinical parameters to optimize the PI-RADSv2-based model. The analysis was conducted based on a data set of 151 patients from 2019 to 2022, multiple regression analysis showed that prostate specific antigen density, age, PI-RADSv2, quantitative parameters (rush time, wash-out area under the curve) were independent predictors. Based on these predictors, we established a new predictive model, the AUCs of the model were 0.910 and 0.879 in training and validation cohort, which were higher than those of PI-RADSv2-based model (0.865 and 0.821 in training and validation cohort). Net Reclassification Index analysis indicated that the new predictive model improved the classification of patients. Decision curve analysis showed that in most risk probabilities, the new predictive model improved the clinical utility of PI-RADSv2-based model. Generally, this new predictive model showed that quantitative parameters from contrast enhanced ultrasound could help to improve the diagnostic performance of PI-RADSv2 based model in detecting csPCa.

Surface ligand-regulated renal clearance of MRI/SPECT dual-modality nanoprobes for tumor imaging.

BACKGROUND: The general sluggish clearance kinetics of functional inorganic nanoparticles tend to raise potential biosafety concerns for in vivo applications. Renal clearance is a possible elimination pathway for functional inorganic nanoparticles delivered through intravenous injection, but largely depending on the surface physical chemical properties of a given particle apart from its size and shape. RESULTS: In this study, three small-molecule ligands that bear a diphosphonate (DP) group, but different terminal groups on the other side, i.e., anionic, cationic, and zwitterionic groups, were synthesized and used to modify ultrasmall Fe3O4 nanoparticles for evaluating the surface structure-dependent renal clearance behaviors. Systematic studies suggested that the variation of the surface ligands did not significantly increase the hydrodynamic diameter of ultrasmall Fe3O4 nanoparticles, nor influence their magnetic resonance imaging (MRI) contrast enhancement effects. Among the three particle samples, Fe3O4 nanoparticle coated with zwitterionic ligands, i.e., Fe3O4@DMSA, exhibited optimal renal clearance efficiency and reduced reticuloendothelial uptake. Therefore, this sample was further labeled with 99mTc through the DP moieties to achieve a renal-clearable MRI/single-photon emission computed tomography (SPECT) dual-modality imaging nanoprobe. The resulting nanoprobe showed satisfactory imaging capacities in a 4T1 xenograft tumor mouse model. Furthermore, the biocompatibility of Fe3O4@DMSA was evaluated both in vitro and in vivo through safety assessment experiments. CONCLUSIONS: We believe that the current investigations offer a simple and effective strategy for constructing renal-clearable nanoparticles for precise disease diagnosis.

Comparing Sonazoid contrast-enhanced ultrasound to contrast-enhanced CT and MRI for differentially diagnosing renal lesions: a prospective multicenter study.

PURPOSE: To evaluate the diagnostic performance of contrast-enhanced (CE) ultrasound using Sonazoid (SNZ-CEUS) by comparing with contrast-enhanced computed tomography (CE-CT) and contrast-enhanced magnetic resonance imaging (CE-MRI) for differentiating benign and malignant renal masses. MATERIALS AND METHODS: 306 consecutive patients (from 7 centers) with renal masses (40 benign tumors, 266 malignant tumors) diagnosed by both SNZ-CEUS, CE-CT or CE-MRI were enrolled between September 2020 and February 2021. The examinations were performed within 7 days, but the sequence was not fixed. Histologic results were available for 301 of 306 (98.37%) lesions and 5 lesions were considered benign after at least 2 year follow-up without change in size and image characteristics. The diagnostic performances were evaluated by sensitivity, specificity, positive predictive value, negative predictive value, and compared by McNemar's test. RESULTS: In the head-to-head comparison, SNZ-CEUS and CE-MRI had comparable sensitivity (95.60 vs. 94.51%, P = 0.997), specificity (65.22 vs. 73.91%, P = 0.752), positive predictive value (91.58 vs. 93.48%) and negative predictive value (78.95 vs. 77.27%); SNZ-CEUS and CE-CT showed similar sensitivity (97.31 vs. 96.24%, P = 0.724); however, SNZ-CEUS had relatively lower than specificity than CE-CT (59.09 vs. 68.18%, P = 0.683). For nodules > 4 cm, CE-MRI demonstrated higher specificity than SNZ-CEUS (90.91 vs. 72.73%, P = 0.617) without compromise the sensitivity. CONCLUSIONS: SNZ-CEUS, CE-CT, and CE-MRI demonstrate desirable and comparable sensitivity for the differentiation of renal mass. However, the specificity of all three imaging modalities is not satisfactory. SNZ-CEUS may be a suitable alternative modality for patients with renal dysfunction and those allergic to gadolinium or iodine-based agents.

MRI Scoring Systems for Predicting Isocitrate Dehydrogenase Mutation and Chromosome 1p/19q Codeletion in Adult-type Diffuse Glioma Lacking Contrast Enhancement.

Background According to 2021 World Health Organization criteria, adult-type diffuse gliomas include glioblastoma, isocitrate dehydrogenase (IDH)-wildtype; oligodendroglioma, IDH-mutant and 1p/19q-codeleted; and astrocytoma, IDH-mutant, even when contrast enhancement is lacking. Purpose To develop and validate simple scoring systems for predicting IDH and subsequent 1p/19q codeletion status in gliomas without contrast enhancement using standard clinical MRI sequences. Materials and Methods This retrospective study included adult-type diffuse gliomas lacking contrast at contrast-enhanced MRI from two tertiary referral hospitals between January 2012 and April 2022 with diagnoses confirmed at pathology. IDH status was predicted primarily by using T2-fluid-attenuated inversion recovery (FLAIR) mismatch sign, followed by 1p/19q codeletion prediction. A visual rating of MRI features, apparent diffusion coefficient (ADC) ratio, and relative cerebral blood volume was measured. Scoring systems were developed through univariable and multivariable logistic regressions and underwent calibration and discrimination, including internal and external validation. Results For the internal validation cohort, 237 patients were included (mean age, 44.4 years ± 14.4 [SD]; 136 male patients; 193 patients in IDH prediction and 163 patients in 1p/19q prediction). For the external validation cohort, 35 patients were included (46.1 years ± 15.3; 20 male patients; 28 patients in IDH prediction and 24 patients in 1p/19q prediction). The T2-FLAIR mismatch sign demonstrated 100% specificity and 100% positive predictive value for IDH mutation. IDH status prediction scoring system for tumors without mismatch sign included age, ADC ratio, and morphologic characteristics, whereas 1p/19q codeletion prediction for IDH-mutant gliomas included ADC ratio, cortical involvement, and mismatch sign. For IDH status and 1p/19q codeletion prediction, bootstrap-corrected areas under the receiver operating characteristic curve were 0.86 (95% CI: 0.81, 0.90) and 0.73 (95% CI: 0.65, 0.81), respectively, whereas at external validation they were 0.99 (95% CI: 0.98, 1.0) and 0.88 (95% CI: 0.63, 1.0). Conclusion The T2-FLAIR mismatch sign and scoring systems using standard clinical MRI predicted IDH and 1p/19q codeletion status in gliomas lacking contrast enhancement. © RSNA, 2024 Supplemental material is available for this article. See also the editorial by Badve and Hodges in this issue.

Predicting response of hepatoblastoma primary lesions to neoadjuvant chemotherapy through contrast-enhanced computed tomography radiomics.

OBJECTIVE: To investigate the clinical value of contrast-enhanced computed tomography (CECT) radiomics for predicting the response of primary lesions to neoadjuvant chemotherapy in hepatoblastoma. METHODS: Clinical and CECT imaging data were retrospectively collected from 116 children with hepatoblastoma who received neoadjuvant chemotherapy. Tumor response was assessed according to the Response Evaluation Criteria in Solid Tumors (RECIST). Subsequently, they were randomly stratified into a training cohort and a test cohort in a 7:3 ratio. The clinical model was constructed using univariate and multivariate logistic regression, while the radiomics model was developed based on selected radiomics features employing the support vector machine algorithm. The combined clinical-radiomics model incorporated both clinical and radiomics features. RESULTS: The area under the curve (AUC) for the clinical, radiomics, and combined models was 0.704 (95% CI: 0.563-0.845), 0.830 (95% CI: 0.704-0.959), and 0.874 (95% CI: 0.768-0.981) in the training cohort, respectively. In the validation cohort, the combined model achieved the highest mean AUC of 0.830 (95% CI 0.616-0.999), with a sensitivity, specificity, accuracy, precision, and f1 score of 72.0%, 81.1%, 78.5%, 57.2%, and 63.5%, respectively. CONCLUSION: CECT radiomics has the potential to predict primary lesion response to neoadjuvant chemotherapy in hepatoblastoma.

Score based on contrast-enhanced ultrasound predict central lymph node metastasis in papillary thyroid cancer.

Objectives: To investigate the association between contrast-enhanced ultrasound (CEUS) features of PTC and central lymph node metastasis (CLNM) and to develop a predictive model for the preoperative identification of CLNM. Methods: This retrospective study evaluated 750 consecutive patients with PTC from August 2020 to April 2023. Conventional ultrasound and qualitative CEUS features were analyzed for the PTC with or without CLNM using univariate and multivariate logistic regression analysis. A nomogram integrating the predictors was constructed to identify CLNM in PTC. The predictive nomogram was validated using a validation cohort. Results: A total of 684 patients were enrolled. The 495 patients in training cohort were divided into two groups according to whether they had CLNM (pCLNM, n= 191) or not (nCLNM, n= 304). There were significant differences in terms of tumor size, shape, echogenic foci, enhancement direction, peak intensity, and score based on CEUS TI-RADS between the two groups. Independent predictive US features included irregular shape, larger tumor size (≥ 1.0cm), and score. Nomogram integrating these predictive features showed good discrimination and calibration in both training and validation cohort with an AUC of 0.72 (95% CI: 0.68, 0.77) and 0.79 (95% CI: 0.72, 0.85), respectively. In the subgroup with larger tumor size, age ≤ 35 years, irregular shape, and score > 6 were independent risk factors for CLNM. Conclusion: The score based on preoperative CEUS features of PTC may help to identify CLNM. The nomogram developed in this study provides a convenient and effective tool for clinicians to determine an optimal treatment regimen for patients with PTC.

PDZK1 is correlated with DCE-MRI perfusion parameters in high-grade glioma.

OBJECTIVE: This study investigated the relationship between PDZK1 expression and Dynamic Contrast-Enhanced MRI (DCE-MRI) perfusion parameters in High-Grade Glioma (HGG). METHODS: Preoperative DCE-MRI scanning was performed on 80 patients with HGG to obtain DCE perfusion transfer coefficient (Ktrans), vascular plasma volume fraction (vp), extracellular volume fraction (ve), and reverse transfer constant (kep). PDZK1 in HGG patients was detected, and its correlation with DCE-MRI perfusion parameters was assessed by the Pearson method. An analysis of Cox regression was performed to determine the risk factors affecting survival, while Kaplan-Meier and log-rank tests to evaluate PDZK1's prognostic significance, and ROC curve analysis to assess its diagnostic value. RESULTS: PDZK1 was upregulated in HGG patients and predicted poor overall survival and progression-free survival. Moreover, PDZK1 expression distinguished grade III from grade IV HGG. PDZK1 expression was positively correlated with Ktrans 90, and ve_90, and negatively correlated with kep_max, and kep_90. CONCLUSION: PDZK1 is upregulated in HGG, predicts poor survival, and differentiates tumor grading in HGG patients. PDZK1 expression is correlated with DCE-MRI perfusion parameters.

Dysregulation of ferroptosis may participate in the mitigating effect of CoCl2 on contrast-induced nephropathy.

BACKGROUND: Contrast agents can directly or indirectly induce renal tubular ischemia and hypoxic damage. Given that cobalt chloride (CoCl2) can protect renal tubules, the protective effect and potential mechanism of action of CoCl2 on contrast-induced nephropathy (CIN) warrant investigation. METHODS: A CIN mouse model was established to determine the protective effect of CoCl2 on renal injury in vivo. Then, TMT-based proteomics was performed to determine the differentially expressed proteins (DEPs), following which, enrichment analyses of gene ontology and the KEGG pathway were performed. In vitro, a CIN model was constructed with renal tubular epithelial cells (HK-2) to determine the effect of CoCl2 on potential targets and the role of the key protein identified from the in vivo experiments. RESULTS: CoCl2 treatment decreased the levels of BUN and serum creatinine (sCr), while increasing the levels of urea and creatinine (Cr) in the urine of mice after CIN injury. Damage to the renal tubules in the CoCl2 treatment group was significantly less than in the CIN model group. We identified 79 DEPs after treating the in vivo model with CoCl2, and frequently observed ferroptosis-related GO and KEGG pathway terms. Of these, Hp (haptoglobin) was selected and found to have a strong renoprotective effect, even though its expression level in kidney tissue decreased after CoCl2 treatment. In HK-2 cells, overexpression of Hp reduced the ferroptosis caused by erastin, while knocking down Hp negated the attenuation effect of CoCl2 on HK-2 cell ferroptosis. CONCLUSION: CoCl2 attenuated kidney damage in the CIN model, and this effect was associated with the decrease in ferroptosis mediated by Hp.

Contrast-Enhanced Ultrasound as a Diagnostic Procedure in Renal Diseases: A Case Report.

Standard ultrasound (US) finds wide use in renal diseases as a screening procedure, but it is not always able to characterize lesions, especially in differential diagnosis between benign and malignant lesions. In contrast, contrast-enhanced ultrasonography (CEUS) is appropriate in differentiating between solid and cystic lesions as well as between tumors and pseudotumors. We show the case of a nephropathic patient who showed a complex, large, growing renal mass, characterized through a CEUS. This seventy-five-year-old diabetic heart patient showed a 6 cm-complex and plurisected cyst on ultrasound of left kidney. Laboratory data showed the presence of stage IIIb chronic renal failure with GFR 30 ml/min, creatinine 2.33 mg/dl, azotemia 88 mg/dl. The patient performed abdominal CT without contrast medium, showing at the level of the left upper pole, a roundish formation with the dimensions of approximately 70x53x50 mm. At the semiannual checkup, the nephrology examination showed a slight rise in creatinine and, therefore, after six months, it was decided to perform a CT scan without contrast medium again. CT showed a slight increase in the size of the mass located at the left kidney (74x56x57 mm). Given the increased size of the left mass, albeit modest, a CEUS was performed to reach a diriment diagnosis. CEUS concluded for complex cystic formation with presence of intraluminal solid-corpuscular material, with thrombotic-hemorrhagic etiology, in progressive phase of organization, classifiable as Bosniak type II cyst. CEUS in the kidneys is a cost-effective and valuable imaging technique; it is accurate in the characterization of indeterminate lesions and complex cysts.

MRI of Soft-Tissue Tumors: What to Include in the Report.

MRI serves as a critical step in the workup, local staging, and treatment planning of extremity soft-tissue masses. For the radiologist to meaningfully contribute to the management of soft-tissue masses, they need to provide a detailed list of descriptors of the lesion outlined in an organized report. While it is occasionally possible to use MRI to provide a diagnosis for patients with a mass, it is more often used to help with determining the differential diagnosis and planning of biopsies, surgery, radiation treatment, and chemotherapy (when provided). Each descriptor on the list outlined in this article is specifically aimed to assist in one or more facets of the overall approach to soft-tissue masses. This applies to all masses, but in particular sarcomas. Those descriptors are useful to help narrow the differential diagnosis and ensure concordance with a pathologic diagnosis and its accompanying grade assignment of soft-tissue sarcomas. These include a lesion's borders and shape, signal characteristics, and contrast enhancement pattern; the presence of peritumoral edema and peritumoral enhancement; and the presence of lymph nodes. The items most helpful in assisting surgical planning include a lesion's anatomic location, site of origin, size, location relative to a landmark, relationship to adjacent structures, and vascularity including feeding and draining vessels. The authors provide some background information on soft-tissue sarcomas, including their diagnosis and treatment, for the general radiologist and as a refresher for radiologists who are more experienced in tumor imaging. ©RSNA, 2024 See the invited commentary by Murphey in this issue.

Semiconducting Polymers Based on Asymmetric Thiadiazoloquinoxaline for Augmented In Vivo NIR-II Photoacoustic Imaging.

A photoacoustic (PA) imaging technique using the second near-infrared (NIR-II) window has attracted more and more attention because of its merits of deeper penetration depth and higher signal-to-noise (S/N) ratio than that using the first near-infrared (NIR-I) one. However, the design and development of high-performance PA imaging contrast agents in the NIR-II window is still a challenge. A semiconducting polymer, constructed by asymmetric units, exhibits regiorandom characteristics that effectively increase the distortion of the backbone. This increase in the degree of twist can regulate the twisted intramolecular charge transfer (TICT) effect, resulting in an enhancement of the PA signal. In this paper, an asymmetric structural acceptor strategy is developed to improve the PA signals of the resulting semiconducting polymer (PATQ-MP) in the NIR-II window with improved brightness, higher S/N ratio, and better photothermal conversion efficiency compared to polymers with the same main-chain structure containing a symmetric acceptor. DFT analysis showed that PATQ-MP containing an asymmetric acceptor monomer had a larger dihedral angle, which effectively improved the PA signal intensity by enhancing the TICT effect. The PEG-encapsulated PATQ-MP nanoparticles exhibit promising performance in the PA imaging of mouse tumors in vivo, demonstrating the clear identification of microvessels as small as 100 µm along with rapid metabolism within a span of 5 h. Therefore, this work provides a unique molecular design strategy for improving the signal intensity of PA imaging in the NIR-II window.

Contrast-enhanced Imaging in Peripheral Pulmonary Lesions: The Role in US-guided Biopsies.

Purpose To compare the tissue adequacy and diagnostic accuracy of US-guided biopsies of peripheral pulmonary lesions (PPLs) with and without contrast agents. Materials and Methods A retrospective study was conducted at four medical centers in patients with PPLs who underwent US-guided percutaneous transthoracic needle biopsy (PTNB) between January 2017 and October 2022. The patients were divided into contrast-enhanced US (CEUS) and US groups based on whether prebiopsy CEUS evaluation was performed. Tissue adequacy and the diagnostic accuracy of PTNB, stratified by lesion size, were analyzed and compared between groups. A propensity score matching (PSM) analysis was conducted using the nearest-neighbor matching method. Results A total of 1027 lesions were analyzed, with 634 patients (mean age, 59.4 years ± 13.0 [SD]; 413 male) in the US group and 393 patients (mean age, 61.2 years ± 12.5; 270 male) in the CEUS group. The CEUS group produced more acceptable samples than the US group (98.2% vs 95.7%; P = .03) and achieved higher diagnostic accuracy (96.9% vs 94.2%; P = .04), with no evidence of a difference in sensitivity (96.7% vs 94.0%; P = .06). PSM and stratified analyses (n = 358 per group) indicated higher tissue adequacy (99.0% vs 95.7%; P = .04) and diagnostic accuracy (98.5% vs 92.9%; P = .006) in the CEUS group compared with the US group for 2-7-cm PPLs but not for lesions larger than 7 cm. Conclusion PTNB with prebiopsy CEUS evaluation demonstrated significantly better tissue adequacy and diagnostic accuracy compared with US guidance alone for PPLs ranging from 2 to 7 cm, with similar biopsy performance achieved between groups for lesions larger than 7 cm. Keywords: Contrast Material, Thoracic Diseases, Ultrasonography, Image-Guided Biopsy © RSNA, 2024.

Contrast Agents Based on Human Serum Albumin and Nitroxides for 1H-MRI and Overhauser-Enhanced MRI.

In cancer diagnostics, magnetic resonance imaging (MRI) uses contrast agents to enhance the distinction between the target tissue and background. Several promising approaches have been developed to increase MRI sensitivity, one of which is Overhauser dynamic nuclear polarization (ODNP)-enhanced MRI (OMRI). In this study, a macromolecular construct based on human serum albumin and nitroxyl radicals (HSA-NIT) was developed using a new synthesis method that significantly increased the modification to 21 nitroxide residues per protein. This was confirmed by electron paramagnetic resonance (EPR) spectroscopy and matrix-assisted laser desorption/ionization time-of-flight (MALDI ToF) mass spectrometry. Gel electrophoresis and circular dichroism showed no significant changes in the structure of HSA-NITs, and no oligomers were formed during modification. The cytotoxicity of HSA-NITs was comparable to that of native albumin. HSA-NITs were evaluated as potential "metal-free" organic radical relaxation-based contrast agents for 1H-MRI and as hyperpolarizing contrast agents for OMRI. Relaxivities (longitudinal and transversal relaxation rates r1 and r2) for HSA-NITs were measured at different magnetic field strengths (1.88, 3, 7, and 14 T). Phantoms were used to demonstrate the potential use of HSA-NIT as a T1- and T2-weighted relaxation-based contrast agent at 3 T and 14 T. The efficacy of 1H Overhauser dynamic nuclear polarization (ODNP) in liquids at an ultralow magnetic field (ULF, B0 = 92 ± 0.8 µT) was investigated for HSA-NIT conjugates. The HSA-NITs themselves did not show ODNP enhancement; however, under the proteolysis conditions simulating cancer tissue, HSA-NIT conjugates were cleaved into lower-molecular-weight (MW) protein fragments that activate ODNP capabilities, resulting in a maximum achievable enhancement |Emax| of 40-50 and a radiofrequency power required to achieve half of Emax, P1/2, of 21-27 W. The HSA-NIT with a higher degree of modification released increased the number of spin probes upon biodegradation, which significantly enhanced the Overhauser effect. Thus, HSA-NITs may represent a new class of MRI relaxation-based contrast agents as well as novel cleavable conjugates for use as hyperpolarizing contrast agents (HCAs) in OMRI.

Inhibition of Drp1-mediated mitochondrial fission improves contrast-induced acute kidney injury by targeting the mROS-TXNIP-NLRP3 inflammasome axis.

Acute kidney injury (AKI) is a critical complication known for their extremely high mortality rate and lack of effective clinical therapy. Disorders in mitochondrial dynamics possess a pivotal role in the occurrence and progression of contrast-induced nephropathy (CIN) by activating NLRP3 inflammasome. The activation of dynamin-related protein-1 (Drp1) can trigger mitochondrial dynamic disorders by regulating excessive mitochondrial fission. However, the precise role of Drp1 during CIN has not been clarified. In vivo experiments revealed that inhibiting Drp1 through Mdivi-1 (one selective inhibitor of Drp1) can significantly decrease the expression of p-Drp1 (Ser616), mitochondrial p-Drp1 (Ser616), mitochondrial Bax, mitochondrial reactive oxygen species (mROS), NLRP3, caspase-1, ASC, TNF-α, IL-1ß, interleukin (IL)-18, IL-6, creatinine (Cr), malondialdehyde (MDA), blood urea nitrogen (BUN), and KIM-1. Moreover, Mdivi-1 reduced kidney pathological injury and downregulated the interaction between NLRP3 and thioredoxin-interacting protein (TXNIP), which was accompanied by decreased interactions between TRX and TXNIP. This resulted in increasing superoxide dismutase (SOD) and CAT activity, TRX expression, up-regulating mitochondrial membrane potential, and augmenting ATP contents and p-Drp1 (Ser616) levels in the cytoplasm. However, it did not bring impact on the expression of p-Drp1 (Ser637) and TXNIP. Activating Drp-1though Acetaldehyde abrogated the effects of Mdivi-1. In addition, the results of in vitro studies employing siRNA-Drp1 and plasmid-Drp1 intervention in HK-2 cells treated with iohexol were consistent with the in vivo experiments. Our findings revealed inhibiting Drp1 phosphorylation at Ser616 could ameliorate iohexol -induced acute kidney injury though alleviating the activation of the TXNIP-NLRP3 inflammasome pathway.

Technical note: Characterization, validation, and spectral optimization of a dedicated breast CT system for contrast-enhanced imaging.

BACKGROUND: The development of a new imaging modality, such as 4D dynamic contrast-enhanced dedicated breast CT (4D DCE-bCT), requires optimization of the acquisition technique, particularly within the 2D contrast-enhanced imaging modality. Given the extensive parameter space, cascade-systems analysis is commonly used for such optimization. PURPOSE: To implement and validate a parallel-cascaded model for bCT, focusing on optimizing and characterizing system performance in the projection domain to enhance the quality of input data for image reconstruction. METHODS: A parallel-cascaded system model of a state-of-the-art bCT system was developed and model predictions of the presampled modulation transfer function (MTF) and the normalized noise power spectrum (NNPS) were compared with empirical data collected in the projection domain. Validation was performed using the default settings of 49 kV with 1.5 mm aluminum filter and at 65 kV and 0.257 mm copper filter. A 10 mm aluminum plate was added to replicate the breast attenuation. Air kerma at the isocenter was measured at different tube current levels. Discrepancies between the measured projection domain metrics and model-predicted values were quantified using percentage error and coefficient of variation (CoV) for MTF and NNPS, respectively. The optimal filtration was for a 5 mm iodine disk detection task at 49, 55, 60, and 65 kV. The detectability index was calculated for the default aluminum filtration and for copper thicknesses ranging from 0.05 to 0.4 mm. RESULTS: At 49 kV, MTF errors were +5.1% and -5.1% at 1 and 2 cycles/mm, respectively; NNPS CoV was 5.3% (min = 3.7%; max = 8.5%). At 65 kV, MTF errors were -0.8% and -3.2%; NNPS CoV was 13.1% (min = 11.4%; max = 16.9%). Air kerma output was linear, with 11.67 µGy/mA (R2 = 0.993) and 19.14 µGy/mA (R2 = 0.996) at 49 and 65 kV, respectively. For iodine detection, a 0.25 mm-thick copper filter at 65 kV was found optimal, outperforming the default technique by 90%. CONCLUSION: The model accurately predicts bCT system performance, specifically in the projection domain, under varied imaging conditions, potentially contributing to the enhancement of 2D contrast-enhanced imaging in 4D DCE-bCT.

The feasibility of half-dose contrast-enhanced scanning of brain tumours at 5.0 T: a preliminary study.

PURPOSE: This study investigated and compared the effects of Gd enhancement on brain tumours with a half-dose of contrast medium at 5.0 T and with a full dose at 3.0 T. METHODS: Twelve subjects diagnosed with brain tumours were included in this study and underwent MRI after contrast agent injection at 3.0 T (full dose) or 5.0 T (half dose) with a 3D T1-weighted gradient echo sequence. The postcontrast images were compared by two independent neuroradiologists in terms of the signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR) and subjective image quality score on a ten-point Likert scale. Quantitative indices and subjective quality ratings were compared with paired Student's t tests, and interreader agreement was assessed with the intraclass correlation coefficient (ICC). RESULTS: A total of 16 enhanced tumour lesions were detected. The SNR was significantly greater at 5.0 T than at 3.0 T in grey matter, white matter and enhanced lesions (p < 0.001). The CNR was also significantly greater at 5.0 T than at 3.0 T for grey matter/tumour lesions, white matter/tumour lesions, and grey matter/white matter (p < 0.001). Subjective evaluation revealed that the internal structure and outline of the tumour lesions were more clearly displayed with a half-dose at 5.0 T (Likert scale 8.1 ± 0.3 at 3.0 T, 8.9 ± 0.3 at 5.0 T, p < 0.001), and the effects of enhancement in the lesions were comparable to those with a full dose at 3.0 T (7.8 ± 0.3 at 3.0 T, 8.7 ± 0.4 at 5.0 T, p < 0.001). All subjective scores were good to excellent at both 5.0 T and 3.0 T. CONCLUSION: Both quantitative and subjective evaluation parameters suggested that half-dose enhanced scanning via 5.0 T MRI might be feasible for meeting clinical diagnostic requirements, as the image quality remains optimal. Enhanced scanning at 5.0 T with a half-dose of contrast agents might benefit patients with conditions that require less intravenous contrast agent, such as renal dysfunction.