When will the immune-stimulating antibody conjugates (ISACs) be transferred from bench to bedside?

Immunostimulatory antibody conjugates (ISACs) as a promising new generation of targeted therapeutic antibody-drug conjugates (ADCs), that not only activate innate immunity but also stimulate adaptive immunity, providing a dual therapeutic effect to eliminate tumor cells. However, several ISACs are still in the early stages of clinical development or have already failed. Therefore, it is crucial to design ISACs more effectively to overcome their limitations, including high toxicity, strong immunogenicity, long development time, and poor pharmacokinetics. This review aims to summarize the composition and function of ISACs, incorporating current design considerations and ongoing clinical trials. Additionally, the review delves into the current issues with ISACs and potential solutions, such as adjusting the drug-antibody ratio (DAR) to improve the bioavailability of ISACs. By leveraging the affinity and bioavailability-enhancing properties of bispecific antibodies, the utility between antibodies and immunostimulatory agents can be balanced. Commonly used immunostimulatory agents may induce systemic immune reactions, and BTK (Bruton's tyrosine kinase) inhibitors can regulate immunogenicity. Finally, the concept of grafting ADC's therapeutic principles is simple, but the combination of payload, linker, and targeted functional molecules is not a simple permutation and combination problem. The development of conjugate drugs faces more complex pharmacological and toxicological issues. Standing on the shoulders of ADC, the development and application scenarios of ISAC are endowed with broader space.

LL-37 improves sepsis-induced acute lung injury by suppressing pyroptosis in alveolar epithelial cells.

BACKGROUND: LL-37 (also known as murine CRAMP) is a human antimicrobial peptide that plays a crucial role in innate immune defence against sepsis through various mechanisms. However, its involvement in sepsis-induced lung injury remains unclear. OBJECTIVES: This work investigates the impact of LL-37 on pyroptosis generated by LPS in alveolar epithelial cells. The research utilizes both in vivo and in vitro sepsis-associated acute lung injury (ALI) models to understand the underlying molecular pathways. METHODS: In vivo, an acute lung injury model induced by sepsis was established by intratracheal administration of LPS in C57BL/6J mice, which were subsequently treated with low-dose CRAMP (recombinant murine cathelicidin, 2.5 mg.kg-1) and high-dose CRAMP (5.0 mg.kg-1). In vitro, pyroptosis was induced in a human alveolar epithelial cell line (A549) by stimulation with LPS and ATP. Treatment was carried out with recombinant human LL-37, or LL-37 was knocked out in A549 cells using small interfering RNA (siRNA). Subsequently, haematoxylin and eosin staining was performed to observe the histopathological changes in lung tissues in the control group and sepsis-induced lung injury group. TUNEL and PI staining were used to observe DNA fragmentation and pyroptosis in mouse lung tissues and cells in the different groups. An lactate dehydrogenase (LDH) assay was performed to measure the cell death rate. The expression levels of NLRP3, caspase1, caspase 1 p20, GSDMD, NT-GSDMD, and CRAMP were detected in mice and cells using Western blotting, qPCR, and immunohistochemistry. ELISA was used to assess the levels of interleukin (IL)-1ß and IL-18 in mouse serum, bronchoalveolar lavage fluid (BALF) and lung tissue and cell culture supernatants. RESULTS: The expression of NLRP3, caspase1 p20, NT-GSDMD, IL 18 and IL1ß in the lung tissue of mice with septic lung injury was increased, which indicated activation of the canonical pyroptosis pathway and coincided with an increase in CRAMP expression. Treatment with recombinant CRAMP improved pyroptosis in mice with lung injury. In vitro, treatment with LPS and ATP upregulated these classic pyroptosis molecules, LL-37 knockdown exacerbated pyroptosis, and recombinant human LL-37 treatment alleviated pyroptosis in alveolar epithelial cells. CONCLUSION: These findings indicate that LL-37 protects against septic lung injury by modulating the expression of classic pyroptotic pathway components, including NLRP3, caspase1, and GSDMD and downstream inflammatory factors in alveolar epithelial cells.

Back to the Future: Dynamic Contrast-Enhanced Photon-Counting Detector CT for the Detection of Pituitary Adenoma in Cushing Disease.

Historically, MR imaging has been unable to detect a pituitary adenoma in up to one-half of patients with Cushing disease. This issue is problematic because the standard-of-care treatment is surgical resection, and its success is correlated with finding the tumor on imaging. Photon-counting detector CT is a recent advancement that has multiple benefits over conventional energy-integrating detector CT. We present the use of dynamic contrast-enhanced imaging using photon-counting detector CT for the detection of pituitary adenomas in patients with Cushing disease.

Targeted Training Reduces Search Errors but Not Classification Errors for Hepatic Metastasis Detection at Contrast-Enhanced CT.

RATIONALE AND OBJECTIVES: Methods are needed to improve the detection of hepatic metastases. Errors occur in both lesion detection (search) and decisions of benign versus malignant (classification). Our purpose was to evaluate a training program to reduce search errors and classification errors in the detection of hepatic metastases in contrast-enhanced abdominal computed tomography (CT). MATERIALS AND METHODS: After Institutional Review Board approval, we conducted a single-group prospective pretest-posttest study. Pretest and posttest were identical and consisted of interpreting 40 contrast-enhanced abdominal CT exams containing 91 liver metastases under eye tracking. Between pretest and posttest, readers completed search training with eye-tracker feedback and coaching to increase interpretation time, use liver windows, and use coronal reformations. They also completed classification training with part-task practice, rating lesions as benign or malignant. The primary outcome was metastases missed due to search errors (<2 seconds gaze under eye tracker) and classification errors (>2 seconds). Jackknife free-response receiver operator characteristic (JAFROC) analysis was also conducted. RESULTS: A total of 31 radiologist readers (8 abdominal subspecialists, 8 nonabdominal subspecialists, 15 senior residents/fellows) participated. Search errors were reduced (pretest 11%, posttest 8%, difference 3% [95% confidence interval, 0.3%-5.1%], P = .01), but there was no difference in classification errors (difference 0%, P = .97) or in JAFROC figure of merit (difference -0.01, P = .36). In subgroup analysis, abdominal subspecialists demonstrated no evidence of change. CONCLUSION: Targeted training reduced search errors but not classification errors for the detection of hepatic metastases at contrast-enhanced abdominal CT. Improvements were not seen in all subgroups.

Radiation exposure in navigated techniques for AIS: is there a difference between pre-operative CT and intraoperative CT?

PURPOSE: Utilization of navigation improves pedicle screw accuracy in adolescent idiopathic scoliosis (AIS). Our center switched from intraoperative CT (ICT) to an optical navigation system that utilizes pre-operative CT (PCT). We aim to evaluate the radiation dose and operative time for low-dose ICT compared to standard and low-dose PCT used for optical navigation in AIS patients undergoing posterior spinal fusion. METHODS: A single-center matched-control cohort study of 38 patients was conducted. Nineteen patients underwent ICT navigation (O-arm) and were matched by sex, age, and weight to 19 patients who underwent PCT for use with an optical-guided navigation (7D, Seaspine). A total of 418 levels were instrumented and reviewed. PCT was either a standard dose (N = 7) or a low dose (N = 12). The mean volume CT dose index, dose-length product, overall effective dose (ED), ED per level instrumented, and operative time per level were compared. RESULTS: ED per level instrumented was 0.061 ± 0.029 mSv in low-dose PCT and 0.14 ± 0.05 mSv in low-dose ICT (p < 0.0001). ED per level instrumented was significantly higher in standard PCT (1.46 ± 0.39 vs. 0.14 ± 0.03 mSv; p < 0.0001). Mean operative time per level was 31 ± 7 min for ICT and 33 ± 3 min for PCT (p = 0.628). CONCLUSION: Low-dose PCT resulted in 0.70 mSv exposure per case and 31 min per level, standard-dose was 16.95 mSv, while ICT resulted in 1.34-1.62 mSv and a similar operative time. Use of a standard-dose PCT involves radiation exposure about 9 times higher than ICT and 23 times higher than low-dose PCT per level instrumented. LEVEL OF EVIDENCE: Level III.

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.

Peptide-drug conjugates (PDCs): a novel trend of research and development on targeted therapy, hype or hope?

Peptide-drug conjugates (PDCs) are the next generation of targeted therapeutics drug after antibody-drug conjugates (ADCs), with the core benefits of enhanced cellular permeability and improved drug selectivity. Two drugs are now approved for market by US Food and Drug Administration (FDA), and in the last two years, the pharmaceutical companies have been developing PDCs as targeted therapeutic candidates for cancer, coronavirus disease 2019 (COVID-19), metabolic diseases, and so on. The therapeutic benefits of PDCs are significant, but poor stability, low bioactivity, long research and development time, and slow clinical development process as therapeutic agents of PDC, how can we design PDCs more effectively and what is the future direction of PDCs? This review summarises the components and functions of PDCs for therapeutic, from drug target screening and PDC design improvement strategies to clinical applications to improve the permeability, targeting, and stability of the various components of PDCs. This holds great promise for the future of PDCs, such as bicyclic peptide‒toxin coupling or supramolecular nanostructures for peptide-conjugated drugs. The mode of drug delivery is determined according to the PDC design and current clinical trials are summarised. The way is shown for future PDC development.

Safety Considerations in MRI and CT.

OBJECTIVE: MRI and CT are indispensable imaging modalities for the evaluation of patients with neurologic disease, and each is particularly well suited to address specific clinical questions. Although both of these imaging modalities have excellent safety profiles in clinical use as a result of concerted and dedicated efforts, each has potential physical and procedural risks that the practitioner should be aware of, which are described in this article. LATEST DEVELOPMENTS: Recent advancements have been made in understanding and reducing safety risks with MR and CT. The magnetic fields in MRI create risks for dangerous projectile accidents, radiofrequency burns, and deleterious interactions with implanted devices, and serious patient injuries and deaths have occurred. Ionizing radiation in CT may be associated with shorter-term deterministic effects on biological tissues at extremely high doses and longer-term stochastic effects related to mutagenesis and carcinogenesis at low doses. The cancer risk of radiation exposure in diagnostic CT is considered extremely low, and the benefit of an appropriately indicated CT examination far outweighs the potential risk. Continuing major efforts are centered on improving image quality and the diagnostic power of CT while concurrently keeping radiation doses as low as reasonably achievable. ESSENTIAL POINTS: An understanding of these MRI and CT safety issues that are central to contemporary radiology practice is essential for the safe and effective treatment of patients with neurologic disease.

Pilot study to determine whether reduced-dose photon-counting detector chest computed tomography can reliably display Brody II score imaging findings for children with cystic fibrosis at radiation doses that approximate radiographs.

BACKGROUND: The Brody II score uses chest CT to guide therapeutic changes in children with cystic fibrosis; however, patients and providers are often reticent to undergo chest CT given concerns about radiation. OBJECTIVE: We sought to determine the ability of a reduced-dose photon-counting detector (PCD) chest CT protocol to reproducibly display pulmonary disease severity using the Brody II score for children with cystic fibrosis (CF) scanned at radiation doses similar to those of a chest radiograph. MATERIALS AND METHODS: Pediatric patients with CF underwent non-contrast reduced-dose chest PCD-CT. Volumetric inspiratory and expiratory scans were obtained without sedation or anesthesia. Three pediatric radiologists with Certificates of Added Qualification scored each scan on an ordinal scale and assigned a Brody II score to grade bronchiectasis, peribronchial thickening, parenchymal opacity, air trapping and mucus plugging. We report image-quality metrics using descriptive statistics. To calculate inter-rater agreement for Brody II scoring, we used the Krippendorff alpha and intraclass correlation coefficient (ICC). RESULTS: Fifteen children with CF underwent reduced-dose PCD chest CT in both inspiration and expiration (mean age 8.9 years, range, 2.5-17.5 years; 4 girls). Mean volumetric CT dose index (CTDIvol) was 0.07 ± 0.03 mGy per scan. Mean effective dose was 0.12 ± 0.04 mSv for the total examination. All three readers graded spatial resolution and noise as interpretable on lung windows. The average Brody II score was 12.5 (range 4-19), with moderate inter-reader reliability (ICC of 0.61 [95% CI=0.27, 0.84]). Inter-rater reliability was moderate to substantial for bronchiectasis (0.52), peribronchial thickening (0.55), presence of opacity (0.62) and air trapping (0.70) and poor for mucus plugging (0.09). CONCLUSION: Reduced-dose PCD-CT permits diagnostic image quality and reproducible identification of Brody II scoring imaging findings at radiation doses similar to those for chest radiography.

Lung Cancer Screening Using Clinical Photon-Counting Detector Computed Tomography and Energy-Integrating-Detector Computed Tomography: A Prospective Patient Study.

OBJECTIVE: To evaluate the diagnostic quality of photon-counting detector (PCD) computed tomography (CT) in patients undergoing lung cancer screening compared with conventional energy-integrating detector (EID) CT in a prospective multireader study. MATERIALS: Patients undergoing lung cancer screening with conventional EID-CT were prospectively enrolled and scanned on a PCD-CT system using similar automatic exposure control settings and reconstruction kernels. Three thoracic radiologists blinded to CT system compared PCD-CT and EID-CT images and scored examinations using a 5-point Likert comparison score (-2 [left image is worse] to +2 [left image is better]) for artifacts, sharpness, image noise, diagnostic image quality, emphysema visualization, and lung nodule evaluation focusing on the border. Post hoc correction of Likert scores was performed such that they reflected PCD-CT performance in comparison to EID-CT. A nonreader radiologist measured objective image noise. RESULTS: Thirty-three patients (mean, 66.9 ± 5.6 years; 11 female; body mass index; 30.1 ± 5.1 kg/m 2 ) were enrolled. Mean volume CT dose index for PCD-CT was lower (0.61 ± 0.21 vs 0.73 ± 0.22; P < 0.001). Pooled reader results showed significant differences between imaging modalities for all comparative rankings ( P < 0.001), with PCD-CT favored for sharpness, image noise, image quality, and emphysema visualization and lung nodule border, but not artifacts. Photon-counting detector CT had significantly lower image noise (74.4 ± 10.5 HU vs 80.1 ± 8.6 HU; P = 0.048). CONCLUSIONS: Photon-counting detector CT with similar acquisition and reconstruction settings demonstrated improved image quality and less noise despite lower radiation dose, with improved ability to depict pulmonary emphysema and lung nodule borders compared with EID-CT at low-dose lung cancer CT screening.

Understanding Reader Variability: A 25-Radiologist Study on Liver Metastasis Detection at CT.

Background Substantial interreader variability exists for common tasks in CT imaging, such as detection of hepatic metastases. This variability can undermine patient care by leading to misdiagnosis. Purpose To determine the impact of interreader variability associated with (a) reader experience, (b) image navigation patterns (eg, eye movements, workstation interactions), and (c) eye gaze time at missed liver metastases on contrast-enhanced abdominal CT images. Materials and Methods In a single-center prospective observational trial at an academic institution between December 2020 and February 2021, readers were recruited to examine 40 contrast-enhanced abdominal CT studies (eight normal, 32 containing 91 liver metastases). Readers circumscribed hepatic metastases and reported confidence. The workstation tracked image navigation and eye movements. Performance was quantified by using the area under the jackknife alternative free-response receiver operator characteristic (JAFROC-1) curve and per-metastasis sensitivity and was associated with reader experience and image navigation variables. Differences in area under JAFROC curve were assessed with the Kruskal-Wallis test followed by the Dunn test, and effects of image navigation were assessed by using the Wilcoxon signed-rank test. Results Twenty-five readers (median age, 38 years; IQR, 31-45 years; 19 men) were recruited and included nine subspecialized abdominal radiologists, five nonabdominal staff radiologists, and 11 senior residents or fellows. Reader experience explained differences in area under the JAFROC curve, with abdominal radiologists demonstrating greater area under the JAFROC curve (mean, 0.77; 95% CI: 0.75, 0.79) than trainees (mean, 0.71; 95% CI: 0.69, 0.73) (P = .02) or nonabdominal subspecialists (mean, 0.69; 95% CI: 0.60, 0.78) (P = .03). Sensitivity was similar within the reader experience groups (P = .96). Image navigation variables that were associated with higher sensitivity included longer interpretation time (P = .003) and greater use of coronal images (P < .001). The eye gaze time was at least 0.5 and 2.0 seconds for 71% (266 of 377) and 40% (149 of 377) of missed metastases, respectively. Conclusion Abdominal radiologists demonstrated better discrimination for the detection of liver metastases on abdominal contrast-enhanced CT images. Missed metastases frequently received at least a brief eye gaze. Higher sensitivity was associated with longer interpretation time and greater use of liver display windows and coronal images. © RSNA, 2022 Online supplemental material is available for this article.

Individualized and generalized models for predicting observer performance on liver metastasis detection using CT.

Purpose: Radiologists exhibit wide inter-reader variability in diagnostic performance. This work aimed to compare different feature sets to predict if a radiologist could detect a specific liver metastasis in contrast-enhanced computed tomography (CT) images and to evaluate possible improvements in individualizing models to specific radiologists. Approach: Abdominal CT images from 102 patients, including 124 liver metastases in 51 patients were reconstructed at five different kernels/doses using projection domain noise insertion to yield 510 image sets. Ten abdominal radiologists marked suspected metastases in all image sets. Potentially salient features predicting metastasis detection were identified in three ways: (i) logistic regression based on human annotations (semantic), (ii) random forests based on radiologic features (radiomic), and (iii) inductive derivation using convolutional neural networks (CNN). For all three approaches, generalized models were trained using metastases that were detected by at least two radiologists. Conversely, individualized models were trained using each radiologist's markings to predict reader-specific metastases detection. Results: In fivefold cross-validation, both individualized and generalized CNN models achieved higher area under the receiver operating characteristic curves (AUCs) than semantic and radiomic models in predicting reader-specific metastases detection ability ( p < 0.001 ). The individualized CNN with an AUC of mean (SD) 0.85(0.04) outperformed the generalized one [ AUC = 0.78 ( 0.06 ) , p = 0.004 ]. The individualized semantic [ AUC = 0.70 ( 0.05 ) ] and radiomic models [ AUC = 0.68 ( 0.06 ) ] outperformed the respective generalized versions [semantic AUC = 0.66 ( 0.03 ) , p = 0.009 ; radiomic AUC = 0.64 ( 0.06 ) , p = 0.03 ]. Conclusions: Individualized models slightly outperformed generalized models for all three feature sets. Inductive CNNs were better at predicting metastases detection than semantic or radiomic features. Generalized models have implementation advantages when individualized data are unavailable.

Computational Recognition of a Regulatory T-cell-specific Signature With Potential Implications in Prognosis, Immunotherapy, and Therapeutic Resistance of Prostate Cancer.

Prostate cancer, recognized as a "cold" tumor, has an immunosuppressive microenvironment in which regulatory T cells (Tregs) usually play a major role. Therefore, identifying a prognostic signature of Tregs has promising benefits of improving survival of prostate cancer patients. However, the traditional methods of Treg quantification usually suffer from bias and variability. Transcriptional characteristics have recently been found to have a predictive power for the infiltration of Tregs. Thus, a novel machine learning-based computational framework has been presented using Tregs and 19 other immune cell types using 42 purified immune cell datasets from GEO to identify Treg-specific mRNAs, and a prognostic signature of Tregs (named "TILTregSig") consisting of five mRNAs (SOCS2, EGR1, RRM2, TPP1, and C11orf54) was developed and validated to monitor the prognosis of prostate cancer using the TCGA and ICGC datasets. The TILTregSig showed a stronger predictive power for tumor immunity compared with tumor mutation burden and glycolytic activity, which have been reported as immune predictors. Further analyses indicate that the TILTregSig might influence tumor immunity mainly by mediating tumor-infiltrating Tregs and could be a powerful predictor for Tregs in prostate cancer. Moreover, the TILTregSig showed a promising potential for predicting cancer immunotherapy (CIT) response in five CIT response datasets and therapeutic resistance in the GSCALite dataset in multiple cancers. Our TILTregSig derived from PBMCs makes it possible to achieve a straightforward, noninvasive, and inexpensive detection assay for prostate cancer compared with the current histopathological examination that requires invasive tissue puncture, which lays the foundation for the future development of a panel of different molecules in peripheral blood comprising a biomarker of prostate cancer.

A 25-reader performance study for hepatic metastasis detection: lessons from unsupervised learning.

There is substantial variability in the performance of radiologist readers. We hypothesized that certain readers may have idiosyncratic weaknesses towards certain types of lesions, and unsupervised learning techniques might identify these patterns. After IRB approval, 25 radiologist readers (9 abdominal subspecialists and 16 non-specialists or trainees) read 40 portal phase liver CT exams, marking all metastases and providing a confidence rating on a scale of 1 to 100. We formed a matrix of reader confidence ratings, with rows corresponding to readers, and columns corresponding to metastases, and each matrix entry providing the confidence rating that a reader gave to the metastasis, with zero confidence used for lesions that were not marked. A clustergram was used to permute the rows and columns of this matrix to group similar readers and metastases together. This clustergram was manually interpreted. We found a cluster of lesions with atypical presentation that were missed by several readers, including subspecialists, and a separate cluster of small, subtle lesions where subspecialists were more confident of their diagnosis than trainees. These and other observations from unsupervised learning could inform targeted training and education of future radiologists.

A minimum SNR criterion for computed tomography object detection in the projection domain.

BACKGROUND: A common rule of thumb for object detection is the Rose criterion, which states that a signal must be five standard deviations above background to be detectable to a human observer. The validity of the Rose criterion in CT imaging is limited due to the presence of correlated noise. Recent reconstruction and denoising methodologies are also able to restore apparent image quality in very noisy conditions, and the ultimate limits of these methodologies are not yet known. PURPOSE: To establish a lower bound on the minimum achievable signal-to-noise ratio (SNR) for object detection, below which detection performance is poor regardless of reconstruction or denoising methodology. METHODS: We consider a numerical observer that operates on projection data and has perfect knowledge of the background and the objects to be detected, and determine the minimum projection SNR that is necessary to achieve predetermined lesion-level sensitivity and case-level specificity targets. We define a set of discrete signal objects O $\mathcal{O}$ that encompasses any lesion of interest and could include lesions of different sizes, shapes, and locations. The task is to determine which object of O $\mathcal{O}$ is present, or to state the null hypothesis that no object is present. We constrain each object in O $\mathcal{O}$ to have equivalent projection SNR and use Monte Carlo methods to calculate the required projection SNR necessary. Because our calculations are performed in projection space, they impose an upper limit on the performance possible from reconstructed images. We chose O $\mathcal{O}$ to be a collection of elliptical or circular low contrast metastases and simulated detection of these objects in a parallel beam system with Gaussian statistics. Unless otherwise stated, we assume a target of 80% lesion-level sensitivity and 80% case-level specificity and a search field of view that is 6 cm by 6 cm by 10 slices. RESULTS: When O $\mathcal{O}$ contains only a single object, our problem is equivalent to two-alternative forced choice (2AFC) and the required projection SNR is 1.7. When O $\mathcal{O}$ consists of circular 6-mm lesions at different locations in space, the required projection SNR is 5.1. When O $\mathcal{O}$ is extended to include ellipses and circles of different sizes, the required projection SNR increases to 5.3. The required SNR increases if the sensitivity target, specificity target, or search field of view increases. CONCLUSIONS: Even with perfect knowledge of the background and target objects, the ideal observer still requires an SNR of approximately 5. This is a lower bound on the SNR that would be required in real conditions, where the background and target objects are not known perfectly. Algorithms that denoise lesions with less than 5 projection SNR, regardless of the denoising methodology, are expected to show vanishing effects or false positive lesions.

Retraction Notice to: miR-181a Induces Macrophage Polarized to M2 Phenotype and Promotes M2 Macrophage-mediated Tumor Cell Metastasis by Targeting KLF6 and C/EBPα.

[This retracts the article DOI: 10.1038/mtna.2016.71.].

Advances of research of Fc-fusion protein that activate NK cells for tumor immunotherapy.

The rapid development of bioengineering technology has introduced Fc-fusion proteins, representing a novel kind of recombinant protein, as promising biopharmaceutical products in tumor therapy. Numerous related anti-tumor Fc-fusion proteins have been investigated and are in different stages of development. Fc-fusion proteins are constructed by fusing the Fc-region of the antibody with functional proteins or peptides. They retain the bioactivity of the latter and partial properties of the former. This structural and functional advantage makes Fc-fusion proteins an effective tool in tumor immunotherapy, especially for the recruitment and activation of natural killer (NK) cells, which play a critical role in tumor immunotherapy. Even though tumor cells have developed mechanisms to circumvent the cytotoxic effect of NK cells or induce defective NK cells, Fc-fusion proteins have been proven to effectively activate NK cells to kill tumor cells in different ways, such as antibody-dependent cell-mediated cytotoxicity (ADCC), activate NK cells in different ways in order to promote killing of tumor cells. In this review, we focus on NK cell-based immunity for cancers and current research progress of the Fc-fusion proteins for anti-tumor therapy by activating NK cells.

Utility of an automatic adaptive iterative metal artifact reduction AiMAR algorithm in improving CT imaging of patients with hip prostheses evaluated for suspected bladder malignancy.

PURPOSE: To compare the utility of a novel metal artifact reduction algorithm to standard imaging in improving visualization of key structures, diagnostic confidence, and patient-level confidence in malignancy in patients with suspected bladder cancer. METHODS: Patients with hip implants undergoing CT urography for suspected bladder malignancy were enrolled. Images were reconstructed using 3 methods: (1) Filtered Back Projection (FBP), (2) Iterative Metal Artifact Reduction (iMAR), and (3) Adaptive Iterative Metal Artifact Reduction (AiMAR) strength 4. In multiple reading sessions, three radiologists graded visualization of critical anatomic structures and artifact severity (6-point scales, lower scores desirable), and diagnostic confidence in blinded fashion. They also graded patient-level confidence in malignancy based on imaging findings in each patient. RESULTS: Thirty-two patients (8 females) with a mean age of 74.5 ± 8.5 years were included. The median (range) visualization scores for FBP, iMAR, and AiMAR were 3.6 (1.1-4.9), 1.6 (0.3-2.8), and 1.6 (0.3-2.6), respectively. Both iMAR and AiMAR had anatomic visualization and artifact scores better than FBP (P < 0.001 for both) and similar to each other (P > 0.05). Structures with the most improvement in visualization score with the use of metal artifact reduction algorithms included the obturator internus muscle, internal and external iliac nodal chains, and vagina. iMAR and AiMAR improved diagnostic confidence (P < 0.001) and patient-level confidence in malignancy (P ≤ 0.24). CONCLUSION: For patients with hip prostheses and suspected bladder malignancy, the use of iMAR or AiMAR was shown to significantly reduce metal artifacts, thus improving diagnostic confidence and patient-level confidence in malignancy.