[Guidelines for Evaluating Treatment Response Based on Bone Scan for Metastatic Castration-Resistant Prostate Cancer: Prostate Cancer Clinical Trial Working Group 3 Recommendations]. / ì „ì´ì„± 거세 ì €í•­ì„± ì „ë¦½ì„ ì•”ì˜ 치료 반응 평가를 위한 뼈스캔 기반의 ì „ì´ì„± 골병변 반응 평가 지침: Prostate Cancer Clinical Trial Working Group 3 권장사항.

In prostate cancer, the bone is the most common site of metastasis, and it is essential to evaluate metastatic bone lesions to assess the tumor burden and treatment response. Castration-resistant prostate cancer refers to the state wherein the cancer continues to progress despite a significant reduction of the sex hormone level and is associated with frequent distant metastasis. The Prostate Cancer Working Group 3 (PCWG3) released guidelines that aimed to standardize the assessment of treatment effects in castration-resistant prostate cancer using bone scintigraphy. However, these guidelines can be challenging to comprehend and implement in practical settings. The purpose of this review was to provide an overview of a specific image acquisition method and treatment response assessment for bone scintigraphy-based evaluation of bone lesions in metastatic castration-resistant prostate cancer, in accordance with the PCWG3 guidelines.

Comprehensive Analysis for Anti-Cancer Target-Indication Prioritization of Placental Growth Factor Inhibitor (PGF) by Use of Omics and Patient Survival Data.

The expression of the placental growth factor (PGF) in cancer cells and the tumor microenvironment can contribute to the induction of angiogenesis, supporting cancer cell metabolism by ensuring an adequate blood supply. Angiogenesis is a key component of cancer metabolism as it facilitates the delivery of nutrients and oxygen to rapidly growing tumor cells. PGF is recognized as a novel target for anti-cancer treatment due to its ability to overcome resistance to existing angiogenesis inhibitors and its impact on the tumor microenvironment. We aimed to integrate bioinformatics evidence using various data sources and analytic tools for target-indication identification of the PGF target and prioritize the indication across various cancer types as an initial step of drug development. The data analysis included PGF gene function, molecular pathway, protein interaction, gene expression and mutation across cancer type, survival prognosis and tumor immune infiltration association with PGF. The overall evaluation was conducted given the totality of evidence, to target the PGF gene to treat the cancer where the PGF level was highly expressed in a certain tumor type with poor survival prognosis as well as possibly associated with poor tumor infiltration level. PGF showed a significant impact on overall survival in several cancers through univariate or multivariate survival analysis. The cancers considered as target diseases for PGF inhibitors, due to their potential effects on PGF, are adrenocortical carcinoma, kidney cancers, liver hepatocellular carcinoma, stomach adenocarcinoma, and uveal melanoma.

Evolution of Radiological Treatment Response Assessments for Cancer Immunotherapy: From iRECIST to Radiomics and Artificial Intelligence.

Immunotherapy has revolutionized and opened a new paradigm for cancer treatment. In the era of immunotherapy and molecular targeted therapy, precision medicine has gained emphasis, and an early response assessment is a key element of this approach. Treatment response assessment for immunotherapy is challenging for radiologists because of the rapid development of immunotherapeutic agents, from immune checkpoint inhibitors to chimeric antigen receptor-T cells, with which many radiologists may not be familiar, and the atypical responses to therapy, such as pseudoprogression and hyperprogression. Therefore, new response assessment methods such as immune response assessment, functional/molecular imaging biomarkers, and artificial intelligence (including radiomics and machine learning approaches) have been developed and investigated. Radiologists should be aware of recent trends in immunotherapy development and new response assessment methods.

Incidence of Immune-Mediated Pseudoprogression of Lymphoma Treated with Immune Checkpoint Inhibitors: Systematic Review and Meta-Analysis.

We evaluated the incidence of pseudoprogression and indeterminate response (IR) in patients with lymphoma treated with immune checkpoint inhibitors (ICIs). A systematic search of PubMed and EMBASE was performed up to 6 February 2021, using the keywords "lymphoma," "immunotherapy," and "pseudoprogression." Random-effects models were used to calculate both pooled incidence of pseudoprogression patients with lymphoma and an IR according to LYRIC criteria, while the Higgins inconsistency index (I2) test and Cochran's Q test were used for heterogeneity. Eight original articles were included, in which the number of patients ranged from 7 to 243. Among the lymphoma patients with ICIs, the pooled incidence of pseudoprogression was 10% (95% confidence interval [CI]: 0.06-0.17). There was no publication bias in Begg's test (p = 0.14). Three articles were analyzed to determine the pooled incidence of pseudoprogression in patients with IR according to LYRIC criteria in a subgroup analysis, which was shown to be 19% (95% CI: 0.08-0.40). A significant proportion (10%) of patients with lymphoma treated with ICIs showed pseudoprogression, and 19% of patients with an IR response showed pseudoprogression and a delayed response. Immune-related response criteria such as LYRIC may be used for patients with lymphoma treated with ICIs.

CDISC-compliant clinical trial imaging management system with automatic verification and data Transformation: Focusing on tumor response assessment data in clinical trials.

OBJECTIVE: Major issues in imaging data management of tumor response assessment in clinical trials include high human errors in data input and unstandardized data structures, warranting a new breakthrough IT solution. Thus, we aim to develop a Clinical Data Interchange Standards Consortium (CDISC)-compliant clinical trial imaging management system (CTIMS) with automatic verification and transformation modules for implementing the CDISC Study Data Tabulation Model (SDTM) in the tumor response assessment dataset of clinical trials. MATERIALS AND METHODS: In accordance with various CDISC standards guides and Response Evaluation Criteria in Solid Tumors (RECIST) guidelines, the overall system architecture of CDISC-compliant CTIMS was designed. Modules for standard-compliant electronic case report form (eCRF) to verify data conformance and transform into SDTM data format were developed by experts in diverse fields such as medical informatics, medical, and clinical trial. External validation of the CDISC-compliant CTIMS was performed by comparing it with our previous CTIMS based on real-world data and CDISC validation rules by Pinnacle 21 Community Software. RESULTS: The architecture of CDISC-compliant CTIMS included the standard-compliant eCRF module of RECIST, the automatic verification module of the input data, and the SDTM transformation module from the eCRF input data to the SDTM datasets based on CDISC Define-XML. This new system was incorporated into our previous CTIMS. External validation demonstrated that all 176 human input errors occurred in the previous CTIMS filtered by a new system yielding zero error and CDISC-compliant dataset. The verified eCRF input data were automatically transformed into the SDTM dataset, which satisfied the CDISC validation rules by Pinnacle 21 Community Software. CONCLUSIONS: To assure data consistency and high quality of the tumor response assessment data, our new CTIMS can minimize human input error by using standard-compliant eCRF with an automatic verification module and automatically transform the datasets into CDISC SDTM format.

A Good Practice-Compliant Clinical Trial Imaging Management System for Multicenter Clinical Trials: Development and Validation Study.

BACKGROUND: With the rapid increase in utilization of imaging endpoints in multicenter clinical trials, the amount of data and workflow complexity have also increased. A Clinical Trial Imaging Management System (CTIMS) is required to comprehensively support imaging processes in clinical trials. The US Food and Drug Administration (FDA) issued a guidance protocol in 2018 for appropriate use of medical imaging in accordance with many regulations including the Good Clinical Practice (GCP) guidelines. Existing research on CTIMS, however, has mainly focused on functions and structures of systems rather than regulation and compliance. OBJECTIVE: We aimed to develop a comprehensive CTIMS to meet the current regulatory guidelines and various required functions. We also aimed to perform computerized system validation focusing on the regulatory compliance of our CTIMS. METHODS: Key regulatory requirements of CTIMS were extracted thorough review of many related regulations and guidelines including International Conference on Harmonization-GCP E6, FDA 21 Code of Federal Regulations parts 11 and 820, Good Automated Manufacturing Practice, and Clinical Data Interchange Standards Consortium. The system architecture was designed in accordance with these regulations by a multidisciplinary team including radiologists, engineers, clinical trial specialists, and regulatory medicine professionals. Computerized system validation of the developed CTIMS was performed internally and externally. RESULTS: Our CTIMS (AiCRO) was developed based on a two-layer design composed of the server system and the client system, which is efficient at meeting the regulatory and functional requirements. The server system manages system security, data archive, backup, and audit trail. The client system provides various functions including deidentification, image transfer, image viewer, image quality control, and electronic record. Computerized system validation was performed internally using a V-model and externally by a global quality assurance company to demonstrate that AiCRO meets all regulatory and functional requirements. CONCLUSIONS: We developed a Good Practice-compliant CTIMS-AiCRO system-to manage large amounts of image data and complexity of imaging management processes in clinical trials. Our CTIMS adopts and adheres to all regulatory and functional requirements and has been thoroughly validated.

Advances in whole body MRI for musculoskeletal imaging: Diffusion-weighted imaging.

Recent advances in imaging technology have enabled the acquisition of anatomical and functional imaging from head to toe in a reasonably short scan time. Accordingly, whole body magnetic resonance imaging (WB-MRI) and diffusion-weighted imaging (WB-DWI) have gained recent attention for the management of musculoskeletal problems such as bone tumors and rheumatologic diseases. WB-MRI is especially useful in diagnosing systemic or widespread disease requiring whole body evaluation, such as bone metastases, multiple myeloma, lymphoma, neurofibromatosis, and spondyloarthropathies. Among WB-MRI sequences, the WB-DWI technique greatly increases the value of WB-MRI in the evaluation of disease extent and characterization as well as treatment monitoring. In support of the utilization of WB-MRI and WB-DWI in orthopedic clinics for various musculoskeletal diseases, we provide an overview of the technical aspects of WB-MRI and WB-DWI and their clinical applications in musculoskeletal tumors and rheumatic diseases.

Normative Data for the Neurobehavioral Symptom Inventory.

The demographically diverse populations served by large health care systems (Veterans Affairs, Department of Defense, Medicare, Medicaid) are routinely screened with the Neurobehavioral Symptom Inventory (NSI). The extent to which a patient's report of symptoms either initially and/or across time is affected by demographic variables-gender, ethnicity, age, or education-has not been investigated despite widespread use of the NSI. In practice, the effectiveness of this tool might be improved with demographically based norms. A large data set of normal community-dwelling individuals was collected using the NSI. Emphasis was made to collect data from individuals of diverse ethnic backgrounds. It was hypothesized that ethnic/cultural backgrounds would have an impact on NSI scores. The results provide normative data for the NSI applicable to a wide variety of individuals of various ages and ethnic backgrounds. An analysis of variance indicated there was no significant difference in NSI responses based on ethnic/cultural background; however, age and gender were found to contribute significantly to the variance associated with symptom endorsement. The NSI appears to be a reliable measure of self-report postconcussive symptoms. Age is a variable associated with differential symptom endorsement on the NSI. Follow-up studies are needed to provide a measure of the sensitivity and specificity of this measure.