Objective: To compare a deep learning (DL)-accelerated non-enhanced abbreviated MRI (AMRI DL) protocol with standard AMRI (AMRI STD) of the liver in terms of image quality and malignant focal lesion detection. Materials and Methods: This retrospective study included 155 consecutive patients (110 male; mean age 62.4 ± 11 years) from two sites who underwent standard liver MRI and additional AMRIDL sequences, specifically DL-accelerated single-shot fast-spin echo (SSFSE DL) and DL-accelerated diffusion-weighted imaging (DWIDL). Additional MRI phantom experiments assessed signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values. Three reviewers evaluated AMRIDL and AMRI STD protocols for image quality using a five-point Likert scale and identified malignant hepatic lesions. Image quality scores and per-lesion sensitivities were compared between AMRIDL and AMRI STD using the Wilcoxon signed-rank test and logistic regression with generalized estimating equations, respectively. Results: Phantom experiments demonstrated comparable SNR and higher CNR for SSFSE DL compared to SSFSE STD, with similar ADC values for DWIDL and DWI STD. Among the 155 patients, 130 (83.9%) had chronic liver disease or a history of intra- or extrahepatic malignancy. Of 104 malignant focal lesions in 64 patients, 58 (55.8%) were hepatocellular carcinomas (HCCs), 38 (36.5%) were metastases, four (3.8%) were cholangiocarcinomas, and four (3.8%) were lymphomas. The pooled per-lesion sensitivity across three readers was 97.6% for AMRIDL, comparable to 97.6% for AMRI STD. Compared with AMRI STD, AMRIDL demonstrated superior image quality regarding structural sharpness, artifacts, and noise (all P < 0.001) and reduced the average scan time by approximately 50% (2 min 29 sec vs. 4 min 11 sec). In patients with chronic liver disease, AMRIDL achieved a 96.6% per-lesion sensitivity for HCC detection, similar to 96.5% for AMRI STD (P > 0.05). Conclusion The AMRIDL protocol offers comparable sensitivity for detecting malignant focal lesions, including HCC while significantly enhancing image quality and reducing scan time by approximately 50% compared to AMRI STD.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: To assess the feasibility of ultrafast brain magnetic resonance imaging (MRI) in pediatric patients. Materials and Methods: We retrospectively reviewed 194 pediatric patients aged 0 to 19 years (median 10.2 years) who underwent both ultrafast and conventional brain MRI between May 2019 and August 2020. Ultrafast MRI sequences included T1 and T2-weighted images (T1WI and T2WI), fluid-attenuated inversion recovery (FLAIR), T2*-weighted image (T2*WI), and diffusion-weighted image (DWI). Qualitative image quality and lesion evaluations were conducted on 5-point Likert scales by two blinded radiologists, with quantitative assessment of lesion count and size on T1WI, T2WI, and FLAIR sequences for each protocol. Wilcoxon signed-rank tests and intraclass correlation coefficient (ICC) analyses were used for comparison. Results: The total scan times for equivalent image contrasts were 1 minute 44 seconds for ultrafast MRI and 15 minutes 30 seconds for conventional MRI. Overall, image quality was lower in ultrafast MRI than in conventional MRI, with mean quality scores ranging from 2.0 to 4.8 for ultrafast MRI and 4.8 to 5.0 for conventional MRI across sequences (P < 0.001 for T1WI, T2WI, FLAIR, and T2*WI for both readers; P = 0.018 [reader 1] and 0.031 [reader 2] for DWI). Lesion detection rates on ultrafast MRI relative to conventional MRI were as follows: T1WI, 97.1%; T2WI, 99.6%; FLAIR, 92.9%; T2*WI, 74.1%; and DWI, 100%. The ICC (95% confidence interval) for lesion size measurements between ultrafast and conventional MRI was as follows: T1WI, 0.998 (0.996–0.999); T2WI, 0.998 (0.997–0.999); and FLAIR, 0.99 (0.985–0.994). Conclusion Ultrafast MRI significantly reduces scan time and provides acceptable results, albeit with slightly lower image quality than conventional MRI, for evaluating intracranial abnormalities in pediatric patients.

Objective: To compare a deep learning (DL)-accelerated non-enhanced abbreviated MRI (AMRI DL) protocol with standard AMRI (AMRI STD) of the liver in terms of image quality and malignant focal lesion detection. Materials and Methods: This retrospective study included 155 consecutive patients (110 male; mean age 62.4 ± 11 years) from two sites who underwent standard liver MRI and additional AMRIDL sequences, specifically DL-accelerated single-shot fast-spin echo (SSFSE DL) and DL-accelerated diffusion-weighted imaging (DWIDL). Additional MRI phantom experiments assessed signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and apparent diffusion coefficient (ADC) values. Three reviewers evaluated AMRIDL and AMRI STD protocols for image quality using a five-point Likert scale and identified malignant hepatic lesions. Image quality scores and per-lesion sensitivities were compared between AMRIDL and AMRI STD using the Wilcoxon signed-rank test and logistic regression with generalized estimating equations, respectively. Results: Phantom experiments demonstrated comparable SNR and higher CNR for SSFSE DL compared to SSFSE STD, with similar ADC values for DWIDL and DWI STD. Among the 155 patients, 130 (83.9%) had chronic liver disease or a history of intra- or extrahepatic malignancy. Of 104 malignant focal lesions in 64 patients, 58 (55.8%) were hepatocellular carcinomas (HCCs), 38 (36.5%) were metastases, four (3.8%) were cholangiocarcinomas, and four (3.8%) were lymphomas. The pooled per-lesion sensitivity across three readers was 97.6% for AMRIDL, comparable to 97.6% for AMRI STD. Compared with AMRI STD, AMRIDL demonstrated superior image quality regarding structural sharpness, artifacts, and noise (all P < 0.001) and reduced the average scan time by approximately 50% (2 min 29 sec vs. 4 min 11 sec). In patients with chronic liver disease, AMRIDL achieved a 96.6% per-lesion sensitivity for HCC detection, similar to 96.5% for AMRI STD (P > 0.05). Conclusion The AMRIDL protocol offers comparable sensitivity for detecting malignant focal lesions, including HCC while significantly enhancing image quality and reducing scan time by approximately 50% compared to AMRI STD.

Objective: This study evaluated the effect of an accelerated three-dimensional (3D) T1-weighted pediatric brain MRI protocol using a deep learning (DL)-based reconstruction algorithm on scan time and image quality. Materials and Methods: This retrospective study included 46 pediatric patients who underwent conventional and accelerated, pre- and post-contrast, 3D T1-weighted brain MRI using a 3T scanner (SIGNA Premier; GE HealthCare) at a single tertiary referral center between March 1, 2023, and April 30, 2023. Conventional scans were reconstructed using intensity Filter A (Conv), whereas accelerated scans were reconstructed using intensity Filter A (Fast_A) and a DL-based algorithm (Fast_DL).Image quality was assessed quantitatively based on the coefficient of variation, relative contrast, apparent signal-to-noise ratio (aSNR), and apparent contrast-to-noise ratio (aCNR) and qualitatively according to radiologists’ ratings of overall image quality, artifacts, noisiness, gray-white matter differentiation, and lesion conspicuity. Results: The acquisition times for the pre- and post-contrast scans were 191 and 135 seconds, respectively, for the conventional scan. With the accelerated protocol, these were reduced to 135 and 80 seconds, achieving time reductions of 29.3% and 40.7%, respectively. DL-based reconstruction significantly reduced the coefficient of variation, improved the aSNR, aCNR, and overall image quality, and reduced the number of artifacts compared with the conventional acquisition method (all P < 0.05). However, the lesion conspicuity remained similar between the two protocols. Conclusion Utilizing a DL-based reconstruction algorithm in accelerated 3D T1-weighted pediatric brain MRI can significantly shorten the acquisition time, enhance image quality, and reduce artifacts, making it a viable option for pediatric imaging.

Objective: To assess the feasibility of ultrafast brain magnetic resonance imaging (MRI) in pediatric patients. Materials and Methods: We retrospectively reviewed 194 pediatric patients aged 0 to 19 years (median 10.2 years) who underwent both ultrafast and conventional brain MRI between May 2019 and August 2020. Ultrafast MRI sequences included T1 and T2-weighted images (T1WI and T2WI), fluid-attenuated inversion recovery (FLAIR), T2*-weighted image (T2*WI), and diffusion-weighted image (DWI). Qualitative image quality and lesion evaluations were conducted on 5-point Likert scales by two blinded radiologists, with quantitative assessment of lesion count and size on T1WI, T2WI, and FLAIR sequences for each protocol. Wilcoxon signed-rank tests and intraclass correlation coefficient (ICC) analyses were used for comparison. Results: The total scan times for equivalent image contrasts were 1 minute 44 seconds for ultrafast MRI and 15 minutes 30 seconds for conventional MRI. Overall, image quality was lower in ultrafast MRI than in conventional MRI, with mean quality scores ranging from 2.0 to 4.8 for ultrafast MRI and 4.8 to 5.0 for conventional MRI across sequences (P < 0.001 for T1WI, T2WI, FLAIR, and T2*WI for both readers; P = 0.018 [reader 1] and 0.031 [reader 2] for DWI). Lesion detection rates on ultrafast MRI relative to conventional MRI were as follows: T1WI, 97.1%; T2WI, 99.6%; FLAIR, 92.9%; T2*WI, 74.1%; and DWI, 100%. The ICC (95% confidence interval) for lesion size measurements between ultrafast and conventional MRI was as follows: T1WI, 0.998 (0.996–0.999); T2WI, 0.998 (0.997–0.999); and FLAIR, 0.99 (0.985–0.994). Conclusion Ultrafast MRI significantly reduces scan time and provides acceptable results, albeit with slightly lower image quality than conventional MRI, for evaluating intracranial abnormalities in pediatric patients.

This guideline outlines the use of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for the diagnosis and management of neuroendocrine tumors, brain tumors, and other tumorous conditions. It provides detailed recommendations on patient preparation, imaging procedures, and result interpretation. Based on inter-national standards and adapted to local clinical practices, the guideline emphasizes safety, quality control, and the effec-tive application of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography for various tumors such as insulinomas, pheochromocytomas, and medullary thyroid carcinoma. It also addresses the use of premedication with carbidopa, fasting protocols, and optimal imaging techniques. The aim is to assist nuclear medicine professionals in delivering precise diagnoses, improving patient outcomes, and accommodating evolving medical knowl-edge and technology. This comprehensive document serves as a practical resource to enhance the accuracy, quality, and safety of 3,4-dihydroxy-6- 18F-fluoro-L-phenylalanine positron emission tomography / computed tomography in oncology.

BACKGROUND/OBJECTIVES: Rosa hybrida has been demonstrated to exert biological effects on several cell types. This study investigated the efficacy of the edible ethanol extract of R.hybrida (EERH) against human colorectal carcinoma cell line (HCT116) cells.MATERIALS/METHODS: HCT116 cells were cultured with different concentrations of EERH (0, 400, 600, 800, and 1,000 µg/mL) in Dulbecco’s modified Eagle medium. Cell viability was measured using the 3-(4,5-dimethylthiazol-2-yl)-2,5 diphenyl tetrazolium bromide and viable cell counting assays. Cell cycle pattern was observed by flow cytometry analysis. The wound-healing migration assay, invasion assay, and zymography were used to determine the migratory and invasive level of HCT116 cells treated with EERH. The protein expression and binding ability level of HCT116 cells following EERH treatment were analyzed via immunoblotting and the electrophoretic mobility shift assay. RESULTS: EERH suppressed HCT116 cell proliferation, thus arresting the G1-phase cell cycle.It also reduced cyclin-dependent kinases and cyclins, which are associated with p27KIP1 expression. Additionally, EERH differentially regulated the phosphorylation of extracellular signal-regulated kinase 1/2, c-Jun NH2-terminal kinase, p38, and protein kinase B. Moreover, EERH treatment inhibited the enzymatic activity of matrix metalloproteinase-9 (MMP-9) and MMP-2, resulting in HCT116 cell migration and invasion. The EERH-induced inhibition of MMP-9 and MMP-2 was attributed to the reduced transcriptional binding of activator protein-1, specificity protein-1, and nuclear factor-κB motifs in HCT116 cells. Kaempferol was identified as the main compound contributing to EERH's antitumor activity. CONCLUSION EERH inhibits HCT116 cell proliferation and metastatic potential. Therefore, it is potentially useful as a preventive and curative nutraceutical agent against colorectal cancer.

The prevalence of postpartum depression (PPD) in Asia is reported to range from 13.53% to 22.31%. However, there remains a gap in the identification of PPD, particularly regarding cultural cutoff points. Therefore, the purpose of this scoping review was to determine the prevalence and associated factors of PPD in Eastern, South-eastern, Western, and Southern Asian countries and analyze the cutoff points of the Edinburgh Postnatal Depression Scale (EPDS) used across these countries. Following Arksey and O'Malley’s five-step scoping review framework, the population was defined as mothers, the concept as the EPDS, and the context as the Asian region. A literature search was conducted using PubMed, Embase, CINAHL, PsycINFO, and Web of Science. The data analysis focused on demographic characteristics, EPDS cutoffs and features, PPD prevalence, and its associated factors. Nineteen studies were selected. Most countries used translated versions of the EPDS with demonstrated reliability and validity. The cutoff scores varied, with most using scores of 10 or higher. The prevalence of PPD ranged from 5.1% to 78.7%. Key associated factors for PPD included cultural factors such as relationships with in-laws and preferences for the newborn’s sex. To improve the accuracy of PPD screening in Asia, the EPDS should be used consistently, and appropriate cutoff criteria must be established. In addition, prevention strategies and programs that reflect the cultural characteristics and social context of Asia need to be developed for the early detection and prevention of PPD.