Is there value in the routine inclusion of chest computed tomography for patients with gastrointestinal stromal tumor?

PURPOSE: National Comprehensive Cancer Network guidelines suggest chest CT when gastrointestinal stromal tumors are larger than 2 cm. We evaluate the value of screening the chest region during initial and follow-up CT. METHOD: Single institution retrospective analysis of GIST cancer registry for patients diagnosed between May 2010 and November 2019 with tumor > 2 cm. We collected the patient demographics and clinical data; reviewed all CT scans of the chest region and recorded the lung nodules. Patients were grouped into lung nodule group and non-nodule group. Categorical variables were compared with the Chi square test and continuous variables with the Mann-Whitney U test. The survival probability was determined from Kaplan-Meier survival analysis and log-rank test for comparing differences. RESULTS: The final cohort included 382 patients (median age 61 years-old [interquartile range: 52-71]) and grouped into non-nodule group (n = 284) and lung nodule group (n = 98). The frequency of the CT scan was more in lung nodule group (8 [5-12]) than in non-nodule group (4 [2-9], p < 0.001). The lung nodule group had more CT including the chest region (6 [3-10] vs 3 [1-7], p < 0.001). In progressive lung nodules (8/98 [8 %]), only one patient had confirmed lung metastasis from GIST (1/382 [3 %]). There was no difference in overall survival between nodule groups (p = 0.12). CONCLUSIONS: GIST patients with tumors larger than 2 cm have extremely low risk for lung metastasis. Routine inclusion of chest CT scan in staging and follow up is unnecessary.

Advancements, Challenges, and Future Prospects in Clinical Hyperpolarized Magnetic Resonance Imaging: A Comprehensive Review.

Hyperpolarized (HP) magnetic resonance imaging (MRI) is a groundbreaking imaging platform advancing from research to clinical practice, offering new possibilities for real-time, non-invasive metabolic imaging. This review explores the latest advancements, challenges, and future directions of HP MRI, emphasizing its transformative impact on both translational research and clinical applications. By employing techniques such as dissolution Dynamic Nuclear Polarization (dDNP), Parahydrogen-Induced Polarization (PHIP), Signal Amplification by Reversible Exchange (SABRE), and Spin-Exchange Optical Pumping (SEOP), HP MRI achieves enhanced nuclear spin polarization, enabling in vivo visualization of metabolic pathways with exceptional sensitivity. Current challenges, such as limited imaging windows, complex pre-scan protocols, and data processing difficulties, are addressed through innovative solutions like advanced pulse sequences, bolus tracking, and kinetic modeling. We highlight the evolution of HP MRI technology, focusing on its potential to revolutionize disease diagnosis and monitoring by revealing metabolic processes beyond the reach of conventional MRI and positron emission tomography (PET). Key advancements include the development of novel tracers like [2-13C]pyruvate and [1-13C]-alpha-ketoglutarate and improved data analysis techniques, broadening the scope of clinical metabolic imaging. Future prospects emphasize integrating artificial intelligence, standardizing imaging protocols, and developing new hyperpolarized agents to enhance reproducibility and expand clinical capabilities particularly in oncology, cardiology, and neurology. Ultimately, we envisioned HP MRI as a standardized modality for dynamic metabolic imaging in clinical practice.

Initial Experience of Metabolic Imaging with Hyperpolarized [1-13C]pyruvate MRI in Kidney Transplant Patients.

BACKGROUND: Kidney transplant is the treatment of choice for patients with end-stage renal disease. Early detection of allograft injury is important to delay or prevent irreversible damage. PURPOSE: To investigate the feasibility of hyperpolarized (HP) [1-13C]pyruvate MRI for assessing kidney allograft metabolism. STUDY TYPE: Prospective. SUBJECTS: 6 participants (mean age, 45.2 ± 12.4 years, 2 females) scheduled for kidney allograft biopsy and 5 patients (mean age, 59.6 ± 10.4 years, 2 females) with renal cell carcinoma (RCC). FIELD STRENGTH/SEQUENCE: 3 Tesla, T2-weighted fast spin echo, multi-echo gradient echo, single shot diffusion-weighted echo-planar imaging, and time-resolved HP 13C metabolite-selective imaging. ASSESSMENT: Five of the six kidney allograft participants underwent biopsy after MRI. Estimated glomerular filtration rate (eGFR) and urine protein-to-creatine ratio (uPCR) were collected within 4 weeks of MRI. Kidney metabolism was quantified from HP [1-13C]pyruvate MRI using the lactate-to-pyruvate ratio in allograft kidneys and non-tumor bearing kidneys from RCC patients. STATISTICAL TESTS: Descriptive statistics (mean ± standard deviation). RESULTS: Biopsy was performed a mean of 9 days (range 5-19 days) after HP [1-13C]pyruvate MRI. Three biopsies were normal, one showed low-grade fibrosis and one showed moderate microvascular inflammation. All had stable functioning allografts with eGFR > 60 mL/min/1.73 m2 and normal uPCR. One participant who did not undergo biopsy had reduced eGFR of 49 mL/min/1.73 m2 and elevated uPCR. The mean lactate-to-pyruvate ratio was 0.373 in participants with normal findings (n = 3) and 0.552 in participants with abnormal findings (n = 2). The lactate-to-pyruvate ratio was highest (0.847) in the participant with reduced eGFR and elevated uPRC. Native non-tumor bearing kidneys had a mean lactate-to-pyruvate ratio of 0.309. DATA CONCLUSION: Stable allografts with normal findings at biopsy showed lactate-to-pyruvate ratios similar to native non-tumor bearing kidneys, whereas allografts with abnormal findings showed higher lactate-to-pyruvate ratios.

Initial Experience of Metabolic Imaging With Hyperpolarized [1-13C]pyruvate MRI in Kidney Transplant Patients.

BACKGROUND: Kidney transplant is the treatment of choice for patients with end-stage renal disease. Early detection of allograft injury is important to delay or prevent irreversible damage. PURPOSE: To investigate the feasibility of hyperpolarized (HP) [1-13C]pyruvate MRI for assessing kidney allograft metabolism. STUDY TYPE: Prospective. SUBJECTS: Six participants (mean age, 45.2 ± 12.4 years, two females) scheduled for kidney allograft biopsy and five patients (mean age, 59.6 ± 10.4 years, two females) with renal cell carcinoma (RCC). FIELD STRENGTH/SEQUENCE: Three Tesla, T2-weighted fast spin echo, multi-echo gradient echo, single shot diffusion-weighted echo-planar imaging, and time-resolved HP 13C metabolite-selective imaging. ASSESSMENT: Five of the six kidney allograft participants underwent biopsy after MRI. Estimated glomerular filtration rate (eGFR) and urine protein-to-creatine ratio (uPCR) were collected within 4 weeks of MRI. Kidney metabolism was quantified from HP [1-13C]pyruvate MRI using the lactate-to-pyruvate ratio in allograft kidneys and non-tumor bearing kidneys from RCC patients. STATISTICAL TESTS: Descriptive statistics (mean ± SD). RESULTS: Biopsy was performed a mean of 9 days (range 5-19 days) after HP [1-13C]pyruvate MRI. Three biopsies were normal, one showed low-grade fibrosis and one showed moderate microvascular inflammation. All had stable functioning allografts with eGFR >60 mL/min/1.73 m2 and normal uPCR. One participant who did not undergo biopsy had reduced eGFR of 49 mL/min/1.73 m2 and elevated uPCR. The mean lactate-to-pyruvate ratio was 0.373 in participants with normal findings (N = 3) and 0.552 in participants with abnormal findings (N = 2). The lactate-to-pyruvate ratio was highest (0.847) in the participant with reduced eGFR and elevated uPRC. Native non-tumor bearing kidneys had a mean lactate-to-pyruvate ratio of 0.309. DATA CONCLUSION: Stable allografts with normal findings at biopsy showed lactate-to-pyruvate ratios similar to native non-tumor bearing kidneys, whereas allografts with abnormal findings showed higher lactate-to-pyruvate ratios. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Hyperpolarized Carbon-13 Magnetic Resonance Imaging: Technical Considerations and Clinical Applications.

Hyperpolarized (HP) carbon-13 (13C) MRI represents an innovative approach for noninvasive, real-time assessment of dynamic metabolic flux, with potential integration into routine clinical MRI. The use of [1-13C]pyruvate as a probe and its conversion to [1-13C]lactate constitute an extensively explored metabolic pathway. This review comprehensively outlines the establishment of HP 13C-MRI, covering multidisciplinary team collaboration, hardware prerequisites, probe preparation, hyperpolarization techniques, imaging acquisition, and data analysis. This article discusses the clinical applications of HP 13C-MRI across various anatomical domains, including the brain, heart, skeletal muscle, breast, liver, kidney, pancreas, and prostate. Each section highlights the specific applications and findings pertinent to these regions, emphasizing the potential versatility of HP 13C-MRI in diverse clinical contexts. This review serves as a comprehensive update, bridging technical aspects with clinical applications and offering insights into the ongoing advancements in HP 13C-MRI.

Hyperpolarized [1-13C]-pyruvate MRS evaluates immune potential and predicts response to radiotherapy in cervical cancer.

BACKGROUND: Monitoring pyruvate metabolism in the spleen is important for assessing immune activity and achieving successful radiotherapy for cervical cancer due to the significance of the abscopal effect. We aimed to explore the feasibility of utilizing hyperpolarized (HP) [1-13C]-pyruvate magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) to evaluate pyruvate metabolism in the human spleen, with the aim of identifying potential candidates for radiotherapy in cervical cancer. METHODS: This prospective study recruited six female patients with cervical cancer (median age 55 years; range 39-60) evaluated using HP [1-13C]-pyruvate MRI/MRS at baseline and 2 weeks after radiotherapy. Proton (1H) diffusion-weighted MRI was performed in parallel to estimate splenic cellularity. The primary outcome was defined as tumor response to radiotherapy. The Student t-test was used for comparing 13C data between the groups. RESULTS: The splenic HP [1-13C]-lactate-to-total carbon (tC) ratio was 5.6-fold lower in the responders than in the non-responders at baseline (p = 0.009). The splenic [1-13C]-lactate-to-tC ratio revealed a 1.7-fold increase (p = 0.415) and the splenic [1-13C]-alanine-to-tC ratio revealed a 1.8-fold increase after radiotherapy (p = 0.482). The blood leukocyte differential count revealed an increased proportion of neutrophils two weeks following treatment, indicating enhanced immune activity (p = 0.013). The splenic apparent diffusion coefficient values between the groups were not significantly different. CONCLUSIONS: This exploratory study revealed the feasibility of HP [1-13C]-pyruvate MRS of the spleen for evaluating baseline immune potential, which was associated with clinical outcomes of cervical cancer after radiotherapy. TRIAL REGISTRATION: ClinicalTrials.gov NCT04951921 , registered 7 July 2021. RELEVANCE STATEMENT: This prospective study revealed the feasibility of using HP 13C MRI/MRS for assessing pyruvate metabolism of the spleen to evaluate the patients' immune potential that is associated with radiotherapeutic clinical outcomes in cervical cancer. KEY POINTS: • Effective radiotherapy induces abscopal effect via altering immune metabolism. • Hyperpolarized 13C MRS evaluates patients' immune potential non-invasively. • Pyruvate-to-lactate conversion in the spleen is elevated following radiotherapy.

Distinct changes to pancreatic volume rather than pancreatic autoantibody positivity: insights into immune checkpoint inhibitors induced diabetes mellitus.

BACKGROUND: Immune checkpoint inhibitors (ICI) are promising treatment options for various cancers. However, their use is associated with immune-related adverse events (irAEs), including ICI-induced diabetes mellitus (ICI-DM). This study aimed to investigate the clinical features of ICI-DM, with a particular focus on alterations to pancreatic volume. METHODS: We conducted a retrospective review of 2829 patients who received ICI treatment at the Chang Gung Memorial Hospital, Linkou, between January 2014 and December 2021. New-onset diabetes or diabetic ketoacidosis (DKA) was identified in ten patients receiving ICI therapy. Pancreatic volumes were assessed by manual segmentation of computed tomography (CT) images before and after ICI-DM diagnosis. RESULTS: Among these ten patients, nivolumab was the most commonly used ICI (50.0%), followed by pembrolizumab (30.0%) and atezolizumab (20.0%). One patient received combination therapy with nivolumab and ipilimumab. The median age was 63.01 years (range: 40.1 - 87.8). ICI-DM developed after a median of 13.5 cycles (range: 2 - 42) of ICI treatment or 9.85 months (range:1.5 - 21.3) since ICI initiation. The initial presentation was DKA in 60.0% of patients. All patients had low or undetectable C-peptide levels (range: <0.033 - 0.133 nmol/L) and were negative for most type 1 diabetes mellitus (T1DM)-related autoantibodies; only one patient tested positive for glutamic acid decarboxylase antibodies. CT imaging revealed significant pancreatic atrophy, with a median pancreatic volume decrease of 19.92% (P = 0.038) from baseline and sustained significant decline at last follow-up (median - 37.14%, P = 0.012). CONCLUSIONS: ICI-DM is often accompanied by pancreatic atrophy and approximately two-thirds of patients initially present with DKA. Although the majority of ICI-DM patients lack T1DM-related autoantibodies, identifying diminished pancreatic volumes through CT imaging provides valuable clues into the subclinical aspects of ICI-DM development, aiding in the prevention of diabetic emergencies. TRIAL REGISTRATION: Not applicable.

Machine Learning Radiomics Signature for Differentiating Lymphoma versus Benign Splenomegaly on CT.

BACKGROUND: We aimed to develop and validate a preoperative CT-based radiomics signature for differentiating lymphoma versus benign splenomegaly. METHODS: We retrospectively analyzed CT studies from 139 patients (age range 26-93 years, 43% female) between 2011 and 2019 with histopathological diagnosis of the spleen (19 lymphoma, 120 benign) and divided them into developing (n = 79) and testing (n = 60) datasets. The volumetric radiomic features were extracted from manual segmentation of the whole spleen on venous-phase CT imaging using PyRadiomics package. LASSO regression was applied for feature selection and development of the radiomic signature, which was interrogated with the complete blood cell count and differential count. All p values < 0.05 were considered to be significant. RESULTS: Seven features were selected for constructing the radiomic signature after feature selection, including first-order statistics (10th percentile and Robust Mean Absolute Deviation), shape-based (Surface Area), and texture features (Correlation, MCC, Small Area Low Gray-level Emphasis and Low Gray-level Zone Emphasis). The radiomic signature achieved an excellent diagnostic accuracy of 97%, sensitivity of 89%, and specificity of 98%, distinguishing lymphoma versus benign splenomegaly in the testing dataset. The radiomic signature significantly correlated with the platelet and segmented neutrophil percentage. CONCLUSIONS: CT-based radiomics signature can be useful in distinguishing lymphoma versus benign splenomegaly and can reflect the changes in underlying blood profiles.

Localization of Colorectal Cancer Lesions in Contrast-Computed Tomography Images via a Deep Learning Approach.

Abdominal computed tomography (CT) is a frequently used imaging modality for evaluating gastrointestinal diseases. The detection of colorectal cancer is often realized using CT before a more invasive colonoscopy. When a CT exam is performed for indications other than colorectal evaluation, the tortuous structure of the long, tubular colon makes it difficult to analyze the colon carefully and thoroughly. In addition, the sensitivity of CT in detecting colorectal cancer is greatly dependent on the size of the tumor. Missed incidental colon cancers using CT are an emerging problem for clinicians and radiologists; consequently, the automatic localization of lesions in the CT images of unprepared bowels is needed. Therefore, this study used artificial intelligence (AI) to localize colorectal cancer in CT images. We enrolled 190 colorectal cancer patients to obtain 1558 tumor slices annotated by radiologists and colorectal surgeons. The tumor sites were double-confirmed via colonoscopy or other related examinations, including physical examination or image study, and the final tumor sites were obtained from the operation records if available. The localization and training models used were RetinaNet, YOLOv3, and YOLOv8. We achieved an F1 score of 0.97 (±0.002), a mAP of 0.984 when performing slice-wise testing, 0.83 (±0.29) sensitivity, 0.97 (±0.01) specificity, and 0.96 (±0.01) accuracy when performing patient-wise testing using our derived model YOLOv8 with hyperparameter tuning.

Developing a Method to Estimate the Downstream Metabolite Signals from Hyperpolarized [1-13C]Pyruvate.

Hyperpolarized carbon-13 MRI has the advantage of allowing the study of glycolytic flow in vivo or in vitro dynamically in real-time. The apparent exchange rate constant of a metabolite dynamic signal reflects the metabolite changes of a disease. Downstream metabolites can have a low signal-to-noise ratio (SNR), causing apparent exchange rate constant inconsistencies. Thus, we developed a method that estimates a more accurate metabolite signal. This method utilizes a kinetic model and background noise to estimate metabolite signals. Simulations and in vitro studies with photon-irradiated and control groups were used to evaluate the procedure. Simulated and in vitro exchange rate constants estimated using our method were compared with the raw signal values. In vitro data were also compared to the Area-Under-Curve (AUC) of the cell medium in 13C Nuclear Magnetic Resonance (NMR). In the simulations and in vitro experiments, our technique minimized metabolite signal fluctuations and maintained reliable apparent exchange rate constants. In addition, the apparent exchange rate constants of the metabolites showed differences between the irradiation and control groups after using our method. Comparing the in vitro results obtained using our method and NMR, both solutions showed consistency when uncertainty was considered, demonstrating that our method can accurately measure metabolite signals and show how glycolytic flow changes. The method enhanced the signals of the metabolites and clarified the metabolic phenotyping of tumor cells, which could benefit personalized health care and patient stratification in the future.

Gastric hydrodistension CT versus CT without gastric distension in preoperative TN staging of gastric carcinoma: analysis of single-center cancer registry.

Accurate staging of gastric cancer is essential for the selection and optimization of therapy. Hydrodistension of the stomach is recommended to improve the accuracy of preoperative staging with contrast-enhanced multidetector computed tomography (MDCT). This study compares the performance of contrast-enhanced gastric water distension versus a nondistension MDCT protocol for T and N staging and serosal invasion in comparison to surgical histopathology. After propensity score matching, 86 patients in each group were included for analysis. The overall accuracy of distension versus nondistension group in T staging was 45% (95% CI 35-56) and 55% (95% CI 44-65), respectively (p = 0.29). There was no difference in the sensitivity and specificity in individual T staging and assessment of serosal invasion (all p > 0.41). Individual stage concordance with pathology was not significantly different (all p > 0.41). The overall accuracy of N staging was the same for distension and nondistension groups (51% [95% CI 40-62]). The majority of N0 staging (78-81%) were correctly staged, whereas N3 staging cases (63-68%) were predominantly understaged. In summary, there was no significant difference in the diagnostic performance of individual TN staging and assessment of serosal invasion using MDCT with or without gastric water distension.

Development of specialized magnetic resonance acquisition techniques for human hyperpolarized [13 C,15 N2 ]urea + [1-13 C]pyruvate simultaneous perfusion and metabolic imaging.

PURPOSE: This study aimed to develop and demonstrate the in vivo feasibility of a 3D stack-of-spiral balanced steady-state free precession(3D-bSSFP) urea sequence, interleaved with a metabolite-specific gradient echo (GRE) sequence for pyruvate and metabolic products, for improving the SNR and spatial resolution of the first hyperpolarized 13 C-MRI human study with injection of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea. METHODS: A metabolite-specific bSSFP urea imaging sequence was designed using a urea-specific excitation pulse, optimized TR, and 3D stack-of-spiral readouts. Simulations and phantom studies were performed to validate the spectral response of the sequence. The image quality of urea data acquired by the 3D-bSSFP sequence and the 2D-GRE sequence was evaluated with 2 identical injections of co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea formula in a rat. Subsequently, the feasibility of the acquisition strategy was validated in a prostate cancer patient. RESULTS: Simulations and phantom studies demonstrated that 3D-bSSFP sequence achieved urea-only excitation, while minimally perturbing other metabolites (<1%). An animal study demonstrated that compared to GRE, bSSFP sequence provided an ∼2.5-fold improvement in SNR without perturbing urea or pyruvate kinetics, and bSSFP approach with a shorter spiral readout reduced blurring artifacts caused by J-coupling of [13 C,15 N2 ]urea. The human study demonstrated the in vivo feasibility and data quality of the acquisition strategy. CONCLUSION: The 3D-bSSFP urea sequence with a stack-of-spiral acquisition demonstrated significantly increased SNR and image quality for [13 C,15 N2 ]urea in co-hyperpolarized [1-13 C]pyruvate and [13 C,15 N2 ]urea imaging studies. This work lays the foundation for future human studies to achieve high-quality and high-SNR metabolism and perfusion images.

Clinical impact of a deep learning system for automated detection of missed pulmonary nodules on routine body computed tomography including the chest region.

OBJECTIVES: To evaluate the clinical impact of a deep learning system (DLS) for automated detection of pulmonary nodules on computed tomography (CT) images as a second reader. METHODS: This single-centre retrospective study screened 21,150 consecutive body CT studies from September 2018 to February 2019. Pulmonary nodules detected by the DLS on axial CT images but not mentioned in initial radiology reports were flagged. Flagged images were scored by four board-certificated radiologists each with at least 5 years of experience. Nodules with scores of 2 (understandable miss) or 3 (should not be missed) were then categorised as unlikely to be clinically significant (2a or 3a) or likely to be clinically significant (2b or 3b) according to the 2017 Fleischner guidelines for pulmonary nodules. The miss rate was defined as the total number of studies receiving scores of 2 or 3 divided by total screened studies. RESULTS: Among 172 nodules flagged by the DLS, 60 (35%) missed nodules were confirmed by the radiologists. The nodules were further categorised as 2a, 2b, 3a, and 3b in 24, 14, 10, and 12 studies, respectively, with an overall positive predictive value of 35%. Missed pulmonary nodules were identified in 0.3% of all CT images, and one-third of these lesions were considered clinically significant. CONCLUSIONS: Use of DLS-assisted automated detection as a second reader can identify missed pulmonary nodules, some of which may be clinically significant. CLINICAL RELEVANCE/APPLICATION: Use of DLS to help radiologists detect pulmonary lesions may improve patient care. KEY POINTS: • DLS-assisted automated detection as a second reader is feasible in a large consecutive cohort. • Performance of combined radiologists and DLS was better than DLS or radiologists alone. • Pulmonary nodules were missed more frequently in abdomino-pelvis CT than the thoracic CT.

Aspartate and Acetate Fuel Gastrointestinal Stromal Tumors Beyond the Warburg Effect.

Metabolic reprogramming is closely linked to the tumorigenesis and drug resistance of gastrointestinal stromal tumors (GISTs). Mapping the metabolic orbit of GISTs is a prerequisite if intervention against the metabolic vulnerability of refractory GISTs is desirable. Methods: A total of 43 patients with treatment-naïve GISTs who had undergone surgical resections were enrolled, on whom a metabolomics profile detected from surgical specimens was constructed based on the 1H-nuclear magnetic resonance (NMR) platform. The mRNA and protein levels of GLUT1, HK2, ACSS2, and FASN were assayed. Dual-tracer 18F-FDG/11C-acetate PET imaging was introduced before surgery in 15 patients. Results: 1H-NMR-based metabolomics revealed that GISTs were characterized by upregulation of glutamate, ascorbate, aspartate and glycine and downregulation of choline, creatine, glucose and glycerol. Bioinformatics analysis showed that the TCA cycle and alanine, aspartate, and glutamate metabolism were the two leading pathways. High- and nonhigh-risk (including intermediate-, low-, and very low-risk) GISTs preferentially displayed upregulation of HK2 and ACSS2, respectively, echoed by in vivo imaging that high- and nonhigh-risk GISTs preferentially exhibited higher uptake of 18F-FDG and 11C-acetate, respectively, while 18F-FDG and 11C-acetate were complementary to each other. Nuclear ACSS2 was exclusively identified in high-risk GISTs. Conclusion: We describe a metabolic landscape of GISTs that read aspartate as a de facto "oncometabolite," which was replenished via the TCA cycle and alanine, aspartate, and glutamate metabolism. Glycolysis and ACSS2-mediated acetate metabolism competed and complemented fatty acid synthesis, although glycolysis remained an aggressive phenotype.

Using MRI Measurement to Improve Accuracy of Femoral Component Sizing in Oxford Unicompartmental Knee Arthroplasty.

Unicompartmental knee arthroplasty (UKA) can achieve better kinematics and faster recovery than total knee arthroplasty. The Phase III Oxford UKA system has five sizes of femoral components to approximate the normal knee geometry. However, these different sizes may also induce problems, such as the misselection of component size. Different criteria have been proposed to predict the ideal size preoperatively. However, no single method can be applied universally. Therefore, this study aimed to develop a preoperative measurement using knee magnetic resonance imaging (MRI) to predict femoral component size. A total of 68 patients who underwent UKA were investigated from June 2019 to April 2020. 16 knees using a different MRI protocol were excluded. We developed an MRI measurement method to determine femoral size instead of gender- and height-based methods. The accuracy of different methods was compared using postoperative true lateral view radiographs. Three different kinds of gender- and height-based criteria, preoperative templating and intraoperative spoon measurement were compared. The accuracy of MRI measurement was 90.3%. Therefore, a significant difference was found between MRI measurements and all other methods, such as templating or gender- and height-based methods. In conclusion, the MRI measurement method can be concluded to accurately predict femoral component size in UKA. This method could be used regardless of different ethnic groups, individual knee geometry, or soft tissue tension.

Monitoring Early Glycolytic Flux Alterations Following Radiotherapy in Cancer and Immune Cells: Hyperpolarized Carbon-13 Magnetic Resonance Imaging Study.

Alterations in metabolism following radiotherapy affect therapeutic efficacy, although the mechanism underlying such alterations is unclear. A new imaging technique-named dynamic nuclear polarization (DNP) carbon-13 magnetic resonance imaging (MRI)-probes the glycolytic flux in a real-time, dynamic manner. The [1-13C]pyruvate is transported by the monocarboxylate transporter (MCT) into cells and converted into [1-13C]lactate by lactate dehydrogenase (LDH). To capture the early glycolytic alterations in the irradiated cancer and immune cells, we designed a preliminary DNP 13C-MRI study by using hyperpolarized [1-13C]pyruvate to study human FaDu squamous carcinoma cells, HMC3 microglial cells, and THP-1 monocytes before and after irradiation. The pyruvate-to-lactate conversion rate (kPL [Pyr.]) calculated by kinetic modeling was used to evaluate the metabolic alterations. Western blotting was performed to assess the expressions of LDHA, LDHB, MCT1, and MCT4 proteins. Following irradiation, the pyruvate-to-lactate conversion rates on DNP 13C-MRI were significantly decreased in the FaDu and the HMC3 cells but increased in the THP-1 cells. Western blot analysis confirmed the similar trends in LDHA and LDHB expression levels. In conclusion, DNP 13C-MRI non-invasively captured the different glycolytic alterations among cancer and immune systems in response to irradiation, implying its potential for clinical use in the future.

A preliminary study of hepatocellular carcinoma post proton beam therapy using MRI as an early prediction of treatment effectiveness.

PURPOSE: To demonstrate the feasibility of magnetic resonance imaging (MRI) for early prediction of proton beam therapy (PBT) effectiveness in hepatocellular carcinoma (HCC). METHODS: Clinical data of the HCC patients without regional lymph node involvement or distant metastasis who received PBT at this institution between 2014 and 2017 were reviewed. A total of 43 patients were included. Tumor regression pattern after PBT were examined on the basis of follow-up duration. The variables were compared between patients with and without early tumor regression (ETR). RESULTS: The median follow-up duration was 40 months (range, 9-62 months). The cumulative overall survival rate at 6 months, 1 years and 5 years was 100%, 88.4%, 63.4%, respectively. Child-Pugh class A, local tumor control (LTC), complete response (CR), and ETR were significantly associated with overall survival (p < 0.05 each). Of 43 patients, 25 patients (58.1%) reached CR in the PBT-irradiated region. Twelve patients (27.9%) had a partial response and 3 patients (7.0%) had a stationary disease. Three patients (7.0%) developed in-field progression. The LTC rate at 5 years was 93.0%. Of the 25 patients who achieved a CR in the PBT-irradiated region, the median time to CR was 5 months (range, 1-19 months). Twenty-two patients (51.2%) showed ETR of the HCC, while 21 patients (48.8%) showed non-ETR. A significant association was observed between ETR and CR of the HCC after PBT (p < 0.001). CONCLUSION: The post-PBT MRI follow-up at 3 months is helpful for monitoring therapeutic response. ETR of the HCC predicted a higher rate of CR and was associated with overall survival, which provides more accurate clinical management.

Risk of nephrogenic systemic fibrosis in patients with impaired renal function undergoing fixed-dose gadoxetic acid-enhanced magnetic resonance imaging.

PURPOSE: To assess the risk of nephrogenic systemic fibrosis (NSF) in patients with renal impairment undergoing gadoxetic acid-enhanced magnetic resonance imaging. METHODS: This retrospective study included patients who had an estimated glomerular filtration rate (eGFR) below 60 mL/min per 1.73 m2 or had undergone dialysis around the time of gadoxetic acid exposure from January 2010 to November 2019. All patients received at least one intravenous injection of gadoxetic acid at a fixed dose of 2.5 mmol. The primary endpoint was the development of NSF after exposure to gadoxetic acid based on Girardi's clinicopathological scoring system. RESULTS: A total of 204 patients with renal impairment received 424 injections of gadoxetic acid, of which 131 and 54 had an eGFR of 30-59 and < 30 mL/min per 1.73 m2, respectively, and 19 had undergone hemodialysis. Eighty-two patients received multiple injections, with 23 receiving five or more injections. The dose of each exposure ranged from 0.02 to 0.07 mmol/kg and the cumulative doses ranged from 0.02 to 0.45 mmol/kg. Thirty-three patients had concomitant Child-Pugh class B or C cirrhosis. No NSF was detected during follow-up (median 20 months; range 6 days to 111 months). The upper bound of the 95% confidence interval for NSF risk was 2.2% and 1.1% per patient and examination, respectively. CONCLUSION: No NSF was detected in this study. However, it is premature to ascertain the risk of NSF using gadoxetic acid in patients with renal impairment and further studies are warranted.

Simple Stepwise Approach to Differentiate Cyst-Like Soft-Tissue Masses by Using Time-Resolved Magnetic Resonance Angiography.

This retrospective study aimed to differentiate cyst-like musculoskeletal soft-tissue masses by using time-resolved magnetic resonance angiography (MRA). During May 2015 to November 2019, patients with cyst-like soft-tissue masses examined through contrast-enhanced MRI followed by histologic diagnosis were included. The masses were classified into vascular lesions, solid lesions, and true cysts. Size, T1 hyperintensity, T2 composition, perilesional edema, time-resolved MRA, and static internal enhancement were assessed. The time-resolved MRA manifestations were classified into vascular pooling, solid stain, and occult lesion. Imaging predictors for each type of mass were identified through logistic regression and were used to develop a diagnostic flowchart. A total of 80 patients (47 men; median age, 42 years) were included, with 22 vascular lesions, 38 solid lesions, and 20 true cysts. The T2 composition, time-resolved MRA, and static internal enhancement were significantly different among the masses. Vascular pooling on time-resolved MRA was the sole predictor of vascular lesions (odds ratio = 722.0, p < 0.001). Solid stain on time-resolved MRA was the sole predictor of solid lesions (odds ratio = 73.6, p < 0.001). Occult lesion on time-resolved MRA (odds ratio = 7.4, p = 0.001) and absence of static internal enhancement (odds ratio = 80.0, p < 0.001) both predicted true cysts, while the latter was the sole predictor of true cysts after multivariate analysis. A diagnostic flowchart based on time-resolved MRA correctly classified 89% of the masses. In conclusion, time-resolved MRA accurately differentiates cyst-like soft-tissue masses and provides guidance for management.

Response evaluation for immunotherapy through semi-automatic software based on RECIST 1.1, irRC, and iRECIST criteria: comparison with subjective assessment.

BACKGROUND: Pseudoprogression is difficult to diagnose in patients undergoing immunotherapy. Subjective response assessment is still common in clinical practice. PURPOSE: To evaluate the differences between response evaluation criteria in solid tumors version 1.1 (RECIST 1.1), immune-related response criteria (irRC), and modified RECIST 1.1 for immunotherapy (iRECIST) through semi-automatic software, and to compare iRECIST-based response evaluation with subjective assessment. MATERIAL AND METHODS: The best overall response of each patient based on RECIST 1.1, irRC, and iRECIST was determined on CT scans through semi-automatic software and the differences between the criteria were evaluated. Criteria-based response evaluation through semi-automatic software was compared with subjective assessment on radiology report by correlating the best overall response to overall survival. RESULTS: A total of 21 patients were included (five patients with melanoma, 12 patients with non-small-cell lung cancer, and four patients with hepatocellular carcinoma). Two patients with progressive disease by RECIST 1.1 but non-progressive disease by irRC and iRECIST eventually experienced tumor response and had favorable outcomes, indicating pseudoprogression. The survival difference between patients with non-progressive disease and progressive disease was better stratified through iRECIST-based response evaluation (P = 0.078) than that through subjective assessment (P = 0.501). CONCLUSION: Pseudoprogression in immunotherapy may be captured through semi-automatic software utilizing irRC or iRECIST criteria. iRECIST-based response evaluation may provide a better survival stratification compared with subjective assessment.