SCOUT® Localization Using MRI Guidance: Initial Experience.

OBJECTIVE: The Food and Drug Administration approved the MRI-compatible wireless SCOUT localization system in April 2022. The purpose of this study was to evaluate feasibility of SCOUT localization under MRI guidance. We present our initial experience adopting MRI-guided SCOUT localization and compare it to MRI-guided wire localization. METHODS: Electronic medical records and imaging were retrospectively reviewed for all patients who underwent MRI-guided SCOUT or wire localization at our institution between October 2022 and July 2023. Statistical analysis was performed using 2-sample proportion and Wilcoxon rank-sum tests. RESULTS: There were 14 MRI-guided SCOUT and 23 MRI-guided wire localization cases during the study period. All SCOUTs were placed without complication and were considered to be in adequate proximity to the target. There was no significant difference in complication rate (P = .25) or days lapsed from MRI-detected abnormality to surgery (P = .82) between SCOUT and wire cases. SCOUT was placed at time of biopsy for 71% (10/14) of cases. 57% (8/14) of SCOUT cases were used for breast conservation surgery (BCS) compared to 100% (23/23) of wire cases (P <.01), with all 6 SCOUTs not used for BCS placed at time of biopsy. CONCLUSION: MRI-guided SCOUT localization is feasible and offers an alternative to MRI-guided wire localization, with no SCOUT complications reported. SCOUT placement at time of biopsy obviates the need for an additional procedure, but predicting appropriateness is challenging, with 60% (6/10) of SCOUTs placed at time of MRI-guided biopsy not used for subsequent localization surgery.

Reproducibility and repeatability of quantitative T2 and T2* mapping of osteosarcomas in a mouse model.

BACKGROUND: New immunotherapies activate tumor-associated macrophages (TAMs) in the osteosarcoma microenvironment. Iron oxide nanoparticles (IONPs) are phagocytosed by TAMs and, therefore, enable TAM detection on T2*- and T2-weighted magnetic resonance images. We assessed the repeatability and reproducibility of T2*- and T2-mapping of osteosarcomas in a mouse model. METHODS: Fifteen BALB/c mice bearing-murine osteosarcomas underwent magnetic resonance imaging (MRI) on 3-T and 7-T scanners before and after intravenous IONP infusion, using T2*-weighted multi-gradient-echo, T2-weighted fast spin-echo, and T2-weighted multi-echo sequences. Each sequence was repeated twice. Tumor T2 and T2* relaxation times were measured twice by two independent investigators. Repeatability and reproducibility of measurements were assessed. RESULTS: We found excellent agreement between duplicate acquisitions for both T2* and T2 measurements at either magnetic field strength, by the same individual (repeatability), and between individuals (reproducibility). The repeatability concordance correlation coefficient (CCC) for T2* values were 0.99 (coefficients of variation (CoV) 4.43%) for reader 1 and 0.98 (CoV 5.82%) for reader 2. The reproducibility of T2* values between the two readers was 0.99 (CoV 3.32%) for the first acquisitions and 0.99 (CoV 6.30%) for the second acquisitions. Regarding T2 values, the repeatability of CCC was similar for both readers, 0.98 (CoV 3.64% for reader 1 and 4.45% for reader 2). The CCC of the reproducibility of T2 was 0.99 (CoV 3.1%) for the first acquisition and 0.98 (CoV 4.38%) for the second acquisition. CONCLUSIONS: Our results demonstrated high repeatability and reproducibility of quantitative T2* and T2 mapping for monitoring the presence of TAMs in osteosarcomas. RELEVANCE STATEMENT: T2* and T2 measurements of osteosarcomas on IONP-enhanced MRI could allow identifying patients who may benefit from TAM-modulating immunotherapies and for monitoring treatment response. The technique described here could be also applied across a wide range of other solid tumors. KEY POINTS: • Optimal integration of TAM-modulating immunotherapies with conventional chemotherapy remains poorly elucidated. • We found high repeatability of T2* and T2 measurements of osteosarcomas in a mouse model, both with and without IONPs contrast, at 3-T and 7-T MRI field strengths. • T2 and T2* mapping may be used to determine response to macrophage-modulating cancer immunotherapies.

SCOUT® Radar Localization at Time of Breast Biopsy.

OBJECTIVE: Evaluate surgical utilization of SCOUT reflectors placed at breast biopsy. METHODS: Consent was waived for this retrospective IRB-approved, HIPAA-compliant study. Breast biopsy examinations that reported the term "SCOUT" between January 2021 and June 2022 were identified using an institutional search engine. Cases were included if a SCOUT reflector was placed at time of breast biopsy and excluded if lesion pathology was already known. Analysis was performed at the lesion level. A multivariate-regression analysis evaluated 6 variables with potential impact on SCOUT utilization. RESULTS: One hundred twenty-one lesions in 112 patients met inclusion criteria. Biopsy yielded 93% (113/121) malignant, 3% (4/121) elevated risk, 2% (2/121) benign-discordant, and 2% (2/121) benign-concordant results. Two cases lost to follow-up were excluded. SCOUT reflectors were utilized for lumpectomy (58%, 69/119 lesions) and excisional biopsy (6%, 7/119 lesions). SCOUTs were not utilized due to mastectomy (23%, 27/119), subsequent wire localization (2%, 2/119), and nonsurgical cases (12%, 14/119). Reflector placement utilization was 52% higher for findings less than 3.5 cm in size (P <.001), 33% higher in patients without prior treated breast cancer (P = .012), and 19% higher in patients with no suspicious ipsilateral lymph node (P = .048). CONCLUSION: SCOUT reflector placement at time of biopsy was utilized for surgery 64% (76/119) of the time, although most (98%, 119/121) biopsies were malignant, elevated risk, or benign-discordant. Factors increasing reflector utilization include smaller lesion size, no suspicious ipsilateral lymph node, and no prior treated breast cancer.

Prospective Comparison of 68Ga-NeoB and 68Ga-PSMA-R2 PET/MRI in Patients with Biochemically Recurrent Prostate Cancer.

Prostate-specific membrane antigen (PSMA) and gastrin-releasing peptide receptors are both overexpressed in prostate cancer (PC) but may provide complementary information.68Ga-PSMA-R2 and 68Ga-NeoB (DOTA-p-aminomethylaniline-diglycolic acid-DPhe-Gln-Trp-Ala-Val-Gly-His-NH-CH[CH2-CH(CH3)2]2) are novel PET radiopharmaceuticals that were developed for theranostic use. In this phase II imaging study, we assessed the feasibility, safety, and diagnostic performance of 68Ga-NeoB and 68Ga-PSMA-R2 PET/MRI for detection of biochemically recurrent PC. Methods: We prospectively enrolled 27 men with suspected biochemically recurrent PC after initial treatment but noncontributory conventional imaging results (negative or equivocal findings on MRI, CT, and/or bone scan). Participants underwent 68Ga-NeoB and 68Ga-PSMA-R2 PET/MRI within 2 wk in noncontrolled order. The SUVmax of putative PC lesions was measured and compared with a composite reference standard (histopathology, follow-up imaging, prostate-specific antigen change). The SUVmax and SUVmean of background organs were measured. Vital signs were recorded before injection of the radiopharmaceuticals and after the scans. Adverse events were recorded up to 72 h after each scan. Results: The prostate-specific antigen level at enrollment was 3.5 ± 3.9 ng/mL (range, 0.3-13.5 ng/mL). 68Ga-NeoB PET/MRI detected 31 lesions in 18 patients (66.7%), whereas 68Ga-PSMA-R2 identified 20 lesions in 15 participants (55.6%). 68Ga-NeoB PET/MRI showed higher sensitivity (85.7% vs. 71.4%), accuracy (88.9% vs. 77.8%), and negative predictive value (66.7% vs. 50.0%) than 68Ga-PSMA-R2, whereas specificity and positive predictive value were equally high (100.0% for both). In 6 patients, 68Ga-NeoB PET/MRI identified 14 lesions that were false-negative on 68Ga-PSMA-R2 PET/MRI. The mean lesion SUVmax was 6.6 ± 3.2 (range, 2.9-13.2) for 68Ga-NeoB and 4.4 ± 1.5 (range, 2.6-8.8) for 68Ga-PSMA-R2 (P = 0.019). Overall lower uptake was noted in tumors and background organs for 68Ga-PSMA-R2. There were no significant changes in vital signs before and after the scans. No adverse events were reported in the 72-h period after scans. Conclusion: 68Ga-NeoB and 68Ga-PSMA-R2 are safe for diagnostic imaging. 68Ga-NeoB PET/MRI showed better diagnostic performance than 68Ga-PSMA-R2. 68Ga-PSMA-R2 showed overall lower uptake, equally in background organs and tumors, and might therefore not be an ideal theranostic compound. Further evaluation in larger cohorts is needed to confirm our preliminary data.

Abdominal CT metrics in 17,646 patients reveal associations between myopenia, myosteatosis, and medical phenotypes: a phenome-wide association study.

BACKGROUND: Deep learning facilitates large-scale automated imaging evaluation of body composition. However, associations of body composition biomarkers with medical phenotypes have been underexplored. Phenome-wide association study (PheWAS) techniques search for medical phenotypes associated with biomarkers. A PheWAS integrating large-scale analysis of imaging biomarkers and electronic health record (EHR) data could discover previously unreported associations and validate expected associations. Here we use PheWAS methodology to determine the association of abdominal CT-based skeletal muscle metrics with medical phenotypes in a large North American cohort. METHODS: An automated deep learning pipeline was used to measure skeletal muscle index (SMI; biomarker of myopenia) and skeletal muscle density (SMD; biomarker of myosteatosis) from abdominal CT scans of adults between 2012 and 2018. A PheWAS was performed with logistic regression using patient sex and age as covariates to assess for associations between CT-derived muscle metrics and 611 common EHR-derived medical phenotypes. PheWAS P values were considered significant at a Bonferroni corrected threshold (α = 0.05/1222). FINDINGS: 17,646 adults (mean age, 56 years ± 19 [SD]; 57.5% women) were included. CT-derived SMI was significantly associated with 268 medical phenotypes; SMD with 340 medical phenotypes. Previously unreported associations with the highest magnitude of significance included higher SMI with decreased cardiac dysrhythmias (OR [95% CI], 0.59 [0.55-0.64]; P < 0.0001), decreased epilepsy (OR, 0.59 [0.50-0.70]; P < 0.0001), and increased elevated prostate-specific antigen (OR, 1.84 [1.47-2.31]; P < 0.0001), and higher SMD with decreased decubitus ulcers (OR, 0.36 [0.31-0.42]; P < 0.0001), sleep disorders (OR, 0.39 [0.32-0.47]; P < 0.0001), and osteomyelitis (OR, 0.43 [0.36-0.52]; P < 0.0001). INTERPRETATION: PheWAS methodology reveals previously unreported associations between CT-derived biomarkers of myopenia and myosteatosis and EHR medical phenotypes. The high-throughput PheWAS technique applied on a population scale can generate research hypotheses related to myopenia and myosteatosis and can be adapted to research possible associations of other imaging biomarkers with hundreds of EHR medical phenotypes. FUNDING: National Institutes of Health, Stanford AIMI-HAI pilot grant, Stanford Precision Health and Integrated Diagnostics, Stanford Cardiovascular Institute, Stanford Center for Digital Health, and Stanford Knight-Hennessy Scholars.

68Ga-RM2 PET-MRI versus MRI alone for evaluation of patients with biochemical recurrence of prostate cancer: a single-centre, single-arm, phase 2/3 imaging trial.

BACKGROUND: National Comprehensive Cancer Network guidelines include prostate-specific membrane antigen (PSMA)-targeted PET for detection of biochemical recurrence of prostate cancer. However, targeting a single tumour characteristic might not be sufficient to reflect the full extent of disease. Gastrin releasing peptide receptors (GRPR) have been shown to be overexpressed in prostate cancer. In this study, we aimed to evaluate the diagnostic performance of the GRPR-targeting radiopharmaceutical 68Ga-RM2 in patients with biochemical recurrence of prostate cancer. METHODS: This single-centre, single-arm, phase 2/3 trial was done at Stanford University (USA). Adult patients (aged ≥18 years) with biochemical recurrence of prostate cancer, a Karnofsky performance status of 50 or higher, increasing prostate-specific antigen concentration 0·2 ng/mL or more after prostatectomy or 2 ng/mL or more above nadir after radiotherapy, and non-contributory conventional imaging (negative CT or MRI, and bone scan) were eligible. All participants underwent 68Ga-RM2 PET-MRI. The primary outcome was the proportion of patients with PET-positive findings on 68Ga-RM2 PET-MRI compared with MRI alone after initial therapy, at a per-patient and per-lesion level. The primary outcome would be considered met if at least 30% of patients had one or more lesions detected by 68Ga-RM2 PET-MRI and the detection by 68Ga-RM2 PET-MRI was significantly greater than for MRI. Each PET scan was interpreted by three independent masked readers using a standardised evaluation criteria. This study is registered with ClinicalTrials.gov, NCT02624518, and is complete. FINDINGS: Between Dec 12, 2015, and July 27, 2021, 209 men were screened for eligibility, of whom 100 were included in analyses. Median follow-up was 49·3 months (IQR 36·7-59·2). The primary endpoint was met; 68Ga-RM2 PET-MRI was positive in 69 (69%) patients and MRI alone was positive in 40 (40%) patients (p<0·0001). In the per-lesion analysis 68Ga-RM2 PET-MRI showed significantly higher detection rates than MRI alone (143 vs 96 lesions; p<0·0001). No grade 1 or worse events were reported. INTERPRETATION: 68Ga-RM2 PET-MRI showed better diagnostic performance than MRI alone in patients with biochemical recurrence of prostate cancer. Further prospective comparative studies with PSMA-targeted PET are needed to gain a better understanding of GRPR and PSMA expression patterns in these patients. FUNDING: The US Department of Defense.

World Health Organization (WHO) 2022 Classification Update: Radiologic and Pathologic Features of Papillary Renal Cell Carcinomas.

RATIONALE AND OBJECTIVES: To describe imaging and pathology features of newly defined papillary renal cell carcinoma (pRCC) based on the WHO 2022 update. MATERIALS AND METHODS: This retrospective study included 87 patients with 93 pathologically proven papillary renal cell carcinomas who underwent pre-treatment renal mass protocol CT or MRI. Baseline and post-treatment follow-up imaging was evaluated by two radiologists systematically based on established lexicon. RESULTS: At pathology, 63 (68%) were grade 1-2, 29 (31%) were grade 3-4, and 1 (%) was unreported. At surgical pathology, 84 (90%) were localized (≤pT2b), 5 (5%) were pT3a, and none were ≥pT3b; 4 (4%) had unknown pT stage (core biopsies). 33 (35%) had necrosis and 39 (41%) had hemorrhage. None had sarcomatoid or rhabdoid differentiation. At imaging, 73 (83%) were solid and 16 (17%) were cystic. Of 16 cystic masses, four were Bosniak class IIF (three were heterogeneously T1 hyperintense) and 12 were class IV. All were well-circumscribed. 92 (99%) were hypovascular. Median follow-up for 74 patients was 30 months (IQR 12-56). One untreated patient had non-regional nodal metastasis at presentation, and one patient had metastasis to lymph nodes and bones after surgery, but the patient had unresected renal masses elsewhere without pathology. Otherwise, no recurrence or metastases were detected. CONCLUSION: Most pRCCs present as a hypovascular, circumscribed, solid renal mass. A few pRCCs present as the newly defined Bosniak class IIF subtype. Our results can form the basis of a non-invasive, likelihood score to identify this relatively indolent pathology in the era of virtual biopsy and active surveillance.

Comparison of diffusion-weighted MRI and [18F]FDG PET/MRI for treatment monitoring in pediatric Hodgkin and non-Hodgkin lymphoma.

OBJECTIVE: To compare tumor therapy response assessments with whole-body diffusion-weighted imaging (WB-DWI) and 18F-fluorodeoxyglucose ([18F]FDG) PET/MRI in pediatric patients with Hodgkin lymphoma and non-Hodgkin lymphoma. MATERIALS AND METHODS: In a retrospective, non-randomized single-center study, we reviewed serial simultaneous WB-DWI and [18F]FDG PET/MRI scans of 45 children and young adults (27 males; mean age, 13 years ± 5 [standard deviation]; age range, 1-21 years) with Hodgkin lymphoma (n = 20) and non-Hodgkin lymphoma (n = 25) between February 2018 and October 2022. We measured minimum tumor apparent diffusion coefficient (ADCmin) and maximum standardized uptake value (SUVmax) of up to six target lesions and assessed therapy response according to Lugano criteria and modified criteria for WB-DWI. We evaluated the agreement between WB-DWI- and [18F]FDG PET/MRI-based response classifications with Gwet's agreement coefficient (AC). RESULTS: After induction chemotherapy, 95% (19 of 20) of patients with Hodgkin lymphoma and 72% (18 of 25) of patients with non-Hodgkin lymphoma showed concordant response in tumor metabolism and proton diffusion. We found a high agreement between treatment response assessments on WB-DWI and [18F]FDG PET/MRI (Gwet's AC = 0.94; 95% confidence interval [CI]: 0.82, 1.00) in patients with Hodgkin lymphoma, and a lower agreement for patients with non-Hodgkin lymphoma (Gwet's AC = 0.66; 95% CI: 0.43, 0.90). After completion of therapy, there was an excellent agreement between WB-DWI and [18F]FDG PET/MRI response assessments (Gwet's AC = 0.97; 95% CI: 0.91, 1). CONCLUSION: Therapy response of Hodgkin lymphoma can be evaluated with either [18F]FDG PET or WB-DWI, whereas patients with non-Hodgkin lymphoma may benefit from a combined approach. CLINICAL RELEVANCE STATEMENT: Hodgkin lymphoma and non-Hodgkin lymphoma exhibit different patterns of tumor response to induction chemotherapy on diffusion-weighted MRI and PET/MRI. KEY POINTS: • Diffusion-weighted imaging has been proposed as an alternative imaging to assess tumor response without ionizing radiation. • After induction therapy, whole-body diffusion-weighted imaging and PET/MRI revealed a higher agreement in patients with Hodgkin lymphoma than in those with non-Hodgkin lymphoma. • At the end of therapy, whole-body diffusion-weighted imaging and PET/MRI revealed an excellent agreement for overall tumor therapy responses for all lymphoma types.

[Analysis of muscle synergy and muscle functional network at different walking speeds based on surface electromyographic signal].

An in-depth understanding of the mechanism of lower extremity muscle coordination during walking is the key to improving the efficacy of gait rehabilitation in patients with neuromuscular dysfunction. This paper investigates the effect of changes in walking speed on lower extremity muscle synergy patterns and muscle functional networks. Eight healthy subjects were recruited to perform walking tasks on a treadmill at three different speeds, and the surface electromyographic signals (sEMG) of eight muscles of the right lower limb were collected synchronously. The non-negative matrix factorization (NNMF) method was used to extract muscle synergy patterns, the mutual information (MI) method was used to construct the alpha frequency band (8-13 Hz), beta frequency band (14-30 Hz) and gamma frequency band (31-60 Hz) muscle functional network, and complex network analysis methods were introduced to quantify the differences between different networks. Muscle synergy analysis extracted 5 muscle synergy patterns, and changes in walking speed did not change the number of muscle synergy, but resulted in changes in muscle weights. Muscle network analysis found that at the same speed, high-frequency bands have lower global efficiency and clustering coefficients. As walking speed increased, the strength of connections between local muscles also increased. The results show that there are different muscle synergy patterns and muscle function networks in different walking speeds. This study provides a new perspective for exploring the mechanism of muscle coordination at different walking speeds, and is expected to provide theoretical support for the evaluation of gait function in patients with neuromuscular dysfunction.

EEG-CDILNet: a lightweight and accurate CNN network using circular dilated convolution for motor imagery classification.

Objective.The combination of the motor imagery (MI) electroencephalography (EEG) signals and deep learning-based methods is an effective way to improve MI classification accuracy. However, deep learning-based methods often need too many trainable parameters. As a result, the trade-off between the network decoding performance and computational cost has always been an important challenge in the MI classification research.Approach.In the present study, we proposed a new end-to-end convolutional neural network (CNN) model called the EEG-circular dilated convolution (CDIL) network, which takes into account both the lightweight model and the classification accuracy. Specifically, the depth-separable convolution was used to reduce the number of network parameters and extract the temporal and spatial features from the EEG signals. CDIL was used to extract the time-varying deep features that were generated in the previous stage. Finally, we combined the features extracted from the two stages and used the global average pooling to further reduce the number of parameters, in order to achieve an accurate MI classification. The performance of the proposed model was verified using three publicly available datasets.Main results.The proposed model achieved an average classification accuracy of 79.63% and 94.53% for the BCIIV2a and HGD four-classification task, respectively, and 87.82% for the BCIIV2b two-classification task. In particular, by comparing the number of parameters, computation and classification accuracy with other lightweight models, it was confirmed that the proposed model achieved a better balance between the decoding performance and computational cost. Furthermore, the structural feasibility of the proposed model was confirmed by ablation experiments and feature visualization.Significance.The results indicated that the proposed CNN model presented high classification accuracy with less computing resources, and can be applied in the MI classification research.

Modified PROMISE criteria for standardized interpretation of gastrin-releasing peptide receptor (GRPR)-targeted PET.

PURPOSE: There are image interpretation criteria to standardize reporting prostate-specific membrane antigen (PSMA)-targeted positron emission tomography (PET). As up to 10% of prostate cancer (PC) do not express PSMA, other targets such as gastrin-releasing peptide receptor (GRPR) are evaluated. Research on GRPR-targeted imaging has been slowly increasing in usage at staging and biochemical recurrence (BCR) of PC. We therefore propose a modification of the Prostate Cancer Molecular Imaging Standardized Evaluation (PROMISE) criteria (mPROMISE) for GRPR-targeted PET. METHODS: [68 Ga]Ga-RM2 PET data from initially prospective studies performed at our institution were retrospectively reviewed: 44 patients were imaged for staging and 100 patients for BCR PC. Two nuclear medicine physicians independently evaluated PET according to the mPROMISE criteria. A third expert reader served as standard reference. Interreader reliability was computed for GRPR expression, prostate bed (T), lymph node (N), skeleton (Mb), organ (Mc) metastases, and final judgment of the scan. RESULTS: The interrater reliability for GRPR PET at staging was moderate for GRPR expression (0.59; 95% confidence interval [CI] 0.40, 0.78), substantial for T-stage (0.78; 95% CI 0.63, 0.94), and almost perfect for N-stage (0.97; 95% CI 0.92, 1.00) and final judgment (0.92; 95% CI 0.82, 1.00). The interreader agreement at BCR showed substantial agreement for GRPR expression (0.70; 95% CI 0.59, 0.81) and final judgment (0.65; 95% CI 0.53, 0.78), while almost perfect agreement was seen across the major categories (T, N, Mb, Mc). Acceptable performance of the mPROMISE criteria was found for all subsets when compared to the standard reference. CONCLUSION: Interpreting GRPR-targeted PET using the mPROMISE criteria showed its reliability with substantial or almost perfect interrater agreement across all major categories. The proposed modification of the PROMISE criteria will aid clinicians in decreasing the level of uncertainty, and clinical trials to achieve uniform evaluation, reporting, and comparability of GRPR-targeted PET. TRIAL REGISTRATION: Clinicaltrials.gov Identifier: NCT03113617 and NCT02624518.

Tyrosine kinase inhibitor therapy in pediatric sarcoma: Prognostic implications of pulmonary metastatic cavitation.

PURPOSES: This study aims to ascertain the prevalence of cavitations in pulmonary metastases among pediatric and young adult patients with sarcoma undergoing tyrosine kinase inhibitor (TKI) therapy, and assess whether cavitation can predict clinical response and survival outcomes. METHODS: In a single-center retrospective analysis, we examined chest computed tomography (CT) scans of 17 patients (median age 16 years; age range: 4-25 years) with histopathologically confirmed bone (n = 10) or soft tissue (n = 7) sarcoma who underwent TKI treatment for lung metastases. The interval between TKI initiation and the onset of lung nodule cavitation and tumor regrowth were assessed. The combination of all imaging studies and clinical data served as the reference standard for clinical responses. Progression-free survival (PFS) was compared between patients with cavitating and solid nodules using Kaplan-Meier survival analysis and log-rank test. RESULTS: Five out of 17 patients (29%) exhibited cavitation of pulmonary nodules during TKI therapy. The median time from TKI initiation to the first observed cavitation was 79 days (range: 46-261 days). At the time of cavitation, all patients demonstrated stable disease. When the cavities began to fill with solid tumor, 60% (3/5) of patients exhibited progression in other pulmonary nodules. The median PFS for patients with cavitated pulmonary nodules after TKI treatment (6.7 months) was significantly longer compared to patients without cavitated nodules (3.8 months; log-rank p-value = .03). CONCLUSIONS: Cavitation of metastatic pulmonary nodules in sarcoma patients undergoing TKI treatment is indicative of non-progressive disease, and significantly correlates with PFS.

Gesture recognition of continuous wavelet transform and deep convolution attention network.

To solve the problem of missing data features using a deep convolutional neural network (DCNN), this paper proposes an improved gesture recognition method. The method first extracts the time-frequency spectrogram of surface electromyography (sEMG) using the continuous wavelet transform. Then, the Spatial Attention Module (SAM) is introduced to construct the DCNN-SAM model. The residual module is embedded to improve the feature representation of relevant regions, and reduces the problem of missing features. Finally, experiments with 10 different gestures are done for verification. The results validate that the recognition accuracy of the improved method is 96.1%. Compared with the DCNN, the accuracy is improved by about 6 percentage points.

Risk of malignancy in T1-hyperintense Bosniak version 2019 class II and IIF cystic renal masses.

BACKGROUND: Bosniak classification version 2019 includes cystic masses in class II and IIF based partly on their hyperintense appearance at T1-weighted MRI. The prevalence of malignancy in non-enhancing heterogeneously T1-hyperintense masses is unknown, nor whether the pattern of T1 hyperintensity affects malignancy likelihood. PURPOSE: To determine the malignancy proportion among six patterns of T1 hyperintensity within non-enhancing cystic renal masses. METHODS: This retrospective, single-institution study included 72 Bosniak class II and IIF, non-enhancing, T1-hyperintense cystic renal masses. Diagnosis was confirmed by histopathology or by follow-up imaging demonstrating 5-year size and morphologic stability, decreased in size by ≥ 30%, resolution, or Bosniak down-classification. Six patterns of T1 hyperintensity were pre-defined: homogeneous (pattern A), fluid-fluid level (pattern B), peripherally markedly T1-hyperintense (pattern C), containing a T1-hyperintense non-enhancing nodule (pattern D), peripherally T1-hypointense (pattern E), and heterogeneously T1-hyperintense without a distinct pattern (pattern F). Three readers independently assigned each mass to a pattern. Individual and mean malignancy proportion were determined. Mann-Whitney test and Fischer's exact test compared the likelihood of malignancy between patterns. Inter-reader agreement was analyzed with Gwet's agreement coefficient (AC). RESULTS: Among 72 masses, the mean number of masses assigned was 11 (15%) to pattern A, 21 (29%) to pattern B, 6 (8%) to pattern C, 7 (10%) to pattern D, 5 (7%) to pattern E, and 22 (31%) to pattern F. Five of 72 masses (7%) were malignant; none was assigned pattern A, B, or D. Mean malignancy proportion was 5% (0/9, 1/6, and 0/4) for pattern C, 13% (0/4, 1/3, and 1/7) for pattern E, and 18% (5/20, 3/21, and 4/25) for pattern F. Malignant masses were more likely assigned to pattern E or F (p = 0.003-0.039). Inter-reader agreement was substantial (Gwet's AC: 0.68). CONCLUSION: Bosniak version 2019 class IIF masses that are non-enhancing and heterogeneously T1-hyperintense with a fluid-fluid level are likely benign. Those that are non-enhancing and heterogeneously T1-hyperintense without a distinct pattern have a malignancy proportion up to 25% (5/20).

A double-channel multiscale depthwise separable convolutional neural network for abnormal gait recognition.

Abnormal gait recognition is important for detecting body part weakness and diagnosing diseases. The abnormal gait hides a considerable amount of information. In order to extract the fine, spatial feature information in the abnormal gait and reduce the computational cost arising from excessive network parameters, this paper proposes a double-channel multiscale depthwise separable convolutional neural network (DCMSDSCNN) for abnormal gait recognition. The method designs a multiscale depthwise feature extraction block (MDB), uses depthwise separable convolution (DSC) instead of standard convolution in the module and introduces the Bottleneck (BK) structure to optimize the MDB. The module achieves the extraction of effective features of abnormal gaits at different scales, and reduces the computational cost of the network. Experimental results show that the gait recognition accuracy is up to 99.60%, while the memory size of the model is reduced 4.21 times than before optimization.

External Validation of a Five-Tiered CT Algorithm for the Diagnosis of Clear Cell Renal Cell Carcinoma: A Retrospective Five-Reader Study.

BACKGROUND. In 2022, a five-tiered CT algorithm was proposed for predicting whether a small (cT1a) solid renal mass represents clear cell renal cell carcinoma (ccRCC). OBJECTIVE. The purpose of this external validation study was to evaluate the proposed CT algorithm for diagnosis of ccRCC among small solid renal masses. METHODS. This retrospective study included 93 patients (median age, 62 years; 42 women, 51 men) with 97 small solid renal masses that were seen on corticomedullary phase contrast-enhanced CT performed between January 2012 and July 2022 and subsequently underwent surgical resection. Five readers (three attending radiologists, two clinical fellows) independently evaluated masses for the mass-to-cortex corticomedullary attenuation ratio and heterogeneity score; these scores were used to derive the CT score by use of the previously proposed CT algorithm. The CT score's sensitivity, specificity, and PPV for ccRCC were calculated at threshold of 4 or greater, and the NPV for ccRCC was calculated at a threshold of 3 or greater (consistent with thresholds in studies of the MRI-based clear cell likelihood score and the CT algorithm's initial study). The CT score's sensitivity and specificity for papillary RCC were calculated at a threshold of 2 or less. Interreader agreement was assessed using the Gwet agreement coefficient (AC1). RESULTS. Overall, 61 of 97 masses (63%) were malignant and 43 of 97 (44%) were ccRCC. Across readers, CT score had sensitivity ranging from 47% to 95% (pooled sensitivity, 74% [95% CI, 68-80%]), specificity ranging from 19% to 83% (pooled specificity, 59% [95% CI, 52-67%]), PPV ranging from 48% to 76% (pooled PPV, 59% [95% CI, 49-71%]), and NPV ranging from 83% to 100% (pooled NPV, 90% [95% CI, 84-95%]), for ccRCC. A CT score of 2 or less had sensitivity ranging from 44% to 100% and specificity ranging from 77% to 98% for papillary RCC (representing nine of 97 masses). Interreader agreement was substantial for attenuation score (AC1 = 0.70), poor for heterogeneity score (AC1 = 0.17), fair for five-tiered CT score (AC1 = 0.32), and fair for dichotomous CT score at a threshold of 4 or greater (AC1 = 0.24 [95% CI, 0.14-0.33]). CONCLUSION. The five-tiered CT algorithm for evaluation of small solid renal masses was tested in an external sample and showed high NPV for ccRCC. CLINICAL IMPACT. The CT algorithm may be used for risk stratification and patient selection for active surveillance by identifying patients unlikely to have ccRCC.

Surface electromyography-based analysis of the lower limb muscle network and muscle synergies at various gait speeds.

Gait movement is an important activity in daily human life. The coordination of gait movement is directly affected by the cooperation and functional connectivity between muscles. However, the mechanisms of muscle operation at different gait speeds remain unclear. Therefore, this study addressed the gait speed effect on the changes in cooperative modules and functional connectivity between muscles. To this end, surface electromyography (sEMG) signals were collected from eight key lower extremity muscles of twelve healthy subjects walking on a treadmill at high, middle, and low motion speeds. Nonnegative matrix factorization (NNMF) was applied to the sEMG envelope and intermuscular coherence matrix, yielding five muscle synergies. Muscle functional networks were constructed by decomposing the intermuscular coherence matrix, revealing different layers of functional muscle networks across frequencies. In addition, the coupling strength between cooperative muscles grew with gait speed. Different coordination patterns among muscles with changes in gait speed related to the neuromuscular system regulation were identified.

SE-TCN network for continuous estimation of upper limb joint angles.

The maturity of human-computer interaction technology has made it possible to use surface electromyographic signals (sEMG) to control exoskeleton robots and intelligent prostheses. However, the available upper limb rehabilitation robots controlled by sEMG have the shortcoming of inflexible joints. This paper proposes a method based on a temporal convolutional network (TCN) to predict upper limb joint angles by sEMG. The raw TCN depth was expanded to extract the temporal features and save the original information. The timing sequence characteristics of the muscle blocks that dominate the upper limb movement are not apparent, leading to low accuracy of the joint angle estimation. Therefore, this study squeeze-and-excitation networks (SE-Net) to improve the network model of the TCN. Finally, seven movements of the human upper limb were selected for ten human subjects, recording elbow angle (EA), shoulder vertical angle (SVA), and shoulder horizontal angle (SHA) values during their movements. The designed experiment compared the proposed SE-TCN model with the backpropagation (BP) and long short-term memory (LSTM) networks. The proposed SE-TCN systematically outperformed the BP network and LSTM model by the mean RMSE values: by 25.0 and 36.8% for EA, by 38.6 and 43.6% for SHA, and by 45.6 and 49.5% for SVA, respectively. Consequently, its R2 values exceeded those of BP and LSTM by 13.6 and 39.20% for EA, 19.01 and 31.72% for SHA, and 29.22 and 31.89% for SVA, respectively. This indicates that the proposed SE-TCN model has good accuracy and can be used to estimate the angles of upper limb rehabilitation robots in the future.

Diagnostic performance of the "drooping" sign in CT diagnosis of exophytic renal angiomyolipoma.

OBJECTIVE: To evaluate the prevalence of angular interface and the "drooping" sign in exophytic renal angiomyolipomas (AMLs) and the diagnostic performance in differentiating exophytic lipid-poor AMLs from other solid renal masses. METHODS: This IRB-approved, two-center study included 185 patients with 188 exophytic solid renal masses < 4 cm with histopathology and pre-operative CT within 30 days of surgical resection or biopsy. Images were reviewed for the presence of angular interface and the "drooping" sign qualitatively by three readers blinded to the final diagnosis, with majority rules applied. Both features were assessed quantitatively by cohort creators (who are not readers) independently. Free-marginal kappa was used to assess inter-reader agreement and agreement between two methods assessing each feature. Fisher's exact test, Mann-Whitney test, and multivariable logistic regression with two-tailed p < 0.05 were used to determine statistical significance. Diagnostic performance was assessed. RESULTS: Ninety-four patients had 96 AMLs, and 91 patients had 92 non-AMLs. Seventy-four (77%) of AMLs were lipid-poor based on quantitative assessment on CT. The presence of angular interface and the "drooping" sign by both qualitative and quantitative assessment were statistically significantly associated with AMLs (39% (qualitative) and 45% (quantitative) vs 15% (qualitative) and 13% (quantitative), and 48% (qualitative) and 43% (quantitative) vs 4% (qualitative) and 1% (quantitative), respectively, all p < 0.001) in univariable analysis. In multivariable analysis, only the "drooping" sign in either qualitative or quantitative assessment was a statistically significant predictor of AMLs (both p < 0.001). Inter-reader agreement for the "drooping" sign was moderate (k = 0.55) and for angular interface was fair (k = 0.33). Agreement between the two methods of assessing the "drooping" sign was substantial (k = 0.84) and of assessing the angular interface was moderate (k = 0.59). The "drooping" sign both qualitatively and quantitatively, alone or in combination of angular interface, had very high specificity (96-100%) and positive predictive value (PPV) (89-100%), moderate negative predictive value (62-68%), but limited sensitivity (23-49%) for lipid-poor AMLs. CONCLUSION: The "drooping" sign by both qualitative and quantitative assessment is highly specific for lipid-rich and lipid-poor AMLs. This feature alone or in combination with angular interface can aid in CT diagnosis of lipid-poor AMLs with very high specificity and PPV.

Multimodal In Vivo Tracking of Chimeric Antigen Receptor T Cells in Preclinical Glioblastoma Models.

OBJECTIVES: Iron oxide nanoparticles have been used to track the accumulation of chimeric antigen receptor (CAR) T cells with magnetic resonance imaging (MRI). However, the only nanoparticle available for clinical applications to date, ferumoxytol, has caused rare but severe anaphylactic reactions. MegaPro nanoparticles (MegaPro-NPs) provide an improved safety profile. We evaluated whether MegaPro-NPs can be applied for in vivo tracking of CAR T cells in a mouse model of glioblastoma multiforme. MATERIALS AND METHODS: We labeled tumor-targeted CD70CAR (8R-70CAR) T cells and non-tumor-targeted controls with MegaPro-NPs, followed by inductively coupled plasma optical emission spectroscopy, Prussian blue staining, and cell viability assays. Next, we treated 42 NRG mice bearing U87-MG/eGFP-fLuc glioblastoma multiforme xenografts with MegaPro-NP-labeled/unlabeled CAR T cells or labeled untargeted T cells and performed serial MRI, magnetic particle imaging, and histology studies. The Kruskal-Wallis test was conducted to evaluate overall group differences, and the Mann-Whitney U test was applied to compare the pairs of groups. RESULTS: MegaPro-NP-labeled CAR T cells demonstrated significantly increased iron uptake compared with unlabeled controls ( P < 0.01). Cell viability, activation, and exhaustion markers were not significantly different between the 2 groups ( P > 0.05). In vivo, tumor T2* relaxation times were significantly lower after treatment with MegaPro-NP-labeled CAR T cells compared with untargeted T cells ( P < 0.01). There is no significant difference in tumor growth inhibition between mice injected with labeled and unlabeled CAR T cells. CONCLUSIONS: MegaPro-NPs can be used for in vivo tracking of CAR T cells. Because MegaPro-NPs recently completed phase II clinical trial investigation as an MRI contrast agent, MegaPro-NP is expected to be applied to track CAR T cells in cancer immunotherapy trials in the near future.