Multi-reader multiparametric DECT study evaluating different strengths of iterative and deep learning-based image reconstruction techniques.

OBJECTIVES: To perform a multi-reader comparison of multiparametric dual-energy computed tomography (DECT) images reconstructed with deep-learning image reconstruction (DLIR) and standard-of-care adaptive statistical iterative reconstruction-V (ASIR-V). METHODS: This retrospective study included 100 patients undergoing portal venous phase abdominal CT on a rapid kVp switching DECT scanner. Six reconstructed DECT sets (ASIR-V and DLIR, each at three strengths) were generated. Each DECT set included 65 keV monoenergetic, iodine, and virtual unenhanced (VUE) images. Using a Likert scale, three radiologists performed qualitative assessments for image noise, contrast, small structure visibility, sharpness, artifact, and image preference. Quantitative assessment was performed by measuring attenuation, image noise, and contrast-to-noise ratios (CNR). For the qualitative analysis, Gwet's AC2 estimates were used to assess agreement. RESULTS: DECT images reconstructed with DLIR yielded better qualitative scores than ASIR-V images except for artifacts, where both groups were comparable. DLIR-H images were rated higher than other reconstructions on all parameters (p-value < 0.05). On quantitative analysis, there was no significant difference in the attenuation values between ASIR-V and DLIR groups. DLIR images had higher CNR values for the liver and portal vein, and lower image noise, compared to ASIR-V images (p-value < 0.05). The subgroup analysis of patients with large body habitus (weight ≥ 90 kg) showed similar results to the study population. Inter-reader agreement was good-to-very good overall. CONCLUSION: Multiparametric post-processed DECT datasets reconstructed with DLIR were preferred over ASIR-V images with DLIR-H yielding the highest image quality scores. CLINICAL RELEVANCE STATEMENT: Deep-learning image reconstruction in dual-energy CT demonstrated significant benefits in qualitative and quantitative image metrics compared to adaptive statistical iterative reconstruction-V. KEY POINTS: Dual-energy CT (DECT) images reconstructed using deep-learning image reconstruction (DLIR) showed superior qualitative scores compared to adaptive statistical iterative reconstruction-V (ASIR-V) reconstructed images, except for artifacts where both reconstructions were rated comparable. While there was no significant difference in attenuation values between ASIR-V and DLIR groups, DLIR images showed higher contrast-to-noise ratios (CNR) for liver and portal vein, and lower image noise (p value < 0.05). Subgroup analysis of patients with large body habitus (weight ≥ 90 kg) yielded similar findings to the overall study population.

Subcutaneous and Visceral Adipose Tissue Reference Values From the Framingham Heart Study Thoracic and Abdominal CT.

BACKGROUND: Computed tomography (CT) captures the quantity, density, and distribution of subcutaneous and visceral (SAT and VAT) adipose tissue compartments. These metrics may change with age and sex. OBJECTIVE: The study aims to provide age-, sex-, and vertebral level-specific reference values for SAT on chest CT and for SAT and VAT on abdomen CT. MATERIALS AND METHODS: This secondary analysis of an observational study describes SAT and VAT measurements in participants of the Framingham Heart Study without known cancer diagnosis who underwent at least 1 of 2 CT examinations between 2002 and 2011. We used a previously validated machine learning-assisted pipeline and rigorous quality assurance to segment SAT at the fifth, eighth, and tenth thoracic vertebra (T5, T8, T10) and SAT and VAT at the third lumbar vertebra (L3). For each metric, we measured cross-sectional area (cm2) and mean attenuation (Hounsfield units [HU]) and calculated index (area/height2) (cm2/m2) and gauge (attenuation × index) (HU × cm2/m2). We summarized body composition metrics by age and sex and modeled sex-, age-, and vertebral level-specific reference curves. RESULTS: We included 14,898 single-level measurements from up to 4 vertebral levels of 3797 scans of 3730 Framingham Heart Study participants (1889 [51%] male with a mean [standard deviation] age of 55.6 ± 10.6 years; range, 38-81 years). The mean VAT index increased with age from 65 (cm2/m2) in males and 29 (cm2/m2) in females in the <45-year-old age group to 99 (cm2/m2) in males and 60 (cm2/m2) in females in >75-year-old age group. The increase of SAT with age was less pronounced, resulting in the VAT/SAT ratio increasing with age. A free R package and online interactive visual web interface allow access to reference values. CONCLUSIONS: This study establishes age-, sex-, and vertebral level-specific reference values for CT-assessed SAT at vertebral levels T5, T8, T10, and L3 and VAT at vertebral level L3.

Material density dual-energy CT images: value added in early diagnosis of peritoneal carcinomatosis : Original research.

OBJECTIVE: To assess the value of material density (MD) images generated from a rapid kilovoltage-switching dual-energy CT (rsDECT) in early detection of peritoneal carcinomatosis (PC). MATERIALS AND METHODS: Thirty patients (60 ± 13 years; 24 women) with PC detected on multiple abdominal DECT scans were included. Four separate DECTs with varying findings of PC from each patient were used for qualitative/quantitative analysis, resulting in a total of 120 DECT scans (n = 30 × 4). Three radiologists independently reviewed DECT images (65 keV alone and 65 keV + MD) for diagnosis of PC (diagnostic confidence, lesion conspicuity, sharpness/delineation and image quality) using a 5-point Likert scale. Quantitative estimation of contrast-to-noise ratio (CNR) was done. Wilcoxon signed-rank test and Odds ratio calculation were used to compare between the two protocols. Inter-observer agreement was evaluated using Kappa coefficient analysis. P values < 0.05 were considered statistically significant. RESULTS: 65 keV + MD images showed a slightly higher sensitivity (89%[95%CI:84,92]) for PC detection compared with 65 keV images alone without statistical significance (84%[95%CI:78,88], p = 0.11) with the experienced reader showing significant improvement (98%[95%CI:93,100] vs. 90%[95%CI:83,94], p = 0.02). On a per-patient basis, use of MD images allowed earlier diagnosis for PC in an additional 13-23% of patients. On sub-group analysis, earlier diagnosis of PC was particularly beneficial in patients with BMI ≤ 29.9 kg/m2. 65 keV + MD images showed higher diagnostic confidence, lesion conspicuity, and lesion sharpness for the experienced reader (p < 0.001). CNR was higher in MD images (1.7 ± 0.5) than 65 keV images (0.1 ± 0.02, p < 0.001). All readers showed moderate interobserver agreement for determining PC by both protocols (κ = 0.58 and κ = 0.47). CONCLUSION: MD images allow earlier and improved detection of PC with the degree of benefit varying based on reader experience and patient body habitus.

Functional hemodynamic imaging markers for the prediction of pathological outcomes in breast cancer patients treated with neoadjuvant chemotherapy.

Significance: Achieving pathologic complete response (pCR) after neoadjuvant chemotherapy (NACT) is a significant predictor of increased likelihood of survival in breast cancer patients. Early prediction of pCR is of high clinical value as it could allow personalized adjustment of treatment regimens in non-responding patients for improved outcomes. Aim: We aim to assess the association between hemoglobin-based functional imaging biomarkers derived from diffuse optical tomography (DOT) and the pathological outcome represented by pCR at different timepoints along the course of NACT. Approach: Twenty-two breast cancer patients undergoing NACT were enrolled in a multimodal DOT and X-ray digital breast tomosynthesis (DBT) imaging study in which their breasts were imaged at different compression levels. Logistic regressions were used to study the associations between DOT-derived imaging markers evaluated after the first and second cycles of chemotherapy, respectively, with pCR status determined after the conclusion of NACT at the time of surgery. Receiver operating characteristic curve analysis was also used to explore the predictive performance of selected DOT-derived markers. Results: Normalized tumor HbT under half compression was significantly lower in the pCR group compared to the non-pCR group after two chemotherapy cycles (p=0.042). In addition, the change in normalized tumor StO2 upon reducing compression from full to half mammographic force was identified as another potential indicator of pCR at an earlier time point, i.e., after the first chemo cycle (p=0.038). Exploratory predictive assessments showed that AUCs using DOT-derived functional imaging markers as predictors reach as high as 0.75 and 0.71, respectively, after the first and second chemo cycle, compared to AUCs of 0.50 and 0.53 using changes in tumor size measured on DBT and MRI. Conclusions: These findings suggest that breast DOT could be used to assist response assessment in women undergoing NACT, a critical but unmet clinical need, and potentially enable personalized adjustments of treatment regimens.

High-Frequency Jet Ventilation Versus Spontaneous Respiration for Percutaneous Cryoablation of Lung Tumors: Comparison of Adverse Events and Procedural Efficiency.

BACKGROUND. High-frequency jet ventilation (HFJV) facilitates accurate probe placement in percutaneous ablation of lung tumors but may increase risk for adverse events, including systemic air embolism. OBJECTIVE. The purpose of this study was to compare major adverse events and procedural efficiency of percutaneous lung ablation with HFJV under general anesthesia to spontaneous respiration (SR) under moderate sedation. METHODS. This retrospective study included consecutive adults who underwent CT-guided percutaneous cryoablation of one or more lung tumors with HFJV or SR between January 1, 2017, and May 31, 2023. We compared major adverse events (Common Terminology Criteria for Adverse Events grade ≥ 3) within 30 days postprocedure and hospital length of stay (HLOS) of 2 days or more using logistic regression analysis. We compared procedure time, room time, CT guidance acquisition time, CT guidance radiation dose, total radiation dose, and pneumothorax using generalized estimating equations. RESULTS. Overall, 139 patients (85 women, 54 men; median age, 68 years) with 310 lung tumors (82% metastases) underwent 208 cryoablations (HFJV, n = 129; SR, n = 79). HFJV showed greater rates than SR for the treatment of multiple tumors per session (43% vs 19%, respectively; p = .02) and tumors in a nonperipheral location (48% vs 24%, p < .001). Major adverse event rate was 8% for HFJV and 5% for SR (p = .46). No systemic air embolism occurred. HLOS was 2 days or more in 17% of sessions and did not differ significantly between HFJV and SR (p = .64), including after adjusting for probe number per session, chronic obstructive pulmonary disease, and operator experience (p = .53). Ventilation modalities showed no significant difference in procedure time, CT guidance acquisition time, CT guidance radiation dose, or total radiation dose (all p > .05). Room time was longer for HFJV than SR (median, 154 vs 127 minutes, p < .001). For HFJV, the median anesthesia time was 136 minutes. Ventilation modalities did not differ in the frequencies of pneumothorax or pneumothorax requiring chest tube placement (both p > .05). CONCLUSION. HFJV appears to be as safe as SR but had longer room times. HFJV can be used in complex cases without significantly impacting HLOS of 2 days or more, procedure time, or radiation exposure. CLINICAL IMPACT. Selection of the ventilation modality during percutaneous lung ablation should be based on patient characteristics and anticipated procedural requirements as well as operator preference.

Multimodality Management of Thoracic Tumors: Initial Experience With a Multidisciplinary Thoracic Ablation Conference.

BACKGROUND: This study aimed to describe lesion-specific management of thoracic tumors referred for consideration of image-guided thermal ablation (IGTA) at a newly established multidisciplinary ablation conference. METHODS: This retrospective single-center cohort study included consecutive patients with non-small cell lung cancer (NSCLC) or thoracic metastases evaluated from June 2020 to January 2022 in a multidisciplinary conference. Outcomes included the management recommendation, treatments received (IGTA, surgical resection, stereotactic body radiation therapy [SBRT], multimodality management), and number of tumors treated per patient. Pearson's chi-square test was used to assess for a change in management, and Poisson regression was used to compare the number of tumors by treatment received. RESULTS: The study included 172 patients (58 % female; median age, 69 years; 56 % thoracic metastases; 27 % multifocal primary lung cancer; 59 % ECOG 0 [range, 0-3]) assessed in 206 evaluations. For the patients with NSCLC, IGTA was considered the most appropriate local therapy in 12 %, equal to SBRT in 22 %, and equal to lung resection in 3 % of evaluations. For the patients with thoracic metastases, IGTA was considered the most appropriate local therapy in 22 %, equal to SBRT in 12 %, and equal to lung resection in 3 % of evaluations. Although all patients were referred for consideration of IGTA, less than one third of patients with NSCLC or thoracic metastases underwent IGTA (p < 0.001). Multimodality management allowed for treatment of more tumors per patient than single-modality management (p < 0.01). CONCLUSIONS: Multidisciplinary evaluation of patients with thoracic tumors referred for consideration of IGTA significantly changed patient management and facilitated lesion-specific multimodality management.

Muscle Reference Values From Thoracic and Abdominal CT for Sarcopenia Assessment: The Framingham Heart Study.

BACKGROUND: Loss of muscle mass is a known feature of sarcopenia and predicts poor clinical outcomes. Although muscle metrics can be derived from routine computed tomography (CT) images, sex-specific reference values at multiple vertebral levels over a wide age range are lacking. OBJECTIVE: The aim of this study was to provide reference values for skeletal muscle mass and attenuation on thoracic and abdominal CT scans in the community-based Framingham Heart Study cohort to aid in the identification of sarcopenia. MATERIALS AND METHODS: This secondary analysis of a prospective trial describes muscle metrics by age and sex for participants from the Framingham Heart Study without prior history of cancer who underwent at least 1 CT scan between 2002 and 2011. Using 2 previously validated machine learning algorithms followed by human quality assurance, skeletal muscle was analyzed on a single axial CT image per level at the 5th, 8th, 10th thoracic, and 3rd lumbar vertebral body (T5, T8, T10, L3). Cross-sectional muscle area (cm 2 ), mean skeletal muscle radioattenuation (SMRA, in Hounsfield units), skeletal muscle index (SMI, in cm 2 /m 2 ), and skeletal muscle gauge (SMRA·SMI) were calculated. Measurements were summarized by age group (<45, 45-54, 55-64, 65-74, ≥75 years), sex, and vertebral level. Models enabling the calculation of age-, sex-, and vertebral-level-specific reference values were created and embedded into an open access online Web application. RESULTS: The cohort consisted of 3804 participants (1917 [50.4%] males; mean age, 55.6 ± 11.8 years; range, 33-92 years) and 7162 CT scans. Muscle metrics qualitatively decreased with increasing age and female sex. CONCLUSIONS: This study established age- and sex-specific reference values for CT-based muscle metrics at thoracic and lumbar vertebral levels. These values may be used in future research investigating the role of muscle mass and attenuation in health and disease, and to identify sarcopenia.

[ 11 C]-PBR28 positron emission tomography signal as an imaging marker of joint inflammation in knee osteoarthritis.

ABSTRACT: Although inflammation is known to play a role in knee osteoarthritis (KOA), inflammation-specific imaging is not routinely performed. In this article, we evaluate the role of joint inflammation, measured using [ 11 C]-PBR28, a radioligand for the inflammatory marker 18-kDa translocator protein (TSPO), in KOA. Twenty-one KOA patients and 11 healthy controls (HC) underwent positron emission tomography/magnetic resonance imaging (PET/MRI) knee imaging with the TSPO ligand [ 11 C]-PBR28. Standardized uptake values were extracted from regions-of-interest (ROIs) semiautomatically segmented from MRI data, and compared across groups (HC, KOA) and subgroups (unilateral/bilateral KOA symptoms), across knees (most vs least painful), and against clinical variables (eg, pain and Kellgren-Lawrence [KL] grades). Overall, KOA patients demonstrated elevated [ 11 C]-PBR28 binding across all knee ROIs, compared with HC (all P 's < 0.005). Specifically, PET signal was significantly elevated in both knees in patients with bilateral KOA symptoms (both P 's < 0.01), and in the symptomatic knee ( P < 0.05), but not the asymptomatic knee ( P = 0.95) of patients with unilateral KOA symptoms. Positron emission tomography signal was higher in the most vs least painful knee ( P < 0.001), and the difference in pain ratings across knees was proportional to the difference in PET signal ( r = 0.74, P < 0.001). Kellgren-Lawrence grades neither correlated with PET signal (left knee r = 0.32, P = 0.19; right knee r = 0.18, P = 0.45) nor pain ( r = 0.39, P = 0.07). The current results support further exploration of [ 11 C]-PBR28 PET signal as an imaging marker candidate for KOA and a link between joint inflammation and osteoarthritis-related pain severity.

CT Texture Analysis in Nonalcoholic Fatty Liver Disease (NAFLD).

Background: Nonalcoholic fatty liver disease (NAFLD) is the most common form of liver disease worldwide. There are limited biomarkers that can detect progression from simple steatosis to nonalcoholic steatohepatitis (NASH). The purpose of our study was to utilize CT texture analysis to distinguish steatosis from NASH. Methods: 16 patients with NAFLD (38% male, median (interquartile range): age 57 (48-64) years, BMI 37.5 (35.0-46.8) kg/m2) underwent liver biopsy and abdominal non-contrast CT. CT texture analysis was performed to quantify gray-level tissue summaries (e.g., entropy, kurtosis, skewness, and attenuation) using commercially available software (TexRad, Cambridge England). Logistic regression analyses were performed to quantify the association between steatosis/NASH status and CT texture. ROC curve analysis was performed to determine sensitivity, specificity, AUC, 95% CIs, and cutoff values of texture parameters to differentiate steatosis from NASH. Results: By histology, 6/16 (37%) of patients had simple steatosis and 10/16 (63%) had NASH. Patients with NASH had lower entropy (median, interquartile range (IQR): 4.3 (4.1, 4.8) vs. 5.0 (4.9, 5.2), P = 0.013) and lower mean value of positive pixels (MPP) (34.4 (21.8, 52.2) vs. 66.5 (57.0, 70.7), P = 0.009) than those with simple steatosis. Entropy values below 4.73 predict NASH with 100% (95%CI: 67-100%) specificity and 80% (50-100%) sensitivity, AUC: 0.88. MPP values below 54.0 predict NASH with 100% (67-100%) specificity and 100% (50-100%) sensitivity, AUC 0.90. Conclusion: Our study provides preliminary evidence that CT texture analysis may serve as a novel imaging biomarker for disease activity in NAFLD and the discrimination of steatosis and NASH.

Differentiation of patients with and without prostate cancer using urine 1 H NMR metabolomics.

Prostate cancer (PCa) is one of the most prevalent cancers in men worldwide. For its detection, serum prostate-specific antigen (PSA) screening is commonly used, despite its lack of specificity, high false positive rate, and inability to discriminate indolent from aggressive PCa. Following increases in serum PSA levels, clinicians often conduct prostate biopsies with or without advanced imaging. Nuclear magnetic resonance (NMR)-based metabolomics has proven to be promising for advancing early-detection and elucidation of disease progression, through the discovery and characterization of novel biomarkers. This retrospective study of urine-NMR samples, from prostate biopsy patients with and without PCa, identified several metabolites involved in energy metabolism, amino acid metabolism, and the hippuric acid pathway. Of note, lactate and hippurate-key metabolites involved in cellular proliferation and microbiome effects, respectively-were significantly altered, unveiling widespread metabolomic modifications associated with PCa development. These findings support urine metabolomics profiling as a promising strategy to identify new clinical biomarkers for PCa detection and diagnosis.

Incorporating algorithmic uncertainty into a clinical machine deep learning algorithm for urgent head CTs.

Machine learning (ML) algorithms to detect critical findings on head CTs may expedite patient management. Most ML algorithms for diagnostic imaging analysis utilize dichotomous classifications to determine whether a specific abnormality is present. However, imaging findings may be indeterminate, and algorithmic inferences may have substantial uncertainty. We incorporated awareness of uncertainty into an ML algorithm that detects intracranial hemorrhage or other urgent intracranial abnormalities and evaluated prospectively identified, 1000 consecutive noncontrast head CTs assigned to Emergency Department Neuroradiology for interpretation. The algorithm classified the scans into high (IC+) and low (IC-) probabilities for intracranial hemorrhage or other urgent abnormalities. All other cases were designated as No Prediction (NP) by the algorithm. The positive predictive value for IC+ cases (N = 103) was 0.91 (CI: 0.84-0.96), and the negative predictive value for IC- cases (N = 729) was 0.94 (0.91-0.96). Admission, neurosurgical intervention, and 30-day mortality rates for IC+ was 75% (63-84), 35% (24-47), and 10% (4-20), compared to 43% (40-47), 4% (3-6), and 3% (2-5) for IC-. There were 168 NP cases, of which 32% had intracranial hemorrhage or other urgent abnormalities, 31% had artifacts and postoperative changes, and 29% had no abnormalities. An ML algorithm incorporating uncertainty classified most head CTs into clinically relevant groups with high predictive values and may help accelerate the management of patients with intracranial hemorrhage or other urgent intracranial abnormalities.

Are you angry? Neural basis of impaired facial expression recognition in pre-manifest Huntington's.

INTRODUCTION: Early non-motor symptoms in Huntington's disease (HD), including visual perceptual difficulties, can have profound negative impacts on quality of life. In particular, deficits in emotion recognition may contribute to misinterpretation of social cues, and may adversely affect interpersonal relationships, work relationships and/or general well-being. This may be particularly salient during the pre-manifest period, a period prior to the onset of motor symptoms. We sought to evaluate impairments in emotion recognition in gene-positive individuals who did not meet criterial for a diagnosis of HD; we also sought to determine associations between emotion recognition processing and altered cortico-striatal circuitry. METHODS: We used a standardized battery to evaluate performance on a facial expression recognition task in a cohort of motor pre-manifest HD (Pre-HD) individuals (N = 21). Functional MRI (fMRI) was then used to assess the face processing network in a subset (N = 15). RESULTS: We found significantly decreased response accuracy to certain facial expressions, particularly of negative emotions (p < 0.001) in Pre-HDs. When Pre-HDs viewed faces with different emotions, activation within the Superior Temporal Sulcus (fSTS) was reduced compared to controls; in contrast, the level of evoked response within other face-selective cortical regions was comparable. CONCLUSION: Early deficits in emotion recognition in Pre-HD appear to be associated with alterations in the fSTS response, a distinctly different pathway from that involved in face perception and provide support for early cognitive and behavioral interventions.

Rate of True-Positive Findings of COVID-19 Typical Appearance at Chest CT per RSNA Consensus Guidelines in an Increasingly Vaccinated Population.

Background RSNA consensus guidelines for COVID-19-related chest CT are widely used but, to the knowledge of the authors, their rate of true-positive findings for COVID-19 pneumonia in vaccinated patients has not been assessed. Purpose To assess the rate of true-positive findings of typical appearance for COVID-19 at chest CT by using RSNA guidelines in fully vaccinated patients with polymerase chain reaction (PCR)-confirmed COVID-19 infection compared with unvaccinated patients. Materials and Methods Included were patients with COVID-19 who had typical appearance on chest CT images and one PCR test for COVID-19 with a positive result or two tests with negative results within 7 days of undergoing chest CT between January 2021 and January 2022 at a quaternary academic medical center. True-positive findings were defined as chest CT images interpreted as COVID-19 typical appearance and PCR-confirmed COVID-19 infection within 7 days. Logistic regression models were constructed to quantify the association between PCR results and vaccination status, vaccination status and COVID-19 variants, and vaccination status and number of months. Results Included were 652 patients (median age, 59 years; IQR, 48-72 years; 371 men [57%]) with CT scans classified as typical appearance. Of those patients, 483 (74%) were unvaccinated and 169 (26%) were fully vaccinated. The overall rate of true-positive findings on CT images rated as typical appearance was lower in vaccinated versus unvaccinated patients (70 of 169 [41%; 95% CI: 34, 49] vs 352 of 483 [73%; 95% CI: 69, 77]; odds ratio [OR], 3.8 [95% CI: 2.6, 5.5]; P < .001). Unvaccinated patients were more likely to have true-positive findings on CT images compared with fully vaccinated patients during the peaks of COVID-19 variants Alpha (OR, 16; 95% CI: 6, 42; P < .001) and Delta (OR, 8; 95% CI: 4, 16; P < .001), but no statistical differences were found during the peak of the Omicron variant (OR, 1.7; 95% CI: 0.3, 11; P = .56). Conclusion Fully vaccinated patients with confirmed COVID-19 breakthrough infections had lower rates of true-positive findings of COVID-19 typical appearance at chest CT. © RSNA, 2022 Supplemental material is available for this article.

Simultaneous multislice diffusion-weighted imaging versus standard diffusion-weighted imaging in whole-body PET/MRI.

OBJECTIVE: To compare standard (STD-DWI) single-shot echo-planar imaging DWI and simultaneous multislice (SMS) DWI during whole-body positron emission tomography (PET)/MRI regarding acquisition time, image quality, and lesion detection. METHODS: Eighty-three adults (47 females, 57%), median age of 64 years (IQR 52-71), were prospectively enrolled from August 2018 to March 2020. Inclusion criteria were (a) abdominal or pelvic tumors and (b) PET/MRI referral from a clinician. Patients were excluded if whole-body acquisition of STD-DWI and SMS-DWI sequences was not completed. The evaluated sequences were axial STD-DWI at b-values 50-400-800 s/mm2 and the apparent diffusion coefficient (ADC), and axial SMS-DWI at b-values 50-300-800 s/mm2 and ADC, acquired with a 3-T PET/MRI scanner. Three radiologists rated each sequence's quality on a five-point scale. Lesion detection was quantified using the anatomic MRI sequences and PET as the reference standard. Regression models were constructed to quantify the association between all imaging outcomes/scores and sequence type. RESULTS: The median whole-body STD-DWI acquisition time was 14.8 min (IQR 14.1-16.0) versus 7.0 min (IQR 6.7-7.2) for whole-body SMS-DWI, p < 0.001. SMS-DWI image quality scores were higher than STD-DWI in the abdomen (OR 5.31, 95% CI 2.76-10.22, p < 0.001), but lower in the cervicothoracic junction (OR 0.21, 95% CI 0.10-0.43, p < 0.001). There was no significant difference in the chest, mediastinum, pelvis, and rectum. STD-DWI detected 276/352 (78%) lesions while SMS-DWI located 296/352 (84%, OR 1.46, 95% CI 1.02-2.07, p = 0.038). CONCLUSIONS: In cancer staging and restaging, SMS-DWI abbreviates acquisition while maintaining or improving the diagnostic yield in most anatomic regions. KEY POINTS: • Simultaneous multislice diffusion-weighted imaging enables faster whole-body image acquisition. • Simultaneous multislice diffusion-weighted imaging maintains or improves image quality when compared to single-shot echo-planar diffusion-weighted imaging in most anatomical regions. • Simultaneous multislice diffusion-weighted imaging leads to superior lesion detection.

Factors Associated with Hospital Length of Stay and Adverse Events following Percutaneous Ablation of Lung Tumors.

PURPOSE: To explore the association between risk factors established in the surgical literature and hospital length of stay (HLOS), adverse events, and hospital readmission within 30 days after percutaneous image-guided thermal ablation of lung tumors. MATERIALS AND METHODS: This bi-institutional retrospective cohort study included 131 consecutive adult patients (67 men [51%]; median age, 65 years) with 180 primary or metastatic lung tumors treated in 131 sessions (74 cryoablation and 57 microwave ablation) from 2006 to 2019. Age-adjusted Charlson Comorbidity Index, sex, performance status, smoking status, chronic obstructive pulmonary disease (COPD), primary lung cancer versus pulmonary metastases, number of tumors treated per session, maximum axial tumor diameter, ablation modality, number of pleural punctures, anesthesia type, pulmonary artery-to-aorta ratio, lung densitometry, sarcopenia, and adipopenia were evaluated. Associations between risk factors and outcomes were assessed using univariable and multivariable generalized linear models. RESULTS: In univariable analysis, HLOS was associated with current smoking (incidence rate ratio [IRR], 4.54 [1.23-16.8]; P = .02), COPD (IRR, 3.56 [1.40-9.04]; P = .01), cryoablations with ≥3 pleural punctures (IRR, 3.13 [1.07-9.14]; P = .04), general anesthesia (IRR, 10.8 [4.18-27.8]; P < .001), and sarcopenia (IRR, 2.66 [1.10-6.44]; P = .03). After multivariable adjustment, COPD (IRR, 3.56 [1.57-8.11]; P = .003) and general anesthesia (IRR, 12.1 [4.39-33.5]; P < .001) were the only risk factors associated with longer HLOS. No associations were observed between risk factors and adverse events in multivariable analysis. Tumors treated per session were associated with risk of hospital readmission (P = .03). CONCLUSIONS: Identified preprocedural risk factors from the surgical literature may aid in risk stratification for HLOS after percutaneous ablation of lung tumors, but were not associated with adverse events.

Designing a quality assurance process for quality control of nuclear magnetic resonance metabolomics studies of human blood.

High-resolution magic angle spinning (HRMAS) nuclear magnetic resonance (NMR)-based metabolomics has demonstrated its utility in studies of biofluids for various diseases. HRMAS NMR spectroscopy is uniquely well suited for analyzing human blood samples because of the small quantity of samples and minimal preparation required. To develop this methodology into standardized clinical protocols, establishment of the method's quality assurance (QA) and evaluations of its quality control (QC) are critical. This study aims to assess the QA/QC measured from human blood specimens in the form of serum and plasma through within-subject and between-subject comparisons, as well as stability and consistency comparisons over several freezing-thawing cycles of sample storage conditions, and most importantly, the agreement of pooled control samples against individual samples.

Intubation and mortality prediction in hospitalized COVID-19 patients using a combination of convolutional neural network-based scoring of chest radiographs and clinical data.

Objective: To predict short-term outcomes in hospitalized COVID-19 patients using a model incorporating clinical variables with automated convolutional neural network (CNN) chest radiograph analysis. Methods: A retrospective single center study was performed on patients consecutively admitted with COVID-19 between March 14 and April 21 2020. Demographic, clinical and laboratory data were collected, and automated CNN scoring of the admission chest radiograph was performed. The two outcomes of disease progression were intubation or death within 7 days and death within 14 days following admission. Multiple imputation was performed for missing predictor variables and, for each imputed data set, a penalized logistic regression model was constructed to identify predictors and their functional relationship to each outcome. Cross-validated area under the characteristic (AUC) curves were estimated to quantify the discriminative ability of each model. Results: 801 patients (median age 59; interquartile range 46-73 years, 469 men) were evaluated. 36 patients were deceased and 207 were intubated at 7 days and 65 were deceased at 14 days. Cross-validated AUC values for predictive models were 0.82 (95% CI, 0.79-0.86) for death or intubation within 7 days and 0.82 (0.78-0.87) for death within 14 days. Automated CNN chest radiograph score was an important variable in predicting both outcomes. Conclusion: Automated CNN chest radiograph analysis, in combination with clinical variables, predicts short-term intubation and death in patients hospitalized for COVID-19 infection. Chest radiograph scoring of more severe disease was associated with a greater probability of adverse short-term outcome. Advances in knowledge: Model-based predictions of intubation and death in COVID-19 can be performed with high discriminative performance using admission clinical data and convolutional neural network-based scoring of chest radiograph severity.

Brief Report: A Blood-Based MicroRNA Complementary Diagnostic Predicts Immunotherapy Efficacy in Advanced-Sta ge NSCLC With High Programmed Death-Ligand 1 Express ion.

Introduction: Patients with advanced, non-oncogene-driven NSCLC with high programmed death-ligand 1 (PD-L1) expression are eligible for treatment with immunotherapy. There is, however, an urgent medical need for biomarkers identifying cases that require additional combination with chemotherapy. We previously uncovered a myeloid-based 5-microRNA (5-miRNA) signature that identified responders to immunotherapy in PD-L1 unstratified patients; however, its potential utility in treatment guidance for patients with PD-L1 high tumors remained unclear. Methods: We trained (n = 68) and validated (n = 56) a 5-miRNA multivariable Cox proportional hazards model predictive of overall survival on small RNA sequencing data of whole blood samples prospectively collected before the commencement of immunotherapy for stage IV NSCLC with PD-L1 tumor proportion score greater than or equal to 50%, treated with PD-1 inhibitor monotherapy (immunotherapy alone [IO]). Specificity was demonstrated in a control cohort treated with immunochemotherapy (ICT) (n = 31). Results: The revised 5-miRNA risk score (miRisk) stratified IO-treated patients and identified a high-risk group with significantly shorter overall survival (hazard ratio = 5.24, 95% confidence interval: 2.17-12.66, p < 0.001). There was a significant interaction between the miRisk score and type of treatment (IO or ICT, p = 0.036), indicating that the miRisk score may serve as a predictive biomarker for immunotherapy response. Furthermore, the miRisk score could identify a group of high-risk patients who may benefit from treatment with ICT as opposed to IO (hazard ratio = 0.35, 95% confidence interval: 0.15-0.82, p = 0.018). Conclusions: The miRisk score can distinguish a group of patients with PD-L1 high, stage IV NSCLC likely to benefit from adding chemotherapy to immunotherapy and may support treatment decisions as a blood-based complementary diagnostic.

Comparison of expected imaging findings following percutaneous microwave and cryoablation of pulmonary tumors: ablation zones and thoracic lymph nodes.

OBJECTIVE: To compare temporal changes of ablation zones and lymph nodes following lung microwave ablation (MWA) and cryoablation. METHODS: This retrospective cohort study compared lung ablation zones and thoracic lymph nodes following MWA and cryoablation performed 2006-2020. In the ablation zone cohort, ablation zone volumes were measured on serial CT for 12 months. In the lymph node cohort, the sum of bidimensional products of lymph node diameters was measured before (baseline) and up to 6 months following ablation. Cumulative incidence curves estimated the time to 75% ablation zone reduction and linear mixed-effects regression models compared the temporal distribution of ablation zones and lymph node sizes between modalities. RESULTS: Ablation zones of 59 tumors treated in 45 sessions (16 MWA, 29 cryoablation) in 36 patients were evaluated. Differences in the time to 75% volume reduction between modalities were not detected. Following MWA, half of the ablation zones required an estimated time of 340 days to achieve a 75% volume reduction compared to 214 days following cryoablation (p = .30). Thoracic lymph node sizes after 33 sessions (13 MWA, 20 cryoablation) differed between modalities (baseline-32 days, p = .01; 32-123 days, p = .001). Following MWA, lymph nodes increased on average by 38 mm2 (95%CI, 5.0-70.7; p = .02) from baseline to 32 days, followed by an estimated decrease of 50 mm2 (32-123 days; p = .001). Following cryoablation, changes in lymph nodes were not detected (baseline-32 days, p = .33). CONCLUSION: The rate of ablation zone volume reduction did not differ between MWA and cryoablation. Thoracic lymph nodes enlarged transiently after MWA but not after cryoablation. KEY POINTS: • Contrary to current belief, the rate of lung ablation zone volume reduction did not differ between microwave and cryoablation. • Transient enlargement of thoracic lymph nodes after microwave ablation was not associated with regional tumor spread and decreased within six months following ablation. • No significant thoracic lymph node enlargement was observed following cryoablation.

Utility of Noncancerous Chest CT Features for Predicting Overall Survival and Noncancer Death in Patients With Stage I Lung Cancer Treated With Stereotactic Body Radiotherapy.

BACKGROUND. Noncancerous imaging markers can be readily derived from pre-treatment diagnostic and radiotherapy planning chest CT examinations. OBJECTIVE. The purpose of this article was to explore the ability of noncancerous features on chest CT to predict overall survival (OS) and noncancer-related death in patients with stage I lung cancer treated with stereotactic body radiation therapy (SBRT). METHODS. This retrospective study included 282 patients (168 female, 114 male; median age, 75 years) with stage I lung cancer treated with SBRT between January 2009 and June 2017. Pretreatment chest CT was used to quantify coronary artery calcium (CAC) score, pulmonary artery (PA)-to-aorta ratio, emphysema, and body composition in terms of the cross-sectional area and attenuation of skeletal muscle and subcutaneous adipose tissue at the T5, T8, and T10 vertebral levels. Associations of clinical and imaging features with OS were quantified using a multivariable Cox proportional hazards (PH) model. Penalized multivariable Cox PH models to predict OS were constructed using clinical features only and using both clinical and imaging features. The models' discriminatory ability was assessed by constructing time-varying ROC curves and computing AUC at prespecified times. RESULTS. After a median OS of 60.8 months (95% CI, 55.8-68.0), 148 (52.5%) patients had died, including 83 (56.1%) with noncancer deaths. Higher CAC score (11-399: hazard ratio [HR], 1.83 [95% CI, 1.15-2.91], p = .01; ≥ 400: HR, 1.63 [95% CI, 1.01-2.63], p = .04), higher PA-to-aorta ratio (HR, 1.33 [95% CI, 1.16-1.52], p < .001, per 0.1-unit increase), and lower thoracic skeletal muscle index (HR, 0.88 [95% CI, 0.79-0.98], p = .02, per 10-cm2/m2 increase) were independently associated with shorter OS. Discriminatory ability for 5-year OS was greater for the model including clinical and imaging features than for the model including clinical features only (AUC, 0.75 [95% CI, 0.68-0.83] vs 0.61 [95% CI, 0.53-0.70]; p < .01). The model's most important clinical or imaging feature according to mean standardized regression coefficients was the PA-to-aorta ratio. CONCLUSION. In patients undergoing SBRT for stage I lung cancer, higher CAC score, higher PA-to-aorta ratio, and lower thoracic skeletal muscle index independently predicted worse OS. CLINICAL IMPACT. Noncancerous imaging features on chest CT performed before SBRT improve survival prediction compared with clinical features alone.