Radiomics and artificial intelligence for precision medicine in lung cancer treatment.

Lung cancer is the leading cause of cancer-related deaths worldwide. It exhibits, at the mesoscopic scale, phenotypic characteristics that are generally indiscernible to the human eye but can be captured non-invasively on medical imaging as radiomic features, which can form a high dimensional data space amenable to machine learning. Radiomic features can be harnessed and used in an artificial intelligence paradigm to risk stratify patients, and predict for histological and molecular findings, and clinical outcome measures, thereby facilitating precision medicine for improving patient care. Compared to tissue sampling-driven approaches, radiomics-based methods are superior for being non-invasive, reproducible, cheaper, and less susceptible to intra-tumoral heterogeneity. This review focuses on the application of radiomics, combined with artificial intelligence, for delivering precision medicine in lung cancer treatment, with discussion centered on pioneering and groundbreaking works, and future research directions in the area.

Lung Abnormalities Detected with Hyperpolarized 129Xe MRI in Patients with Long COVID.

Background Post-COVID-19 condition encompasses symptoms following COVID-19 infection that linger at least 4 weeks after the end of active infection. Symptoms are wide ranging, but breathlessness is common. Purpose To determine if the previously described lung abnormalities seen on hyperpolarized (HP) pulmonary xenon 129 (129Xe) MRI scans in participants with post-COVID-19 condition who were hospitalized are also present in participants with post-COVID-19 condition who were not hospitalized. Materials and Methods In this prospective study, nonhospitalized participants with post-COVID-19 condition (NHLC) and posthospitalized participants with post-COVID-19 condition (PHC) were enrolled from June 2020 to August 2021. Participants underwent chest CT, HP 129Xe MRI, pulmonary function testing, and the 1-minute sit-to-stand test and completed breathlessness questionnaires. Control subjects underwent HP 129Xe MRI only. CT scans were analyzed for post-COVID-19 interstitial lung disease severity using a previously published scoring system and full-scale airway network (FAN) modeling. Analysis used group and pairwise comparisons between participants and control subjects and correlations between participant clinical and imaging data. Results A total of 11 NHLC participants (four men, seven women; mean age, 44 years ± 11 [SD]; 95% CI: 37, 50) and 12 PHC participants (10 men, two women; mean age, 58 years ±10; 95% CI: 52, 64) were included, with a significant difference in age between groups (P = .05). Mean time from infection was 287 days ± 79 (95% CI: 240, 334) and 143 days ± 72 (95% CI: 105, 190) in NHLC and PHC participants, respectively. NHLC and PHC participants had normal or near normal CT scans (mean, 0.3/25 ± 0.6 [95% CI: 0, 0.63] and 7/25 ± 5 [95% CI: 4, 10], respectively). Gas transfer (Dlco) was different between NHLC and PHC participants (mean Dlco, 76% ± 8 [95% CI: 73, 83] vs 86% ± 8 [95% CI: 80, 91], respectively; P = .04), but there was no evidence of other differences in lung function. Mean red blood cell-to-tissue plasma ratio was different between volunteers (mean, 0.45 ± 0.07; 95% CI: 0.43, 0.47]) and PHC participants (mean, 0.31 ± 0.10; 95% CI: 0.24, 0.37; P = .02) and between volunteers and NHLC participants (mean, 0.37 ± 0.10; 95% CI: 0.31, 0.44; P = .03) but not between NHLC and PHC participants (P = .26). FAN results did not correlate with Dlco) or HP 129Xe MRI results. Conclusion Nonhospitalized participants with post-COVID-19 condition (NHLC) and posthospitalized participants with post-COVID-19 condition (PHC) showed hyperpolarized pulmonary xenon 129 MRI and red blood cell-to-tissue plasma abnormalities, with NHLC participants demonstrating lower gas transfer than PHC participants despite having normal CT findings. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Parraga and Matheson in this issue.

Hyperpolarized 129Xe MRI Abnormalities in Dyspneic Patients 3 Months after COVID-19 Pneumonia: Preliminary Results.

Background SARS-CoV-2 targets angiotensin-converting enzyme 2-expressing cells in the respiratory tract. There are reports of breathlessness in patients many months after infection. Purpose To determine whether hyperpolarized xenon 129 MRI (XeMRI) imaging could be used to identify the possible cause of breathlessness in patients at 3 months after hospital discharge following COVID-19 infection. Materials and Methods This prospective study was undertaken between August and December of 2020, with patients and healthy control volunteers being enrolled. All patients underwent lung function tests; ventilation and dissolved-phase XeMRI, with the mean red blood cell (RBC) to tissue or plasma (TP) ratio being calculated; and a low-dose chest CT, with scans being scored for the degree of abnormalities after COVID-19. Healthy control volunteers underwent XeMRI. The intraclass correlation coefficient was calculated for volunteer and patient scans to assess repeatability. A Wilcoxon rank sum test and Cohen effect size calculation were performed to assess differences in the RBC/TP ratio between patients and control volunteers. Results Nine patients (mean age, 57 years ± 7 [standard deviation]; six male patients) and five volunteers (mean age, 29 years ± 3; five female volunteers) were enrolled. The mean time from hospital discharge for patients was 169 days (range, 116-254 days). There was a difference in the RBC/TP ratio between patients and control volunteers (0.3 ± 0.1 vs 0.5 ± 0.1, respectively; P = .001; effect size, 1.36). There was significant difference between the RBC and gas phase spectral full width at half maximum between volunteers and patients (median ± range, 567 ± 1 vs 507 ± 81 [P = .002] and 104 ± 2 vs 122 ± 17 [P = .004], respectively). Results were reproducible, with intraclass correlation coefficients of 0.82 and 0.88 being demonstrated for patients and volunteers, respectively. Participants had normal or nearly normal CT scans (mean, seven of 25; range, zero of 25 to 10 of 25). Conclusion Hyperpolarized xenon 129 MRI results showed alveolar capillary diffusion limitation in all nine patients after COVID-19 pneumonia, despite normal or nearly normal results at CT. © RSNA, 2021 See also the editorial by Dietrich in this issue.

Delayed ventilation assessment using fast dynamic hyperpolarised Xenon-129 magnetic resonance imaging.

OBJECTIVES: To investigate the use of a fast dynamic hyperpolarised 129Xe ventilation magnetic resonance imaging (DXeV-MRI) method for detecting and quantifying delayed ventilation in patients with chronic obstructive pulmonary disease (COPD). METHODS: Three male participants (age range 31-43) with healthy lungs and 15 patients (M/F = 12:3, age range = 48-73) with COPD (stages II-IV) underwent spirometry tests, quantitative chest computed tomography (QCT), and DXeV-MRI at 1.5-Tesla. Regional delayed ventilation was captured by measuring the temporal signal change in each lung region of interest (ROI) in comparison to that in the trachea. In addition to its qualitative assessment through visual inspection by a clinical radiologist, delayed ventilation was quantitatively captured by calculating a covariance measurement of the lung ROI and trachea signals, and quantified using both the time delay, and the difference between the integrated areas covered by the signal-time curves of the two signals. RESULTS: Regional temporal ventilation, consistent with the expected physiological changes across a free breathing cycle, was demonstrated with DXeV-MRI in all patients. Delayed ventilation was observed in 13 of the 15 COPD patients and involved variable lung ROIs. This was in contrast to the control group, where no delayed ventilation was demonstrated (p = 0.0173). CONCLUSIONS: DXeV-MRI offers a non-invasive way of detecting and quantifying delayed ventilation in patients with COPD, and provides physiological information on regional pulmonary function during a full breathing cycle. KEY POINTS: • Dynamic xenon MRI allows for the non-invasive detection and measurement of delayed ventilation in COPD patients. • Dynamic xenon MRI during a free breathing cycle can provide unique information about pulmonary physiology and pulmonary disease pathophysiology. • With further validation, dynamic xenon MRI could offer a non-invasive way of measuring collateral ventilation which can then be used to guide lung volume reduction therapy (LVRT) for certain COPD patients.

Magnetic resonance imaging of the time course of hyperpolarized 129Xe gas exchange in the human lungs and heart.

PURPOSE: To perform magnetic resonance imaging (MRI), human lung imaging, and quantification of the gas-transfer dynamics of hyperpolarized xenon-129 (HPX) from the alveoli into the blood plasma. MATERIALS AND METHODS: HPX MRI with iterative decomposition of water and fat with echo asymmetry and least-square estimation (IDEAL) approach were used with multi-interleaved spiral k-space sampling to obtain HPX gas and dissolved phase images. IDEAL time-series images were then obtained from ten subjects including six normal subjects and four patients with pulmonary emphysema to test the feasibility of the proposed technique for capturing xenon-129 gas-transfer dynamics (XGTD). The dynamics of xenon gas diffusion over the entire lung was also investigated by measuring the signal intensity variations between three regions of interest, including the left and right lungs and the heart using Welch's t test. RESULTS: The technique enabled the acquisition of HPX gas and dissolved phase compartment images in a single breath-hold interval of 8 s. The y-intersect of the XGTD curves were also found to be statistically lower in the patients with lung emphysema than in the healthy group (p < 0.05). CONCLUSION: This time-series IDEAL technique enables the visualization and quantification of inhaled xenon from the alveoli to the left ventricle with a clinical gradient strength magnet during a single breath-hold, in healthy and diseased lungs. KEY POINTS: • The proposed hyperpolarized xenon-129 gas and dissolved magnetic resonance imaging technique can provide regional and temporal measurements of xenon-129 gas-transfer dynamics. • Quantitative measurement of xenon-129 gas-transfer dynamics from the alveolar to the heart was demonstrated in normal subjects and pulmonary emphysema. • Comparison of gas-transfer dynamics in normal subjects and pulmonary emphysema showed that the proposed technique appears sensitive to changes affecting the alveoli, pulmonary interstitium, and capillaries.

Time-series hyperpolarized xenon-129 MRI of lobar lung ventilation of COPD in comparison to V/Q-SPECT/CT and CT.

PURPOSE: To derive lobar ventilation in patients with chronic obstructive pulmonary disease (COPD) using a rapid time-series hyperpolarized xenon-129 (HPX) magnetic resonance imaging (MRI) technique and compare this to ventilation/perfusion single-photon emission computed tomography (V/Q-SPECT), correlating the results with high-resolution computed tomography (CT) and pulmonary function tests (PFTs). MATERIALS AND METHODS: Twelve COPD subjects (GOLD stages I-IV) participated in this study and underwent HPX-MRI, V/Q-SPECT/CT, high-resolution CT, and PFTs. HPX-MRI was performed using a novel time-series spiral k-space sampling approach. Relative percentage ventilations were calculated for individual lobe for comparison to the relative SPECT lobar ventilation and perfusion. The absolute HPX-MRI percentage ventilation in each lobe was compared to the absolute CT percentage emphysema score calculated using a signal threshold method. Pearson's correlation and linear regression tests were performed to compare each imaging modality. RESULTS: Strong correlations were found between the relative lobar percentage ventilation with HPX-MRI and percentage ventilation SPECT (r = 0.644; p < 0.001) and percentage perfusion SPECT (r = 0.767; p < 0.001). The absolute CT percentage emphysema and HPX percentage ventilation correlation was also statistically significant (r = 0.695, p < 0.001). The whole lung HPX percentage ventilation correlated with the PFT measurements (FEV1 with r = - 0.886, p < 0.001*, and FEV1/FVC with r = - 0.861, p < 0.001*) better than the whole lung CT percentage emphysema score (FEV1 with r = - 0.635, p = 0.027; and FEV1/FVC with r = - 0.652, p = 0.021). CONCLUSION: Lobar ventilation with HPX-MRI showed a strong correlation with lobar ventilation and perfusion measurements derived from SPECT/CT, and is better than the emphysema score obtained with high-resolution CT. KEY POINTS: • The ventilation hyperpolarized xenon-129 MRI correlates well with ventilation and perfusion with SPECT/CT with the advantage of higher temporal and spatial resolution. • The hyperpolarized xenon-129 MRI correlates with the PFT measurements better than the high-resolution CT with the advantage of avoiding the use of ionizing radiation.

Chronic Obstructive Pulmonary Disease: Lobar Analysis with Hyperpolarized 129Xe MR Imaging.

Purpose To compare lobar ventilation and apparent diffusion coefficient (ADC) values obtained with hyperpolarized xenon 129 (129Xe) magnetic resonance (MR) imaging to quantitative computed tomography (CT) metrics on a lobar basis and pulmonary function test (PFT) results on a whole-lung basis in patients with chronic obstructive pulmonary disease (COPD). Materials and Methods The study was approved by the National Research Ethics Service Committee; written informed consent was obtained from all patients. Twenty-two patients with COPD (Global Initiative for Chronic Obstructive Lung Disease stage II-IV) underwent hyperpolarized 129Xe MR imaging at 1.5 T, quantitative CT, and PFTs. Whole-lung and lobar 129Xe MR imaging parameters were obtained by using automated segmentation of multisection hyperpolarized 129Xe MR ventilation images and hyperpolarized 129Xe MR diffusion-weighted images after coregistration to CT scans. Whole-lung and lobar quantitative CT-derived metrics for emphysema and bronchial wall thickness were calculated. Pearson correlation coefficients were used to evaluate the relationship between imaging measures and PFT results. Results Percentage ventilated volume and average ADC at lobar 129Xe MR imaging showed correlation with percentage emphysema at lobar quantitative CT (r = -0.32, P < .001 and r = 0.75, P < .0001, respectively). The average ADC at whole-lung 129Xe MR imaging showed moderate correlation with PFT results (percentage predicted transfer factor of the lung for carbon monoxide [Tlco]: r = -0.61, P < .005) and percentage predicted functional residual capacity (r = 0.47, P < .05). Whole-lung quantitative CT percentage emphysema also showed statistically significant correlation with percentage predicted Tlco (r = -0.65, P < .005). Conclusion Lobar ventilation and ADC values obtained from hyperpolarized 129Xe MR imaging demonstrated correlation with quantitative CT percentage emphysema on a lobar basis and with PFT results on a whole-lung basis. © RSNA, 2016.

The Broad Neutralizing Antibody Responses after HIV-1 Superinfection Are Not Dominated by Antibodies Directed to Epitopes Common in Single Infection.

HIV-1 vaccines designed to date have failed to elicit neutralizing antibodies (Nabs) that are capable of protecting against globally diverse HIV-1 subtypes. One relevant setting to study the development of a strong, cross-reactive Nab response is HIV-1 superinfection (SI), defined as sequential infections from different source partners. SI has previously been shown to lead to a broader and more potent Nab response when compared to single infection, but it is unclear whether SI also impacts epitope specificity and if the epitopes targeted after SI differ from those targeted after single infection. Here the post-SI Nab responses were examined from 21 Kenyan women collectively exposed to subtypes A, C, and D and superinfected after a median time of ~1.07 years following initial infection. Plasma samples chosen for analysis were collected at a median time point ~2.72 years post-SI. Because previous studies of singly infected populations with broad and potent Nab responses have shown that the majority of their neutralizing activity can be mapped to 4 main epitopes on the HIV-1 Envelope, we focused on these targets, which include the CD4-binding site, a V1/V2 glycan, the N332 supersite in V3, and the membrane proximal external region of gp41. Using standard epitope mapping techniques that were applied to the previous cohorts, the present study demonstrates that SI did not induce a dominant Nab response to any one of these epitopes in the 21 women. Computational sera delineation analyses also suggested that 20 of the 21 superinfected women's Nab responses could not be ascribed a single specificity with high confidence. These data are consistent with a model in which SI with diverse subtypes promotes the development of a broad polyclonal Nab response, and thus would provide support for vaccine designs using multivalent HIV immunogens to elicit a diverse repertoire of Nabs.

Deep representation learning of tissue metabolome and computed tomography annotates NSCLC classification and prognosis.

The rich chemical information from tissue metabolomics provides a powerful means to elaborate tissue physiology or tumor characteristics at cellular and tumor microenvironment levels. However, the process of obtaining such information requires invasive biopsies, is costly, and can delay clinical patient management. Conversely, computed tomography (CT) is a clinical standard of care but does not intuitively harbor histological or prognostic information. Furthermore, the ability to embed metabolome information into CT to subsequently use the learned representation for classification or prognosis has yet to be described. This study develops a deep learning-based framework -- tissue-metabolomic-radiomic-CT (TMR-CT) by combining 48 paired CT images and tumor/normal tissue metabolite intensities to generate ten image embeddings to infer metabolite-derived representation from CT alone. In clinical NSCLC settings, we ascertain whether TMR-CT results in an enhanced feature generation model solving histology classification/prognosis tasks in an unseen international CT dataset of 742 patients. TMR-CT non-invasively determines histological classes - adenocarcinoma/squamous cell carcinoma with an F1-score = 0.78 and further asserts patients' prognosis with a c-index = 0.72, surpassing the performance of radiomics models and deep learning on single modality CT feature extraction. Additionally, our work shows the potential to generate informative biology-inspired CT-led features to explore connections between hard-to-obtain tissue metabolic profiles and routine lesion-derived image data.

Validated machine learning tools to distinguish immune checkpoint inhibitor, radiotherapy, COVID-19 and other infective pneumonitis.

BACKGROUND: Pneumonitis is a well-described, potentially disabling, or fatal adverse effect associated with both immune checkpoint inhibitors (ICI) and thoracic radiotherapy. Accurate differentiation between checkpoint inhibitor pneumonitis (CIP) radiation pneumonitis (RP), and infective pneumonitis (IP) is crucial for swift, appropriate, and tailored management to achieve optimal patient outcomes. However, correct diagnosis is often challenging, owing to overlapping clinical presentations and radiological patterns. METHODS: In this multi-centre study of 455 patients, we used machine learning with radiomic features extracted from chest CT imaging to develop and validate five models to distinguish CIP and RP from COVID-19, non-COVID-19 infective pneumonitis, and each other. Model performance was compared to that of two radiologists. RESULTS: Models to distinguish RP from COVID-19, CIP from COVID-19 and CIP from non-COVID-19 IP out-performed radiologists (test set AUCs of 0.92 vs 0.8 and 0.8; 0.68 vs 0.43 and 0.4; 0.71 vs 0.55 and 0.63 respectively). Models to distinguish RP from non-COVID-19 IP and CIP from RP were not superior to radiologists but demonstrated modest performance, with test set AUCs of 0.81 and 0.8 respectively. The CIP vs RP model performed less well on patients with prior exposure to both ICI and radiotherapy (AUC 0.54), though the radiologists also had difficulty distinguishing this test cohort (AUC values 0.6 and 0.6). CONCLUSION: Our results demonstrate the potential utility of such tools as a second or concurrent reader to support oncologists, radiologists, and chest physicians in cases of diagnostic uncertainty. Further research is required for patients with exposure to both ICI and thoracic radiotherapy.

A Novel Radiogenomics Biomarker for Predicting Treatment Response and Pneumotoxicity From Programmed Cell Death Protein or Ligand-1 Inhibition Immunotherapy in NSCLC.

INTRODUCTION: Patient selection for checkpoint inhibitor immunotherapy is currently guided by programmed death-ligand 1 (PD-L1) expression obtained from immunohistochemical staining of tumor tissue samples. This approach is susceptible to limitations resulting from the dynamic and heterogeneous nature of cancer cells and the invasiveness of the tissue sampling procedure. To address these challenges, we developed a novel computed tomography (CT) radiomic-based signature for predicting disease response in patients with NSCLC undergoing programmed cell death protein 1 (PD-1) or PD-L1 checkpoint inhibitor immunotherapy. METHODS: This retrospective study comprises a total of 194 patients with suitable CT scans out of 340. Using the radiomic features computed from segmented tumors on a discovery set of 85 contrast-enhanced chest CTs of patients diagnosed with having NSCLC and their CD274 count, RNA expression of the protein-encoding gene for PD-L1, as the response vector, we developed a composite radiomic signature, lung cancer immunotherapy-radiomics prediction vector (LCI-RPV). This was validated in two independent testing cohorts of 66 and 43 patients with NSCLC treated with PD-1 or PD-L1 inhibition immunotherapy, respectively. RESULTS: LCI-RPV predicted PD-L1 positivity in both NSCLC testing cohorts (area under the curve [AUC] = 0.70, 95% confidence interval [CI]: 0.57-0.84 and AUC = 0.70, 95% CI: 0.46-0.94). In one cohort, it also demonstrated good prediction of cases with high PD-L1 expression exceeding key treatment thresholds (>50%: AUC = 0.72, 95% CI: 0.59-0.85 and >90%: AUC = 0.66, 95% CI: 0.45-0.88), the tumor's objective response to treatment at 3 months (AUC = 0.68, 95% CI: 0.52-0.85), and pneumonitis occurrence (AUC = 0.64, 95% CI: 0.48-0.80). LCI-RPV achieved statistically significant stratification of the patients into a high- and low-risk survival group (hazard ratio = 2.26, 95% CI: 1.21-4.24, p = 0.011 and hazard ratio = 2.45, 95% CI: 1.07-5.65, p = 0.035). CONCLUSIONS: A CT radiomics-based signature developed from response vector CD274 can aid in evaluating patients' suitability for PD-1 or PD-L1 checkpoint inhibitor immunotherapy in NSCLC.

Tumor and local lymphoid tissue interaction determines prognosis in high-grade serous ovarian cancer.

Tertiary lymphoid structure (TLS) is associated with prognosis in copy-number-driven tumors, including high-grade serous ovarian cancer (HGSOC), although the function of TLS and its interaction with copy-number alterations in HGSOC are not fully understood. In the current study, we confirm that TLS-high HGSOC patients show significantly better progression-free survival (PFS). We show that the presence of TLS in HGSOC tumors is associated with B cell maturation and cytotoxic tumor-specific T cell activation and proliferation. In addition, the copy-number loss of IL15 and CXCL10 may limit TLS formation in HGSOC; a list of genes that may dysregulate TLS function is also proposed. Last, a radiomics-based signature is developed to predict the presence of TLS, which independently predicts PFS in both HGSOC patients and immune checkpoint inhibitor (ICI)-treated non-small cell lung cancer (NSCLC) patients. Overall, we reveal that TLS coordinates intratumoral B cell and T cell response to HGSOC tumor, while the cancer genome evolves to counteract TLS formation and function.

A radiomics-based decision support tool improves lung cancer diagnosis in combination with the Herder score in large lung nodules.

BACKGROUND: Large lung nodules (≥15 mm) have the highest risk of malignancy, and may exhibit important differences in phenotypic or clinical characteristics to their smaller counterparts. Existing risk models do not stratify large nodules well. We aimed to develop and validate an integrated segmentation and classification pipeline, incorporating deep-learning and traditional radiomics, to classify large lung nodules according to cancer risk. METHODS: 502 patients from five U.K. centres were recruited to the large-nodule arm of the retrospective LIBRA study between July 2020 and April 2022. 838 CT scans were used for model development, split into training and test sets (70% and 30% respectively). An nnUNet model was trained to automate lung nodule segmentation. A radiomics signature was developed to classify nodules according to malignancy risk. Performance of the radiomics model, termed the large-nodule radiomics predictive vector (LN-RPV), was compared to three radiologists and the Brock and Herder scores. FINDINGS: 499 patients had technically evaluable scans (mean age 69 ± 11, 257 men, 242 women). In the test set of 252 scans, the nnUNet achieved a DICE score of 0.86, and the LN-RPV achieved an AUC of 0.83 (95% CI 0.77-0.88) for malignancy classification. Performance was higher than the median radiologist (AUC 0.75 [95% CI 0.70-0.81], DeLong p = 0.03). LN-RPV was robust to auto-segmentation (ICC 0.94). For baseline solid nodules in the test set (117 patients), LN-RPV had an AUC of 0.87 (95% CI 0.80-0.93) compared to 0.67 (95% CI 0.55-0.76, DeLong p = 0.002) for the Brock score and 0.83 (95% CI 0.75-0.90, DeLong p = 0.4) for the Herder score. In the international external test set (n = 151), LN-RPV maintained an AUC of 0.75 (95% CI 0.63-0.85). 18 out of 22 (82%) malignant nodules in the Herder 10-70% category in the test set were identified as high risk by the decision-support tool, and may have been referred for earlier intervention. INTERPRETATION: The model accurately segments and classifies large lung nodules, and may improve upon existing clinical models. FUNDING: This project represents independent research funded by: 1) Royal Marsden Partners Cancer Alliance, 2) the Royal Marsden Cancer Charity, 3) the National Institute for Health Research (NIHR) Biomedical Research Centre at the Royal Marsden NHS Foundation Trust and The Institute of Cancer Research, London, 4) the National Institute for Health Research (NIHR) Biomedical Research Centre at Imperial College London, 5) Cancer Research UK (C309/A31316).

Imaging Dynamic Expiration: Feasibility of MRI Spirometry Using Hyperpolarized Xenon Gas.

PURPOSE: To examine the feasibility of imaging-based spirometry using high-temporal-resolution projection MRI and hyperpolarized xenon 129 (129Xe) gas. MATERIALS AND METHODS: In this prospective exploratory study, five healthy participants (age range, 25-45 years; three men) underwent an MRI spirometry technique using inhaled hyperpolarized 129Xe and rapid two-dimensional projection MRI. Participants inhaled 129Xe, then performed a forced expiratory maneuver while in an MR imager. Images of the lungs during expiration were captured in time intervals as short as 250 msec. Volume-corrected images of the lungs at expiration commencement (0 second), 1 second after expiration, and 6 seconds after expiration were extracted to generate forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), and FEV1/FVC ratio pulmonary maps. For comparison, participants performed conventional spirometry in the sitting position using room air, in the supine position using room air, and in the supine position using a room air and 129Xe mixture. Paired t tests with Bonferroni corrections for multiple comparisons were used for statistical analyses. RESULTS: The mean MRI-derived FEV1/FVC value was lower in comparison with conventional spirometry (0.52 ± 0.03 vs 0.70 ± 0.05, P < .01), which may reflect selective 129Xe retention. A secondary finding of this study was that 1 L of inhaled 129Xe negatively impacted pulmonary function as measured by conventional spirometry (in supine position), which reduced measured FEV1 (2.70 ± 0.90 vs 3.04 ± 0.85, P < .01) and FEV1/FVC (0.70 ± 0.05 vs 0.79 ± 0.04, P < .01). CONCLUSION: A forced expiratory maneuver was successfully imaged with hyperpolarized 129Xe and high-temporal-resolution MRI. Derivation of regional lung spirometric maps was feasible.Keywords: MR-Imaging, MR-Dynamic Contrast Enhanced, MR-Functional Imaging, Pulmonary, Thorax, Diaphragm, Lung, Pleura, Physics Supplemental material is available for this article. © RSNA, 2021.

Computed tomography pulmonary angiography using a 20% reduction in contrast medium dose delivered in a multiphasic injection.

AIM: To evaluate the feasibility of reducing the dose of iodinated contrast agent in computed tomography pulmonary angiography (CTPA). METHODS: One hundred and twenty-seven patients clinically suspected of having pulmonary embolism underwent spiral CTPA, out of whom fifty-seven received 75 mL and the remaining seventy a lower dose of 60 mL of contrast agent. Both doses were administered in a multiphasic injection. A minimum opacification threshold of 250 Hounsfield units (HU) in the main pulmonary artery is used for assessing the technical adequacy of the scans. RESULTS: Mean opacification was found to be positively correlated to patient age (Pearson's correlation 0.4255, P < 0.0001) and independent of gender (male:female, 425.6 vs 450.4, P = 0.34). When age is accounted for, the study and control groups did not differ significantly in their mean opacification in the main (436.8 vs 437.9, P = 0.48), left (416.6 vs 419.8, P = 0.45) or the right pulmonary arteries (417.3 vs 423.5, P = 0.40). The number of sub-optimally opacified scans (the mean opacification in the main pulmonary artery < 250 HU) did not differ significantly between the study and control groups (7 vs 10). CONCLUSION: A lower dose of iodine contrast at 60 mL can be feasibly used in CTPA without resulting in a higher number of sub-optimally opacified scans.

Computer-aided volumetric assessment of malignant pleural mesothelioma on CT using a random walk-based method.

OBJECTIVE: The aim of this study is to assess the performance of a computer-aided semi-automated algorithm we have adapted for the purpose of segmenting malignant pleural mesothelioma (MPM) on CT. METHODS: Forty-five CT scans were collected from 15 patients (M:F [Formula: see text] 10:5, mean age 62.8 years) in a multi-centre clinical drug trial. A computer-aided random walk-based algorithm was applied to segment the tumour; the results were then compared to radiologist-drawn contours and correlated with measurements made using the MPM-adapted Response Evaluation Criteria in Solid Tumour (modified RECIST). RESULTS: A mean accuracy (Sørensen-Dice index) of 0.825 (95% CI [0.758, 0.892]) was achieved. Compared to a median measurement time of 68.1 min (range [40.2, 102.4]) for manual delineation, the median running time of our algorithm was 23.1 min (range [10.9, 37.0]). A linear correlation (Pearson's correlation coefficient: 0.6392, [Formula: see text]) was established between the changes in modified RECIST and computed tumour volume. CONCLUSION: Volumetric tumour segmentation offers a potential solution to the challenges in quantifying MPM. Computer-assisted methods such as the one presented in this study facilitate this in an accurate and time-efficient manner and provide additional morphological information about the tumour's evolution over time.

Correlation between fine motor activity and striatal dopamine D2 receptor density in patients with schizophrenia and healthy controls.

Striatal dopamine D2 receptor density is an important indicator of many neuropsychiatric disorders and also of motor activity. This study examined the relationship between a fine motor task (finger tapping test, FTT) and striatal D2 dopamine receptor density by examining 20 healthy volunteers and 20 schizophrenic patients. Striatal D2 receptor density was determined with single photon emission computed tomography using [123I]IBZM (iodo-benzamide). The correlation between the FTT score and striatal D2 receptor density was statistically significant not only in the patient group but also in healthy controls. The FTT scores and striatal D2 receptor density were lower in medicated patients than that in healthy controls. Compared with the Simpson-Angus Scale scores, the FTT scores were more strongly associated with striatal D2 receptor density. The use of neuroleptic medication seemed to influence the associations between FTT scores and striatal D2 receptor density in the patient group. The FTT scores and striatal D2 receptor density were age-sensitive in healthy controls. FTT may be a more sensitive tool for detecting neuroleptic-induced motor impairment in patients with schizophrenia. The sensitivity of the FTT to age and neuroleptic effects may be explained in part by a decline in dopamine D2 density.

Patient- and family-rated scale for bipolar disorder symptoms: Internal State Scale.

The monitoring of patients, by themselves and their caregivers, is very important in the prophylaxis of bipolar disorder. This study aimed to develop a Chinese-language version of an instrument for assessment of manic and depressive symptoms by patients and their families. Fifty-eight inpatients and outpatients with a DSM-IV (Diagnostic and Statistical Manual of Mental Disorders) diagnosis of bipolar disorder were recruited. All subjects underwent clinical psychopathologic assessment by experienced psychiatrists using the Young Mania Rating Scale (YMRS) and the Hamilton Depression Rating Scale (HDRS). At the same time, each patient and key family members filled out the Chinese-language version of the Internal State Scale (ISS) for monitoring mental symptoms. Patients were examined a second time if they had entered remission or a new episode of the opposite polarity. The ISS was divided into two subscales, of well-being/activation and of irritability. Patients' well-being/activation and irritability subscales were significantly correlated with YMRS scores and the well-being/activation subscale was also significantly correlated with the HDRS score. Family members' irritability subscales were significantly correlated with HDRS scores only. The reliability and constructive validity of the ISS was good in both patients with bipolar disorder and their families.