Efficacy of compressed sensing and deep learning reconstruction for adult female pelvic MRI at 1.5 T.

BACKGROUND: We aimed to determine the capabilities of compressed sensing (CS) and deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) for improving image quality while reducing examination time on female pelvic 1.5-T magnetic resonance imaging (MRI). METHODS: Fifty-two consecutive female patients with various pelvic diseases underwent MRI with T1- and T2-weighted sequences using CS and PI. All CS data was reconstructed with and without DLR. Signal-to-noise ratio (SNR) of muscle and contrast-to-noise ratio (CNR) between fat tissue and iliac muscle on T1-weighted images (T1WI) and between myometrium and straight muscle on T2-weighted images (T2WI) were determined through region-of-interest measurements. Overall image quality (OIQ) and diagnostic confidence level (DCL) were evaluated on 5-point scales. SNRs and CNRs were compared using Tukey's test, and qualitative indexes using the Wilcoxon signed-rank test. RESULTS: SNRs of T1WI and T2WI obtained using CS with DLR were higher than those using CS without DLR or conventional PI (p < 0.010). CNRs of T1WI and T2WI obtained using CS with DLR were higher than those using CS without DLR or conventional PI (p < 0.003). OIQ of T1WI and T2WI obtained using CS with DLR were higher than that using CS without DLR or conventional PI (p < 0.001). DCL of T2WI obtained using CS with DLR was higher than that using conventional PI or CS without DLR (p < 0.001). CONCLUSION: CS with DLR provided better image quality and shorter examination time than those obtainable with PI for female pelvic 1.5-T MRI. RELEVANCE STATEMENT: CS with DLR can be considered effective for attaining better image quality and shorter examination time for female pelvic MRI at 1.5 T compared with those obtainable with PI. KEY POINTS: Patients underwent MRI with T1- and T2-weighted sequences using CS and PI. All CS data was reconstructed with and without DLR. CS with DLR allowed for examination times significantly shorter than those of PI and provided significantly higher signal- and CNRs, as well as OIQ.

Usefulness of serum transthyretin for prediction of the 1-year outcome in idiopathic pulmonary fibrosis: An evaluation of sarcopenic and nutritional indicators.

BACKGROUND: Patients with idiopathic pulmonary fibrosis (IPF) often experience sarcopenia and malnutrition. However, this has not been fully examined through longitudinal surveys. This study investigated whether sarcopenia and malnutrition were associated with 1-year outcomes in IPF. METHODS: We evaluated sarcopenia and nutritional status in 64 outpatients with IPF. We assessed the time-to-event for respiratory-related hospitalizations or deaths 12 months after enrollment. Sarcopenia was diagnosed by the criteria of the Asian Working Group for Sarcopenia, 2019. Nutritional status was assessed by serum transthyretin and the Geriatric Nutritional Risk Index (GNRI). RESULTS: The average age was 73.6 ± 7.9 years, and the percent predicted forced vital capacity (FVC) was 81.9 ± 15.7%. Of the 64 patients, 24 (37.5%) had sarcopenia. The median serum transthyretin level and mean GNRI were 23.8 mg/dL and 102, respectively. Eleven patients (17.2%) experienced respiratory-related hospitalization or death within the first year. Cox regression analysis showed that the % predicted diffusion capacity for carbon monoxide, lowest oxygen saturation in the 6-min walk test, serum transthyretin level, and GNRI were significant predictors of 1-year outcomes. The Kaplan-Meier method, which divided the patients into two groups based on a transthyretin level of 22.6 mg/dL, showed a significant difference (P < 0.001, log-rank test). Sarcopenia and the percent predicted FVC did not predict the 1-year outcomes. CONCLUSIONS: This pilot study represents the first longitudinal survey assessing patients with IPF for sarcopenia and malnutrition. Serum transthyretin levels may predict respiratory-related hospitalization or death within 1 year in patients with IPF.

Efficacy of dupilumab for severe chronic rhinosinusitis with nasal polyps and asthma: A prospective study.

BACKGROUND: Dupilumab exerts clinical effects, including improved sinus opacification, olfactory function, and quality of life, in patients with severe chronic rhinosinusitis with nasal polyps (CRSwNPs). Meanwhile, only a few studies have reported its effects on nasal airway resistance and olfactory function, particularly in the Japanese population. Predictors of response remain unclear. OBJECTIVE: To assess the comprehensive efficacy and therapeutic response to dupilumab in patients with severe CRSwNP with comorbid asthma. METHODS: In 16 adult patients with severe CRSwNP with comorbid asthma, the efficacy of 48-week dupilumab treatment, including olfactory function measured by a T&T olfactometer, nasal airway resistance measured by rhinomanometry, nasal polyp score, Lund-Mackay computed tomography score, and 22-item Sinonasal Outcome Test (SNOT-22), was assessed. Regarding asthma, the annualized rate of exacerbations, 7-item Asthma Control Questionnaire (ACQ-7), and spirometry were assessed. Treatment responsiveness was analyzed. RESULTS: With 48-week dupilumab treatment, olfactory function, nasal airway resistance, nasal polyp score, Lund-Mackay computed tomography score, and SNOT-22 scores improved significantly. Regarding comorbid asthma, the annualized rate of exacerbations decreased, and ACQ-7 scores and lung function improved significantly. According to the European Position Paper on Rhinosinusitis and Nasal Polyps 2020/European Forum for Research and Education in Allergy and Airway Diseases criteria, 15 patients (94%) were moderate-to-excellent responders at 48 weeks of treatment. Patients with higher SNOT-22 scores, ACQ-7 scores, the rate of asthma exacerbations in the previous year, and blood eosinophil counts benefited more from the treatment. CONCLUSION: Dupilumab improved upper and lower airway outcomes especially in patients with severe CRSwNP with comorbid, poorly controlled asthma. TRIAL REGISTRATION: UMIN Clinical Trials Registry: UMIN000038669.

Deep Learning Reconstruction for DWIs by EPI and FASE Sequences for Head and Neck Tumors.

BACKGROUND: Diffusion-weighted images (DWI) obtained by echo-planar imaging (EPI) are frequently degraded by susceptibility artifacts. It has been suggested that DWI obtained by fast advanced spin-echo (FASE) or reconstructed with deep learning reconstruction (DLR) could be useful for image quality improvements. The purpose of this investigation using in vitro and in vivo studies was to determine the influence of sequence difference and of DLR for DWI on image quality, apparent diffusion coefficient (ADC) evaluation, and differentiation of malignant from benign head and neck tumors. METHODS: For the in vitro study, a DWI phantom was scanned by FASE and EPI sequences and reconstructed with and without DLR. Each ADC within the phantom for each DWI was then assessed and correlated for each measured ADC and standard value by Spearman's rank correlation analysis. For the in vivo study, DWIs obtained by EPI and FASE sequences were also obtained for head and neck tumor patients. Signal-to-noise ratio (SNR) and ADC were then determined based on ROI measurements, while SNR of tumors and ADC were compared between all DWI data sets by means of Tukey's Honest Significant Difference test. RESULTS: For the in vitro study, all correlations between measured ADC and standard reference were significant and excellent (0.92 ≤ ρ ≤ 0.99, p < 0.0001). For the in vivo study, the SNR of FASE with DLR was significantly higher than that of FASE without DLR (p = 0.02), while ADC values for benign and malignant tumors showed significant differences between each sequence with and without DLR (p < 0.05). CONCLUSION: In comparison with EPI sequence, FASE sequence and DLR can improve image quality and distortion of DWIs without significantly influencing ADC measurements or differentiation capability of malignant from benign head and neck tumors.

Chest Magnetic Resonance Imaging: Advances and Clinical Care.

Many promising study results as well as technical advances for chest magnetic resonance imaging (MRI) have demonstrated its academic and clinical potentials during the last few decades, although chest MRI has been used for relatively few clinical situations in routine clinical practice. However, the Fleischner Society as well as the Japanese Society of Magnetic Resonance in Medicine have published a few white papers to promote chest MRI in routine clinical practice. In this review, we present clinical evidence of the efficacy of chest MRI for 1) thoracic oncology and 2) pulmonary vascular diseases.

Efficacy of dupilumab for airway hypersecretion and airway wall thickening in patients with moderate-to-severe asthma: A prospective, observational study.

BACKGROUND: Dupilumab has clinical effects in patients with moderate-to-severe asthma. When considering interleukin (IL)-4 and IL-13 signaling, effects of dupilumab on airway mucus hypersecretion and airway remodeling are expected, but they have been reported in only a few short-term studies. Its efficacy for airway hyperresponsiveness (AHR) remains unknown. We comprehensively assessed the efficacy of dupilumab, especially for subjective and objective measures of airway mucus hypersecretion and airway dimensions in moderate-to-severe asthmatic patients. METHODS: In 28 adult patients with moderate-to-severe uncontrolled asthma, the comprehensive efficacy of 48-week dupilumab treatment, including the Cough and Sputum Assessment Questionnaire (CASA-Q), radiological mucus scores and airway dimensions on computed tomography (CT), was assessed prospectively. Treatment responsiveness to dupilumab was analyzed. RESULTS: With 48-week dupilumab treatment, all four cough and sputum domain scores of CASA-Q improved significantly. Radiological mucus scores and airway wall thickening on CT were significantly decreased. The decreases in mucus scores were significantly associated with improvements in Asthma Control Questionnaire scores, Asthma Quality of Life Questionnaire (AQLQ) overall scores, airway obstruction, and airway type 2 inflammation. When defined by > 0.5 improvement in AQLQ overall scores, 18 patients (64%) were identified as responders. CONCLUSIONS: Dupilumab reversed subjective and objective measures of airway mucus hypersecretion and some aspects of airway remodeling in patients with moderate-to-severe uncontrolled asthma.

Compressed sensing with deep learning reconstruction: Improving capability of gadolinium-EOB-enhanced 3D T1WI.

PURPOSE: The purpose of this study was to determine the utility of compressed sensing (CS) with deep learning reconstruction (DLR) for improving spatial resolution, image quality and focal liver lesion detection on high-resolution contrast-enhanced T1-weighted imaging (HR-CE-T1WI) obtained by CS with DLR as compared with conventional CE-T1WI with parallel imaging (PI). METHODS: Seventy-seven participants with focal liver lesions underwent conventional CE-T1WI with PI and HR-CE-T1WI, surgical resection, transarterial chemoembolization, and radiofrequency ablation, followed by histopathological or >2-year follow-up examinations in our hospital. Signal-to-noise ratios (SNRs) of liver, spleen and kidney were calculated for each patient, after which each SNR was compared by means of paired t-test. To compare focal lesion detection capabilities of the two methods, a 5-point visual scoring system was adopted for a per lesion basis analysis. Jackknife free-response receiver operating characteristic (JAFROC) analysis was then performed, while sensitivity and false positive rates (/data set) for consensus assessment of the two methods were also compared by using McNemar's test or the signed rank test. RESULTS: Each SNR of HR-CE-T1WI was significantly higher than that of conventional CE-T1WI with PI (p < 0.05). Sensitivities for consensus assessment showed that HR-CE-MRI had significantly higher sensitivity than conventional CE-T1WI with PI (p = 0.004). Moreover, there were significantly fewer FP/cases for HR-CE-T1WI than for conventional CE-T1WI with PI (p = 0.04). CONCLUSION: CS with DLR are useful for improving spatial resolution, image quality and focal liver lesion detection capability of Gd-EOB-DTPA enhanced 3D T1WI without any need for longer breath-holding time.

Diffusion weighted imaging with reverse encoding distortion correction: Improvement of image quality and distortion for accurate ADC evaluation in in vitro and in vivo studies.

PURPOSE: The purpose of this in vivo study was to determine the effect of reverse encoding direction (RDC) on apparent diffusion coefficient (ADC) measurements and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign tumors on head and neck diffusion-weighted imaging (DWI). METHODS: Forty-eight patients with head and neck tumors underwent DWI with and without RDC and pathological examinations. Their tumors were then divided into two groups: malignant (n = 21) and benign (n = 27). To determine the utility of RDC for DWI, the difference in the deformation ratio (DR) between DWI and T2-weighted images of each tumor was determined for each tumor area. To compare ADC measurement accuracy of DWIs with and without RDC for each patient, ADC values for tumors and spinal cord were determined by using ROI measurements. To compare DR and ADC between two methods, Student's t-tests were performed. Then, ADC values were compared between malignant and benign tumors by Student's t-test on each DWI. Finally, sensitivity, specificity and accuracy were compared by means of McNemar's test. RESULTS: DR of DWI with RDC was significantly smaller than that without RDC (p < 0.0001). There were significant differences in ADC between malignant and benign lesions on each DWI (p < 0.05). However, there were no significant difference of diagnostic accuracy between the two DWIs (p > 0.05). CONCLUSION: RDC can improve image quality and distortion of DWI and may have potential for more accurate ADC evaluation and differentiation of malignant from benign head and neck tumors.

Pulmonary MRI with ultra-short TE using single- and dual-echo methods: comparison of capability for quantitative differentiation of non- or minimally invasive adenocarcinomas from other lung cancers with that of standard-dose thin-section CT.

OBJECTIVE: The purpose of this study was thus to compare capabilities for quantitative differentiation of non- and minimally invasive adenocarcinomas from other of pulmonary MRIs with ultra-short TE (UTE) obtained with single- and dual-echo techniques (UTE-MRISingle and UTE-MRIDual) and thin-section CT for stage IA lung cancer patients. METHODS: Ninety pathologically diagnosed stage IA lung cancer patients who underwent thin-section standard-dose CT, UTE-MRISingle, and UTE-MRIDual, surgical treatment and pathological examinations were included in this retrospective study. The largest dimension (Dlong), solid portion (solid Dlong), and consolidation/tumor (C/T) ratio of each nodule were assessed. Two-tailed Student's t-tests were performed to compare all indexes obtained with each method between non- and minimally invasive adenocarcinomas and other lung cancers. Receiver operating characteristic (ROC)-based positive tests were performed to determine all feasible threshold values for distinguishing non- or minimally invasive adenocarcinoma (MIA) from other lung cancers. Sensitivity, specificity, and accuracy were then compared by means of McNemar's test. RESULTS: Each index showed significant differences between the two groups (p < 0.0001). Specificities and accuracies of solid Dlong for UTE-MRIDual2nd echo and CTMediastinal were significantly higher than those of solid Dlong for UTE-MRISingle and UTE-MRIDual1st echo and all C/T ratios except CTMediastinal (p < 0.05). Moreover, the specificities and accuracies of solid Dlong and C/T ratio were significantly higher than those of Dlong for each method (p < 0.05). CONCLUSION: Pulmonary MRI with UTE is considered at least as valuable as thin-section CT for quantitative differentiation of non- and minimally invasive adenocarcinomas from other stage IA lung cancers. CLINICAL RELEVANCE STATEMENT: Pulmonary MRI with UTE's capability for quantitative differentiation of non- and minimally invasive adenocarcinomas from other lung cancers in stage IA lung cancer patients is equal or superior to that of thin-section CT. KEY POINTS: • Correlations were excellent for pathologically examined nodules with the largest dimensions (Dlong) and a solid component (solid Dlong) for all indexes (0.95 ≤ r ≤ 0.99, p < 0.0001). • Pathologically examined Dlong and solid Dlong obtained with all methods showed significant differences between non- and minimally invasive adenocarcinomas and other lung cancers (p < 0.0001). • Solid tumor components are most accurately measured by UTE-MRIDual2nd echo and CTMediastinal, whereas the ground-glass component is imaged by UTE-MRIDual1st echo and CTlung with high accuracy. UTE-MRIDual predicts tumor invasiveness with 100% sensitivity and 87.5% specificity at a C/T threshold of 0.5.

Computed tomography radiomic feature analysis of thymic epithelial tumors: Differentiation of thymic epithelial tumors from thymic cysts and prediction of histological subtypes.

PURPOSE: To investigate the value of computed tomography (CT) radiomic feature analysis for the differential diagnosis between thymic epithelial tumors (TETs) and thymic cysts, and prediction of histological subtypes of TETs. MATERIALS AND METHODS: Twenty-four patients with TETs (13 low-risk and 9 high-risk thymomas, and 2 thymic carcinomas) and 12 with thymic cysts were included in this study. For each lesion, the radiomic features of a volume of interest covering the lesion were extracted from non-contrast enhanced CT images. The Least Absolute Shrinkage and Selection Operator (Lasso) method was used for the feature selection. Predictive models for differentiating TETs from thymic cysts (model A), and high risk thymomas + thymic carcinomas from low risk thymomas (model B) were created from the selected features. The receiver operating characteristic curve was used to evaluate the effectiveness of radiomic feature analysis for differentiating among these tumors. RESULTS: In model A, the selected 5 radiomic features for the model A were NGLDM_Contrast, GLCM_Correlation, GLZLM_SZLGE, DISCRETIZED_HISTO_Entropy_log2, and DISCRETIZED_HUmin. In model B, sphericity was the only selected feature. The area under the curve, sensitivity, and specificity of radiomic feature analysis were 1 (95% confidence interval [CI]: 1-1), 100%, and 100%, respectively, for differentiating TETs from thymic cysts (model A), and 0.76 (95%CI: 0.53-0.99), 64%, and 100% respectively, for differentiating high-risk thymomas + thymic carcinomas from low-risk thymomas (model B). CONCLUSION: CT radiomic analysis could be utilized as a non-invasive imaging technique for differentiating TETs from thymic cysts, and high-risk thymomas + thymic carcinomas from low-risk thymomas.

Lung Magnetic Resonance Imaging: Technical Advancements and Clinical Applications.

ABSTRACT: Since lung magnetic resonance imaging (MRI) became clinically available, limited clinical utility has been suggested for applying MRI to lung diseases. Moreover, clinical applications of MRI for patients with lung diseases or thoracic oncology may vary from country to country due to clinical indications, type of health insurance, or number of MR units available. Because of this situation, members of the Fleischner Society and of the Japanese Society for Magnetic Resonance in Medicine have published new reports to provide appropriate clinical indications for lung MRI. This review article presents a brief history of lung MRI in terms of its technical aspects and major clinical indications, such as (1) what is currently available, (2) what is promising but requires further validation or evaluation, and (3) which developments warrant research-based evaluations in preclinical or patient studies. We hope this article will provide Investigative Radiology readers with further knowledge of the current status of lung MRI and will assist them with the application of appropriate protocols in routine clinical practice.

Low Daily Step Count Associated with Small Erector Spine Muscle Area and Sarcopenia in Idiopathic Pulmonary Fibrosis.

Objective The daily step count is associated with mortality in idiopathic pulmonary fibrosis (IPF). However, the factors associated with this phenomenon are not yet fully understood. We therefore clarified its association with clinical parameters. Methods Fifty-nine patients with IPF with available data for daily step counts; 6-minute walk distance (6MWD); chest, abdominal, and pelvic computed tomography (CT); pulmonary function; psychological evaluations; and sarcopenia assessments were prospectively enrolled. The daily step count was measured continuously for seven consecutive days. The cross-sectional areas of the erector spinae muscles at the level of the 12th vertebra (ESMCSA) and psoas major muscle volume (PMV) obtained by CT were assessed. Results The average age of the patients was 73.3±8.1 years old, and the percent predicted forced vital capacity was 81.6% ±15.8%. The average daily step count was 4,258 (2,155-6,991) steps. The average 6MWD, ESMCSA, and PMV were 413±97 m, 25.5±6.7 cm2, and 270±75.6 cm3, respectively. A linear regression analysis for daily step count showed that the ESMCSA and 6MWD were independent factors for the daily step count, whereas the PMV and skeletal muscle index were not. The daily step count, ESMCSA, and 6MWD were lower in patients with sarcopenia than in those without sarcopenia. Conclusions A lower daily step count was associated with a smaller erector spinae muscle area and sarcopenia in patients with IPF. Further studies are warranted to confirm the importance of physical therapy for muscle strengthening in patients with IPF.

Deep Learning Reconstruction to Improve the Quality of MR Imaging: Evaluating the Best Sequence for T-category Assessment in Non-small Cell Lung Cancer Patients.

PURPOSE: Deep learning reconstruction (DLR) has been recommended as useful for improving image quality. Moreover, compressed sensing (CS) or DLR has been proposed as useful for improving temporal resolution and image quality on MR sequences in different body fields. However, there have been no reports regarding the utility of DLR for image quality and T-factor assessment improvements on T2-weighted imaging (T2WI), short inversion time (TI) inversion recovery (STIR) imaging, and unenhanced- and contrast-enhanced (CE) 3D fast spoiled gradient echo (GRE) imaging with and without CS in comparison with thin-section multidetector-row CT (MDCT) for non-small cell lung cancer (NSCLC) patients. The purpose of this study was to determine the utility of DLR for improving image quality and the appropriate sequence for T-category assessment for NSCLC patients. METHODS: As subjects for this study, 213 pathologically diagnosed NSCLC patients who underwent thin-section MDCT and MR imaging as well as T-factor diagnosis were retrospectively enrolled. SNR of each tumor was calculated and compared by paired t-test for each sequence with and without DLR. T-factor for each patient was assessed with thin-section MDCT and all MR sequences, and the accuracy for T-factor diagnosis was compared among all sequences and thin-section CT by means of McNemar's test. RESULTS: SNRs of T2WI, STIR imaging, unenhanced thin-section Quick 3D imaging, and CE-thin-section Quick 3D imaging with DLR were significantly higher than SNRs of those without DLR (P < 0.05). Diagnostic accuracy of STIR imaging and CE-thick- or thin-section Quick 3D imaging was significantly higher than that of thin-section CT, T2WI, and unenhanced thick- or thin-section Quick 3D imaging (P < 0.05). CONCLUSION: DLR is thus considered useful for image quality improvement on MR imaging. STIR imaging and CE-Quick 3D imaging with or without CS were validated as appropriate MR sequences for T-factor evaluation in NSCLC patients.

Area-Detector Computed Tomography for Pulmonary Functional Imaging.

An area-detector CT (ADCT) has a 320-detector row and can obtain isotropic volume data without helical scanning within an area of nearly 160 mm. The actual-perfusion CT data within this area can, thus, be obtained by means of continuous dynamic scanning for the qualitative or quantitative evaluation of regional perfusion within nodules, lymph nodes, or tumors. Moreover, this system can obtain CT data with not only helical but also step-and-shoot or wide-volume scanning for body CT imaging. ADCT also has the potential to use dual-energy CT and subtraction CT to enable contrast-enhanced visualization by means of not only iodine but also xenon or krypton for functional evaluations. Therefore, systems using ADCT may be able to function as a pulmonary functional imaging tool. This review is intended to help the reader understand, with study results published during the last a few decades, the basic or clinical evidence about (1) newly applied reconstruction methods for radiation dose reduction for functional ADCT, (2) morphology-based pulmonary functional imaging, (3) pulmonary perfusion evaluation, (4) ventilation assessment, and (5) biomechanical evaluation.

Advances for Pulmonary Functional Imaging: Dual-Energy Computed Tomography for Pulmonary Functional Imaging.

Dual-energy computed tomography (DECT) can improve the differentiation of material by using two different X-ray energy spectra, and may provide new imaging techniques to diagnostic radiology to overcome the limitations of conventional CT in characterizing tissue. Some techniques have used dual-energy imaging, which mainly includes dual-sourced, rapid kVp switching, dual-layer detectors, and split-filter imaging. In iodine images, images of the lung's perfused blood volume (PBV) based on DECT have been applied in patients with pulmonary embolism to obtain both images of the PE occluding the pulmonary artery and the consequent perfusion defects in the lung's parenchyma. PBV images of the lung also have the potential to indicate the severity of PE, including chronic thromboembolic pulmonary hypertension. Virtual monochromatic imaging can improve the accuracy of diagnosing pulmonary vascular diseases by optimizing kiloelectronvolt settings for various purposes. Iodine images also could provide a new approach in the area of thoracic oncology, for example, for the characterization of pulmonary nodules and mediastinal lymph nodes. DECT-based lung ventilation imaging is also available with noble gases with high atomic numbers, such as xenon, which is similar to iodine. A ventilation map of the lung can be used to image various pulmonary diseases such as chronic obstructive pulmonary disease.

Effectiveness of deep learning reconstruction on standard to ultra-low-dose high-definition chest CT images.

PURPOSE: Deep learning reconstruction (DLR) has been introduced by major vendors, tested for CT examinations of a variety of organs, and compared with other reconstruction methods. The purpose of this study was to compare the capabilities of DLR for image quality improvement and lung texture evaluation with those of hybrid-type iterative reconstruction (IR) for standard-, reduced- and ultra-low-dose CTs (SDCT, RDCT and ULDCT) obtained with high-definition CT (HDCT) and reconstructed at 0.25-mm, 0.5-mm and 1-mm section thicknesses with 512 × 512 or 1024 × 1024 matrixes for patients with various pulmonary diseases. MATERIALS AND METHODS: Forty age-, gender- and body mass index-matched patients with various pulmonary diseases underwent SDCT (CT dose index volume : mean ± standard deviation, 9.0 ± 1.8 mGy), RDCT (CTDIvol: 1.7 ± 0.2 mGy) and ULDCT (CTDIvol: 0.8 ± 0.1 mGy) at a HDCT. All CT data set were then reconstructed with 512 × 512 or 1024 × 1024 matrixes by means of hybrid-type IR and DLR. SNR of lung parenchyma and probabilities of all lung textures were assessed for each CT data set. SNR and detection performance of each lung texture reconstructed with DLR and hybrid-type IR were then compared by means of paired t tests and ROC analyses for all CT data at each section thickness. RESULTS: Data for each radiation dose showed DLR attained significantly higher SNR than hybrid-type IR for each of the CT data (p < 0.0001). On assessments of all findings except consolidation and nodules or masses, areas under the curve (AUCs) for ULDCT with hybrid-type IR for each section thickness (0.91 ≤ AUC ≤ 0.97) were significantly smaller than those with DLR (0.97 ≤ AUC ≤ 1, p < 0.05) and the standard protocol (0.98 ≤ AUC ≤ 1, p < 0.05). CONCLUSION: DLR is potentially more effective for image quality improvement and lung texture evaluation than hybrid-type IR on all radiation dose CTs obtained at HDCT and reconstructed with each section thickness with both matrixes for patients with a variety of pulmonary diseases.

Capability for dose reduction while maintaining nodule detection: Comparison of silver and copper X-ray spectrum modulation filters for chest CT using a phantom study with different reconstruction methods.

PURPOSE: To compare the capability of CTs obtained with a silver or copper x-ray beam spectral modulation filter (Ag filter and Cu filter) and reconstructed with FBP, hybrid-type IR and deep learning reconstruction (DLR) for radiation dose reduction for lung nodule detection using a chest phantom study. MATERIALS AND METHODS: A chest CT phantom was scanned with a 320-detector row CT with Ag filter at 0.6, 1.6 and 2.5 mGy and Cu filters at 0.6, 1.6, 2.5 and 9.6 mGy, and reconstructed with the aforementioned methods. To compare image quality of all the CT data, SNRs and CNRs for any nodule were calculated for all protocols. To compare nodule detection capability among all protocols, the probability of detection of any nodule was assessed with a 5-point visual scoring system. Then, ROC analyses were performed to compare nodule detection capability of Ag and Cu filters for each radiation dose data with the same method and of the three methods for any radiation dose data and obtained with either filter. RESULTS: At any of the doses, SNR, CNR and area under the curve for the Ag filter were significantly higher or larger than those for the Cu filter (p < 0.05). Moreover, with DLR, those values were significantly higher or larger than all the others for CTs obtained with any of the radiation doses and either filter (p < 0.05). CONCLUSION: The Ag filter and DLR can significantly improve image quality and nodule detection capability compared with the Cu filter and other reconstruction methods at each of radiation doses used.

Reverse encoding distortion correction for diffusion-weighted MRI: Efficacy for improving image quality and ADC evaluation for differentiating malignant from benign areas in suspected prostatic cancer patients.

PURPOSE: The purpose of this study was to determine the influenceof reverse encoding distortion correction (RDC) on ADC measurement and its efficacy for improving image quality and diagnostic performance for differentiating malignant from benign prostatic areas on prostatic DWI. METHODS: Forty suspected prostatic cancer patients underwent DWI with or without RDC (i.e. RDC DWI or DWI) using a 3 T MR system as well as pathological examinations. The pathological examination results indicated 86 areas were malignant while 86 out of 394 areas were computationally selected as benign. SNR for benign areas and muscle and ADCs for malignant and benign areas were determined by ROI measurements on each DWI. Moreover, overall image quality was assessed with a 5-point visual scoring system on each DWI. Paired t-test or Wilcoxon's signed rank test was performed to compare SNR and overall image quality for DWIs. ROC analysis was then used to compare the diagnostic performance, and sensitivity (SE), specificity (SP) and accuracy (AC) of ADC were compared between two DWI by means of McNemar's test. RESULTS: SNR and overall image quality of RDC DWI showed significant improvements when compared with those of DWI (p < 0.05). Areas under the curve (AUC), SP and AC of DWI RDC DWI (AUC: 0.85, SP: 72.1%, AC: 79.1%) were significantly better than those of DWI (AUC: 0.79, p = 0.008; SP: 64%, p = 0.02; AC: 74.4%, p = 0.008). CONCLUSION: RDC technique has the potential to improve image quality and ability to differentiate malignant from benign prostatic areas on DWIs of suspected prostatic cancer patients.

Chemical Exchange Saturation Transfer MRI: Capability for Predicting Therapeutic Effect of Chemoradiotherapy on Non-Small Cell Lung Cancer Patients.

BACKGROUND: Amide proton transfer (APT) weighted chemical exchange saturation transfer CEST (APTw/CEST) magnetic resonance imaging (MRI) has been suggested as having the potential for assessing the therapeutic effect of brain tumors or rectal cancer. Moreover, diffusion-weighted imaging (DWI) and positron emission tomography fused with computed tomography by means of 2-[fluorine-18]-fluoro-2-deoxy-D-glucose (FDG-PET/CT) have been suggested as useful in same setting. PURPOSE: To compare the capability of APTw/CEST imaging, DWI, and FDG-PET/CT for predicting therapeutic effect of chemoradiotherapy (CRT) on stage III non-small cell lung cancer (NSCLC) patients. STUDY TYPE: Prospective. POPULATION: Eighty-four consecutive patients with Stage III NSCLC, 45 men (age range, 62-75 years; mean age, 71 years) and 39 women (age range, 57-75 years; mean age, 70 years). All patients were then divided into two groups (Response Evaluation Criteria in Solid Tumors [RECIST] responders, consisting of the complete response and partial response groups, and RECIST non-responders, consisting of the stable disease and progressive disease groups). FIELD STRENGTH/SEQUENCE: 3 T, echo planar imaging or fast advanced spin-echo (FASE) sequences for DWI and 2D half Fourier FASE sequences with magnetization transfer pulses for CEST imaging. ASSESSMENT: Magnetization transfer ratio asymmetry (MTRasym ) at 3.5 ppm, apparent diffusion coefficient (ADC), and maximum standard uptake value (SUVmax, ) on PET/CT were assessed by means of region of interest (ROI) measurements at primary tumor. STATISTICAL TESTS: Kaplan-Meier method followed by log-rank test and Cox proportional hazards regression analysis with multivariate analysis. A P value <0.05 was considered statistically significant. RESULTS: Progression-free survival (PFS) and overall survival (OS) had significant difference between two groups. MTRasym at 3.5 ppm (hazard ratio [HR] = 0.70) and SUVmax (HR = 1.41) were identified as significant predictors for PFS. Tumor staging (HR = 0.57) was also significant predictors for OS. DATA CONCLUSION: APTw/CEST imaging showed potential performance as DWI and FDG-PET/CT for predicting the therapeutic effect of CRT on stage III NSCLC patients. LEVEL OF EVIDENCE: 2 TECHNICAL EFFICACY: Stage 1.

State of the Art MR Imaging for Lung Cancer TNM Stage Evaluation.

Since the Radiology Diagnostic Oncology Group (RDOG) report had been published in 1991, magnetic resonance (MR) imaging had limited clinical availability for thoracic malignancy, as well as pulmonary diseases. However, technical advancements in MR systems, such as sequence and reconstruction methods, and adjustments in the clinical protocol for gadolinium contrast media administration have provided fruitful results and validated the utility of MR imaging (MRI) for lung cancer evaluations. These techniques include: (1) contrast-enhanced MR angiography for T-factor evaluation, (2) short-time inversion recovery turbo spin-echo sequences as well as diffusion-weighted imaging (DWI) for N-factor assessment, and (3) whole-body MRI with and without DWI and with positron emission tomography fused with MRI for M-factor or TNM stage evaluation as well as for postoperative recurrence assessment of lung cancer or other thoracic tumors using 1.5 tesla (T) or 3T systems. According to these fruitful results, the Fleischner Society has changed its position to approve of MRI for lung or thoracic diseases. The purpose of this review is to analyze recent advances in lung MRI with a particular focus on lung cancer evaluation, clinical staging, and recurrence assessment evaluation.