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.

Enhanced measures, including PCR-based screening and syndromic surveillance for nosocomial outbreaks of the COVID-19 Omicron variant, using descriptive epidemiology and whole-genome sequencing in a Japanese tertiary care hospital.

INTRODUCTION: In this study, we aimed to analyze the effectiveness of enhanced preventive measures against nosocomial COVID-19 Omicron outbreaks based on those encountered. METHODS: We introduced PCR-based screening and syndromic surveillance, in addition to standard and transmission-based precautions, during a COVID-19 outbreak in three wards of Kagoshima University Hospital, a Japanese tertiary care hospital, in February 2022, amid the Omicron variant endemic. Furthermore, we analyzed the descriptive epidemiology and whole-genome sequencing (WGS) of positive SARS-CoV-2 PCR samples from this outbreak. RESULTS: PCR-based screening tests were conducted following the identification of three cases through syndromic surveillance. As a result, 30 individuals tested positive for SARS-CoV-2, including 13 inpatients, five attendant family members, and 12 healthcare workers across the three wards. Notably, no new infections were observed within eight days following the implementation of preventive measures. Among the SARS-CoV-2 genomes analyzed (n = 16; 53.3%), all strains were identified as belonged to BA.1.1 variant. Detailed analysis of descriptive and molecular epidemiology, incorporating single-nucleotide polymorphism analysis of WGS and clarification of transmission links, considering two potential entry routes to the hospital. CONCLUSIONS: Introduction of additional preventive measures, including PCR-based screening and syndromic surveillance, in addition to WGS and descriptive epidemiology, is useful for the early intervention of nosocomial outbreaks and for revealing the transmission route of the COVID-19 Omicron variant.

Genomic and phylogenetic characterization of Elizabethkingia anophelis strains: The first two cases of life-threatening infection in Japan.

OBJECTIVE: Elizabethkingia anophelis causes meningitis, bloodstream infections, and respiratory infections in immunocompromised individuals. We examined two E. anophelis strains isolated from the first life-threatening cases caused by this species in Japan to determine the phylogenetic origin and genomic features of them. METHODS: We performed whole genome-based analysis to clarify the genetic relationship for the two strains (EK0004 and EK0079) and Elizabethkingia sp. strains isolated from worldwide and to characterize the genomic features such as the prevalence of virulence- and antimicrobial resistance (AMR)-related genes. PATIENTS: A 29-year-old man with hepatosplenic T-cell lymphoma and a 52-year-old man with systemic lupus erythematosus developed fatal bacteremia and meningitis due to E. anophelis, respectively. RESULTS: Two strains, EK0004 and EK0079, were genetically different but most closely related to the strains isolated from the largest outbreak in Wisconsin, USA from 2015 to 2016, and the strain isolated from cerebrospinal fluid of a patient in Florida, USA in 1982, respectively. The two strains contained AMR-related genes such as those encoding for an extended-spectrum ß-lactamase and multiple metallo-ß-lactamases and several virulence-related genes such as capsular polysaccharide synthesis gene clusters. CONCLUSIONS: Although further functional analyses are required to understand the virulence of these clones, these finding suggests that enough caution of E. anophelis infection in immunocompromised patients is required since the number of infections by this species is increasing outside Japan.

Computed DWI MRI Results in Superior Capability for N-Stage Assessment of Non-Small Cell Lung Cancer Than That of Actual DWI, STIR Imaging, and FDG-PET/CT.

BACKGROUND: Computed diffusion-weighted imaging (cDWI) is a mathematical computation technique that generates DWIs for any b-value by using actual DWI (aDWI) data with at least two different b-values and may improve differentiation of metastatic from nonmetastatic lymph nodes. PURPOSE: To determine the appropriate b-value for cDWI to achieve a better diagnostic capability for lymph node staging (N-staging) in non-small cell lung cancer (NSCLC) patients compared to aDWI, short inversion time (TI) inversion recovery (STIR) imaging, or positron emission tomography with 2-[fluorine-18] fluoro-2-deoxy-d-glucose combined with computed tomography (FDG-PET/CT). STUDY TYPE: Prospective. SUBJECTS: A total of 245 (127 males and 118 females; mean age 72 years) consecutive histopathologically confirmed NSCLC patients. FIELD STRENGTH/SEQUENCE: A 3 T, half-Fourier single-shot turbo spin-echo sequence, electrocardiogram (ECG)-triggered STIR fast advanced spin-echo (FASE) sequence with black blood and STIR acquisition and DWI obtained by FASE with b-values of 0 and 1000 sec/mm2 . ASSESSMENT: From aDWIs with b-values of 0 and 1000 (aDWI1000 ) sec/mm2 , cDWI using 400 (cDWI400 ), 600 (cDWI600 ), 800 (cDWI800 ), and 2000 (cDWI2000 ) sec/mm2 were generated. Then, 114 metastatic and 114 nonmetastatic nodes (mediastinal and hilar lymph nodes) were selected and evaluated with a contrast ratio (CR) for each cDWI and aDWI, apparent diffusion coefficient (ADC), lymph node-to-muscle ratio (LMR) on STIR, and maximum standard uptake value (SUVmax ). STATISTICAL TESTS: Receiver operating characteristic curve (ROC) analysis, Youden index, and McNemar's test. RESULTS: Area under the curve (AUC) of CR600 was significantly larger than the CR400 , CR800 , CR2000 , aCR1000 , and SUVmax . Comparison of N-staging accuracy showed that CR600 was significantly higher than CR400 , CR2000 , ADC, aCR1000 , and SUVmax , although there were no significant differences with CR800 (P = 0.99) and LMR (P = 0.99). DATA CONCLUSION: cDWI with b-value at 600 sec/mm2 may have potential to improve N-staging accuracy as compared with aDWI, STIR, and PET/CT. EVIDENCE LEVEL: 2 TECHNICAL EFFICACY: Stage 2.

Comparison of lung CT number and airway dimension evaluation capabilities of ultra-high-resolution CT, using different scan modes and reconstruction methods including deep learning reconstruction, with those of multi-detector CT in a QIBA phantom study.

OBJECTIVE: Ultra-high-resolution CT (UHR-CT), which can be applied normal resolution (NR), high-resolution (HR), and super-high-resolution (SHR) modes, has become available as in conjunction with multi-detector CT (MDCT). Moreover, deep learning reconstruction (DLR) method, as well as filtered back projection (FBP), hybrid-type iterative reconstruction (IR), and model-based IR methods, has been clinically used. The purpose of this study was to directly compare lung CT number and airway dimension evaluation capabilities of UHR-CT using different scan modes with those of MDCT with different reconstruction methods as investigated in a lung density and airway phantom design recommended by QIBA. MATERIALS AND METHODS: Lung CT number, inner diameter (ID), inner area (IA), and wall thickness (WT) were measured, and mean differences between measured CT number, ID, IA, WT, and standard reference were compared by means of Tukey's HSD test between all UHR-CT data and MDCT reconstructed with FBP as 1.0-mm section thickness. RESULTS: For each reconstruction method, mean differences in lung CT numbers and all airway parameters on 0.5-mm and 1-mm section thickness CTs obtained with SHR and HR modes showed significant differences with those obtained with the NR mode on UHR-CT and MDCT (p < 0.05). Moreover, the mean differences on all UHR-CTs obtained with SHR, HR, or NR modes were significantly different from those of 1.0-mm section thickness MDCTs reconstructed with FBP (p < 0.05). CONCLUSION: Scan modes and reconstruction methods used for UHR-CT were found to significantly affect lung CT number and airway dimension evaluations as did reconstruction methods used for MDCT. KEY POINTS: • Scan and reconstruction methods used for UHR-CT showed significantly higher CT numbers and smaller airway dimension evaluations as did those for MDCT in a QIBA phantom study (p < 0.05). • Mean differences in lung CT number for 0.25-mm, 0.5-mm, and 1.0-mm section thickness CT images obtained with SHR and HR modes were significantly larger than those for CT images at 1.0-mm section thickness obtained with MDCT and reconstructed with FBP (p < 0.05). • Mean differences in inner diameter (ID), inner area (IA), and wall thickness (WT) measured with SHR and HR modes on 0.5- and 1.0-mm section thickness CT images were significantly smaller than those obtained with NR mode on UHR-CT and MDCT (p < 0.05).

MR imaging for shoulder diseases: Effect of compressed sensing and deep learning reconstruction on examination time and imaging quality compared with that of parallel imaging.

PURPOSE: To compare capabilities of compressed sensing (CS) with and without deep learning reconstruction (DLR) with those of conventional parallel imaging (PI) with and without DLR for improving examination time and image quality of shoulder MRI for patients with various shoulder diseases. METHODS AND MATERIALS: Thirty consecutive patients with suspected shoulder diseases underwent MRI at a 3 T MR system using PI and CS. All MR data was reconstructed with and without DLR. For quantitative image quality evaluation, ROI measurements were used to determine signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). For qualitative image quality assessment, two radiologists evaluated overall image quality, artifacts and diagnostic confidence level using a 5-point scoring system, and consensus of the two readers determined each final value. Tukey's HSD test was used to compare examination times to establish the capability of the two techniques for reducing examination time. All indexes for all methods were then compared by means of Tukey's HSD test or Wilcoxon's signed rank test. RESULTS: CS with and without DLR showed significantly shorter examination times than PI with and without DLR (p < 0.05). SNR and CNR of CS or PI with DLR were significantly higher than of those without DLR (p < 0.05). Use of DLR significantly improved overall image quality and artifact incidence of CS and PI (p < 0.05). CONCLUSION: Examination time with CS is shorter than with PI without deterioration of image quality of shoulder MRI. Moreover, DLR is useful for both CS and PI for improvement of image quality on shoulder MRI.

Deep Learning Reconstruction of Diffusion-weighted MRI Improves Image Quality for Prostatic Imaging.

Background Deep learning reconstruction (DLR) may improve image quality. However, its impact on diffusion-weighted imaging (DWI) of the prostate has yet to be assessed. Purpose To determine whether DLR can improve image quality of diffusion-weighted MRI at b values ranging from 1000 sec/mm2 to 5000 sec/mm2 in patients with prostate cancer. Materials and Methods In this retrospective study, images of the prostate obtained at DWI with a b value of 0 sec/mm2, DWI with a b value of 1000 sec/mm2 (DWI1000), DWI with a b value of 3000 sec/mm2 (DWI3000), and DWI with a b value of 5000 sec/mm2 (DWI5000) from consecutive patients with biopsy-proven cancer from January to June 2020 were reconstructed with and without DLR. Image quality was assessed using signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) from region-of-interest analysis and qualitatively assessed using a five-point visual scoring system (1 [very poor] to 5 [excellent]) for each high-b-value DWI sequence with and without DLR. The SNR, CNR, and visual score for DWI with and without DLR were compared with the paired t test and the Wilcoxon signed rank test with Bonferroni correction, respectively. Apparent diffusion coefficients (ADCs) from DWI with and without DLR were also compared with the paired t test with Bonferroni correction. Results A total of 60 patients (mean age, 67 years; age range, 49-79 years) were analyzed. DWI with DLR showed significantly higher SNRs and CNRs than DWI without DLR (P < .001); for example, with DWI1000 the mean SNR was 38.7 ± 0.6 versus 17.8 ± 0.6, respectively (P < .001), and the mean CNR was 18.4 ± 5.6 versus 7.4 ± 5.6, respectively (P < .001). DWI with DLR also demonstrated higher qualitative image quality than DWI without DLR (mean score: 4.8 ± 0.4 vs 4.0 ± 0.7, respectively, with DWI1000 [P = .001], 3.8 ± 0.7 vs 3.0 ± 0.8 with DWI3000 [P = .002], and 3.1 ± 0.8 vs 2.0 ± 0.9 with DWI5000 [P < .001]). ADCs derived with and without DLR did not differ substantially (P > .99). Conclusion Deep learning reconstruction improves the image quality of diffusion-weighted MRI scans of prostate cancer with no impact on apparent diffusion coefficient quantitation with a 3.0-T MRI system. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Turkbey in this issue.

Machine learning for lung texture analysis on thin-section CT: Capability for assessments of disease severity and therapeutic effect for connective tissue disease patients in comparison with expert panel evaluations.

BACKGROUND: The need for quantitative assessment of interstitial lung involvement on thin-section computed tomography (CT) has arisen in interstitial lung diseases including connective tissue disease (CTD). PURPOSE: To evaluate the capability of machine learning (ML)-based CT texture analysis for disease severity and treatment response assessments in comparison with qualitatively assessed thin-section CT for patients with CTD. MATERIAL AND METHODS: A total of 149 patients with CTD-related ILD (CTD-ILD) underwent initial and follow-up CT scans (total 364 paired serial CT examinations), pulmonary function tests, and serum KL-6 level tests. Based on all follow-up examination results, all paired serial CT examinations were assessed as "Stable" (n = 188), "Worse" (n = 98) and "Improved" (n = 78). Next, quantitative index changes were determined by software, and qualitative disease severity scores were assessed by consensus of two radiologists. To evaluate differences in each quantitative index as well as in disease severity score between paired serial CT examinations, Tukey's honestly significant difference (HSD) test was performed among the three statuses. Stepwise regression analyses were performed to determine changes in each pulmonary functional parameter and all quantitative indexes between paired serial CT scans. RESULTS: Δ% normal lung, Δ% consolidation, Δ% ground glass opacity, Δ% reticulation, and Δdisease severity score showed significant differences among the three statuses (P < 0.05). All differences in pulmonary functional parameters were significantly affected by Δ% normal lung, Δ% reticulation, and Δ% honeycomb (0.16 ≤r2 ≤0.42; P < 0.05). CONCLUSION: ML-based CT texture analysis has better potential than qualitatively assessed thin-section CT for disease severity assessment and treatment response evaluation for CTD-ILD.

State-of-the-art MR Imaging for Thoracic Diseases.

Since thoracic MR imaging was first used in a clinical setting, it has been suggested that MR imaging has limited clinical utility for thoracic diseases, especially lung diseases, in comparison with x-ray CT and positron emission tomography (PET)/CT. However, in many countries and states and for specific indications, MR imaging has recently become practicable. In addition, recently developed pulmonary MR imaging with ultra-short TE (UTE) and zero TE (ZTE) has enhanced the utility of MR imaging for thoracic diseases in routine clinical practice. Furthermore, MR imaging has been introduced as being capable of assessing pulmonary function. It should be borne in mind, however, that these applications have so far been academically and clinically used only for healthy volunteers, but not for patients with various pulmonary diseases in Japan or other countries. In 2020, the Fleischner Society published a new report, which provides consensus expert opinions regarding appropriate clinical indications of pulmonary MR imaging for not only oncologic but also pulmonary diseases. This review article presents a brief history of MR imaging for thoracic diseases regarding its technical aspects and major clinical indications in Japan 1) in terms of what is currently available, 2) promising but requiring further validation or evaluation, and 3) developments warranting research investigations in preclinical or patient studies. State-of-the-art MR imaging can non-invasively visualize lung structural and functional abnormalities without ionizing radiation and thus provide an alternative to CT. MR imaging is considered as a tool for providing unique information. Moreover, prospective, randomized, and multi-center trials should be conducted to directly compare MR imaging with conventional methods to determine whether the former has equal or superior clinical relevance. The results of these trials together with continued improvements are expected to update or modify recommendations for the use of MRI in near future.

Overview of MRI for pulmonary functional imaging.

Morphological evaluation of the lung is important in the clinical evaluation of pulmonary diseases. However, the disease process, especially in its early phases, may primarily result in changes in pulmonary function without changing the pulmonary structure. In such cases, the traditional imaging approaches to pulmonary morphology may not provide sufficient insight into the underlying pathophysiology. Pulmonary imaging community has therefore tried to assess pulmonary diseases and functions utilizing not only nuclear medicine, but also CT and MR imaging with various technical approaches. In this review, we overview state-of-the art MR methods and the future direction of: (1) ventilation imaging, (2) perfusion imaging and (3) biomechanical evaluation for pulmonary functional imaging.

Safe and low-dose but therapeutically effective adenovirus-mediated hepatocyte growth factor gene therapy for type 1 diabetes in mice.

AIMS: Hepatocyte growth factor (HGF) is a multifunctional cytokine that plays important roles in pancreatic physiology. Approvals of gene therapy drugs have highlighted gene therapy as an innovative new drug modality, but the very recent reports of deaths in clinical trials have provided a warning that high-dose gene therapy can cause dangerous liver toxicity. The present study aimed to develop a safe and low-dose but therapeutically effective adenovirus-mediated HGF gene therapy for streptozotocin (STZ)-induced type 1 diabetes (T1D) in mice. MAIN METHODS: A single intravenous injection of a low dose (3 × 108 plaque forming units) of adenoviral vector expressing the HGF gene under the transcriptional control of a strong promoter, i.e., the cytomegalovirus immediate-early enhancer and a modified chicken ß-actin promoter (Ad.CA-HGF), was given to T1D mice. KEY FINDINGS: Low-dose HGF gene therapy significantly attenuated the elevation of blood glucose concentrations at the acute phase of T1D, and this effect persisted for several weeks. Temporal upregulation of plasma insulin at the acute phase was maintained at a normal level in Ad.CA-HGF-treated mice, suggesting that the therapeutic mechanism may involve protection of the remaining ß-cells by HGF. Liver enzymes in plasma were not elevated in any of the mice, including the Ad.CA-HGF-treated animals, all of which looked healthy, suggesting the absence of lethal adverse effects observed in patients receiving high intravenous doses of viral vectors. SIGNIFICANCE: A low dose of intravenous Ad-mediated HGF gene therapy is clinically feasible and safe, and thus represents a new therapeutic strategy for treating T1D.

Compressed sensing and deep learning reconstruction for women's pelvic MRI denoising: Utility for improving image quality and examination time in routine clinical practice.

PURPOSE: To demonstrate the utility of compressed sensing with parallel imaging (Compressed SPEEDER) and AiCE compared with that of conventional parallel imaging (SPEEDER) for shortening examination time and improving image quality of women's pelvic MRI. METHOD: Thirty consecutive patients with women's pelvic diseases (mean age 50 years) underwent T2-weighted imaging using Compressed SPEEDER as well as conventional SPEEDER reconstructed with and without AiCE. The examination times were recorded, and signal-to-noise ratio (SNR) was calculated for every patient. Moreover, overall image quality was assessed using a 5-point scoring system, and final scores for all patients were determined by consensus of two readers. Mean examination time, SNR and overall image quality were compared among the four data sets by Wilcoxon signed-rank test. RESULTS: Examination times for Compressed SPEEDER with and without AiCE were significantly shorter than those for conventional SPEEDER with and without AiCE (with AiCE: p < 0.0001, without AiCE: p < 0.0001). SNR of Compressed SPEEDER and of SPEEDER with AiCE was significantly superior to that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER, p = 0.01; vs. SPEEDER, p = 0.009). Overall image quality of Compressed SPEEDER with AiCE and of SPEEDER with and without AiCE was significantly higher than that of Compressed SPEEDER without AiCE (vs. Compressed SPEEDER with AiCE, p < 0.0001; vs. SPEEDER with AiCE, p < 0.0001; SPEEDER without AiCE, p = 0.0003). CONCLUSION: Image quality and shorten examination time for T2-weighted imaging in women's pelvic MRI can be significantly improved by using Compressed SPEEDER with AiCE in comparison with conventional SPEEDER, although other sequences were not tested.

The diagnostic ability of SPECT/CT fusion imaging for gastrointestinal bleeding: a retrospective study.

BACKGROUND: Blood loss from the gastrointestinal tract can be an acute and life-threatening event. For the treatment of gastrointestinal bleeding, it is important to accurately detect gastrointestinal bleeding and to localize the sites of bleeding. The purpose of this study was to retrospectively assess the capabilities of SPECT/CT in the diagnosis of gastrointestinal bleeding by a comparison with planar imaging alone as well as planar and SPECT. METHODS: We conducted a retrospective analysis of 20 patients (21 examinations) who underwent gastrointestinal bleeding scintigraphy in the past 7 years and in whom the bleeding site was identified by endoscopy or capsule endoscopy, or in whom no evidence of gastrointestinal bleeding was identified during the clinical course. Five patients (5 examinations) were diagnosed by planar imaging (planar group). Eight patients (9 examinations) were diagnosed by planar imaging and SPECT (planar + SPECT group). Seven patients (7 examinations) were diagnosed by planar imaging and SPECT/CT (planar + SPECT/CT group). We calculated the diagnostic ability of each method in detecting the presence of bleeding, as well as the ability of each method to identify the sites of bleeding. The sensitivity, specificity, and accuracy of the methods were compared. RESULTS: The diagnostic ability of the three imaging methods in detecting the presence of gastrointestinal bleeding was as follows. Planar imaging showed 100% sensitivity (3/3), 100% specificity (2/2), and 100% accuracy (5/5). Planar + SPECT imaging showed 85.7% sensitivity (6/7), 100% specificity (2/2), and 88.9% accuracy (8/9). Planar + SPECT/CT imaging showed 100% sensitivity (6/6), 100% specificity (1/1), and 100% accuracy (7/7). The diagnostic ability of the three modalities in detecting the site of bleeding was as follows: planar, 33.3% (1/3); planar + SPECT, 71.4% (5/7); and planar + SPECT/CT, 100% (6/6). CONCLUSIONS: All 3 imaging methods showed good accuracy in detecting the presence of gastrointestinal bleeding. The addition of SPECT or SPECT/CT made the anatomical position of the uptake clear and contributed to the localization of the site of gastrointestinal bleeding. Planar + SPECT/CT imaging therefore showed the highest diagnostic ability for detecting the site of gastrointestinal bleeding.

Spectrally-Narrowed Emissions from Organic Crystals Having a One-Dimensional Grating on Their Surface.

We have succeeded in directly engraving one-dimensional diffraction gratings on the surface of organic semiconducting oligomer crystals by using focused ion beam (FIB) lithography and laser ablation (LA) methods. The FIB method enabled us to shape the gratings with varying periods down to ~150 nm. With the LA method a large-area grating with a ~500-nm period was readily accessible. All the above crystals indicated spectrally-narrowed emission (SNE) lines even in the case of shallow groove depths ~2-4 nm. In particular, we definitively observed the SNE pertinent to the first-order diffraction with the crystal having the diffraction grating of a 148.3-nm average period. The present results indicate utility of the built-in gratings that can directly be fabricated on the surface of the crystals.

Clinical Significance of Discrepancy between Arterial Spin Labeling Images and Contrast-enhanced Images in the Diagnosis of Brain Tumors.

PURPOSE: In the imaging of intra-axial brain tumors, we sometimes found areas of high signal intensity around the enhanced tumor lesions on arterial spin labeling (ASL) magnetic resonance (MR) imaging. We undertook this study to investigate the relationship between high signal intensity on ASL imaging outside the area of contrast enhancement (CE) and histological diagnosis of intra-axial brain tumors. METHODS: We examined images from 28 consecutive patients with intra-axial brain tumors who underwent ASL and CE MR imaging-three with low grade glioma (LGG), 13 with high grade glioma (HGG), six with metastasis, and six with primary central nervous system lymphoma (PCNSL)-and divided imaging findings into an "ASL dominant" group when hyperintensity on ASL was found outside the CE area and a "CE dominant" group when hyperintensity on ASL was not found outside the area of enhancement. We then analyzed the relationship between imaging findings and the histological diagnosis of the tumors. RESULTS: Four cases were excluded because of poor quality of ASL images, 7 cases were classified as ASL dominant, and 17 cases were classified as CE dominant. The histological diagnoses of ASL dominant cases were LGG in 3 cases, HGG in 3 cases, and PCNSL in one case. Those of CE dominant cases were HGG in 10 cases, metastasis in 5 cases, and PCNSL in 2 cases. All cases with brain metastasis were classified as CE dominant. CONCLUSION: The high signal intensity outside the area of contrast enhancement is probably caused by increased perfusion or vascular proliferation, which indicates the presence of glioma or PCNSL and not metastasis. This finding indicates a new utility for ASL images in the diagnosis of brain tumors as a supplement to the conventional measurement of perfusion obtained from ASL images.

Diagnosis of brain tumors using dynamic contrast-enhanced perfusion imaging with a short acquisition time.

This study sought to determine the diagnostic utility of perfusion parameters derived from dynamic contrast-enhanced (DCE) perfusion MRI with a short acquisition time (approximately 3.5 min) in patients with glioma, brain metastasis, and primary CNS lymphoma (PCNSL). Twenty-six patients with 29 lesions (4 low-grade glioma, 13 high-grade glioma, 7 metastasis, and 5 PCNSL) underwent DCE-MRI in a 3 T scanner. A ROI was placed on the hotspot of each tumor in maps for volume transfer contrast K (trans) , extravascular extracellular volume V e , and fractional plasma volume V p . We analyzed differences in parameters between tumors using the Mann-Whitney U test. We calculated sensitivity and specificity using receiver operating characteristics analysis. Mean K (trans) values of LGG, HGG, metastasis and PCNSL were 0.034, 0.31, 0.38, 0.44, respectively. Mean Ve values of each tumors was 0.036, 0.57, 0.47, 0.96, and mean Vp value of each tumors was 0.070, 0.086, 0.26, 0.17, respectively. Compared with other tumor types, low-grade glioma showed lower K (trans) (P < 0.01, sensitivity = 88%, specificity = 100%) and lower V e (P < 0.01, sensitivity = 96%, specificity = 100%). PCNSL showed higher V e (P < 0.01, sensitivity = 100%, specificity = 88%), but the other perfusion parameters overlapped with those of different histology. Kinetic parameters derived from DCE-MRI with short acquisition time provide useful information for the differential diagnosis of brain tumors.