MRI Extracellular Volume Fraction in Liver Fibrosis-A Comparison of Different Time Points and Blood Pool Measurements.

BACKGROUND: Extracellular volume (ECV) correlates with the degree of liver fibrosis. PURPOSE: To analyze the performance of liver MRI-based ECV evaluations with different blood pool measurements at different time points. STUDY TYPE: Prospective. SAMPLE: 73 consecutive patients (n = 31 females, mean age 56 years) with histopathology-proven liver fibrosis. FIELD STRENGTH/SEQUENCE: 3T acquisition within 90 days of biopsy, including shortened modified look-locker inversion recovery T1 mapping. ASSESSMENT: Polygonal regions of interest were manually drawn in the liver, aorta, vena cava, and in the main, left and right portal vein on four slices before and after Gd-DOTA administration at 5/10/15 minutes. ECV was calculated 1) on one single slice on portal bifurcation level, and 2) averaged over all four slices. STATISTICAL TESTS: Parameters were compared between patients with fibrosis grades F0-2 and F3-F4 with the Mann-Whitney U and fishers exact test. ROC analysis was used to assess the performance of the parameters to predict F3-4 fibrosis. A P-value <0.05 was considered statistically significant. RESULTS: ECV was significantly higher in F3-4 fibrosis (35.4% [33.1%-37.6%], 36.1% [34.2%-37.5%], and 37.0% [34.8%-39.2%] at 5/10/15 minutes) than in patients with F0-2 fibrosis (33.3% [30.8%-34.8%], 33.7% [31.6%-34.7%] and 34.9% [32.2%-36.0%]; AUC = 0.72-0.75). Blood pool T1 relaxation times in the aorta and vena cava were longer on the upper vs. lower slices at 5 minutes, but not at 10/15 minutes. AUC values were similar when measured on a single slice (AUC = 0.69-0.72) or based on blood pool measurements in the cava or portal vein (AUC = 0.63-0.67 and AUC = 0.65-0.70). DATA CONCLUSION: Liver ECV is significantly higher in F3-4 fibrosis compared to F0-2 fibrosis with blood pool measurements performed in the aorta, inferior vena cava, and portal vein at 5, 10, and 15 minutes. However, a smaller variability was observed for blood pool measurements between slices at 15 minutes. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 3.

Multicenter Repeatability and Reproducibility of MR Fingerprinting in Phantoms and in Prostatic Tissue.

PURPOSE: To evaluate multicenter repeatability and reproducibility of T1 and T2 maps generated using MR fingerprinting (MRF) in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom and in prostatic tissues. METHODS: MRF experiments were performed on 5 different 3 Tesla MRI scanners at 3 different institutions: University Hospitals Cleveland Medical Center (Cleveland, OH), Brigham and Women's Hospital (Boston, MA) in the United States, and Diagnosticos da America (Rio de Janeiro, RJ) in Brazil. Raw MRF data were reconstructed using a Gadgetron-based MRF online reconstruction pipeline to yield quantitative T1 and T2 maps. The repeatability of T1 and T2 values over 6 measurements in the International Society for Magnetic Resonance in Medicine/National Institute of Standards and Technology MRI system phantom was assessed to demonstrate intrascanner variation. The reproducibility between the 4 clinical scanners was assessed to demonstrate interscanner variation. The same-day test-retest normal prostate mean T1 and T2 values from peripheral zone and transitional zone were also compared using the intraclass correlation coefficient and Bland-Altman analysis. RESULTS: The intrascanner variation of values measured using MRF was less than 2% for T1 and 4.7% for T2 for relaxation values, within the range of 307.7 to 2360 ms for T1 and 19.1 to 248.5 ms for T2 . Interscanner measurements showed that the T1 variation was less than 4.9%, and T2 variation was less than 8.1% between multicenter scanners. Both T1 and T2 values in in vivo prostatic tissue demonstrated high test-retest reliability (intraclass correlation coefficient > 0.92) and strong linear correlation (R2  > 0.840). CONCLUSION: Prostate MRF measurements of T1 and T2 are repeatable and reproducible between MRI scanners at different centers on different continents for the above measurement ranges.

Diagnostic validation of a deep learning nodule detection algorithm in low-dose chest CT: determination of optimized dose thresholds in a virtual screening scenario.

OBJECTIVES: This study was conducted to evaluate the effect of dose reduction on the performance of a deep learning (DL)-based computer-aided diagnosis (CAD) system regarding pulmonary nodule detection in a virtual screening scenario. METHODS: Sixty-eight anthropomorphic chest phantoms were equipped with 329 nodules (150 ground glass, 179 solid) with four sizes (5 mm, 8 mm, 10 mm, 12 mm) and scanned with nine tube voltage/current combinations. The examinations were analyzed by a commercially available DL-based CAD system. The results were compared by a comparison of proportions. Logistic regression was performed to evaluate the impact of tube voltage, tube current, nodule size, nodule density, and nodule location. RESULTS: The combination with the lowest effective dose (E) and unimpaired detection rate was 80 kV/50 mAs (sensitivity: 97.9%, mean false-positive rate (FPR): 1.9, mean CTDIvol: 1.2 ± 0.4 mGy, mean E: 0.66 mSv). Logistic regression revealed that tube voltage and current had the greatest impact on the detection rate, while nodule size and density had no significant influence. CONCLUSIONS: The optimal tube voltage/current combination proposed in this study (80 kV/50 mAs) is comparable to the proposed combinations in similar studies, which mostly dealt with conventional CAD software. Modification of tube voltage and tube current has a significant impact on the performance of DL-based CAD software in pulmonary nodule detection regardless of their size and composition. KEY POINTS: • Modification of tube voltage and tube current has a significant impact on the performance of deep learning-based CAD software. • Nodule size and composition have no significant impact on the software's performance. • The optimal tube voltage/current combination for the examined software is 80 kV/50 mAs.

Avoiding the Intercostal Arteries in Percutaneous Thoracic Interventions.

The purpose of this study was to define relevant intercostal artery (ICA) anatomy potentially impacting the safety of thoracic percutaneous interventional procedures. An ICA abutting the upper rib and running in the subcostal groove was defined as the lowest risk zone for interventions requiring a supracostal needle puncture. A theoretical high-risk zone was defined by the ICA coursing in the lower half of the intercostal space (ICS), and a theoretical moderate-risk zone was defined by the ICA coursing below the subcostal groove but in the upper half of the ICS. Arterial phase computed tomography data from 250 patients were analyzed, revealing demographic variability, with high-risk zones extending more laterally with advancing age and with more cranial ribs. Overall, within the 97.5th percentile, an ICS puncture >7-cm lateral to the spinous process incurs moderate risk and >10-cm lateral incurs the lowest risk.

Knee Diameter and Cross-Sectional Area as Biomarkers for Cartilage Knee Degeneration on Magnetic Resonance Images.

Background and Objectives: Osteoarthritis (OA) of the knee is a degenerative disorder characterized by damage to the joint cartilage, pain, swelling, and walking disability. The purpose of this study was to assess whether demographic and radiologic parameters (knee diameters and knee cross-sectional area from magnetic resonance (MR) images) could be used as surrogate biomarkers for the prediction of OA. Materials and Methods: The knee diameters and cross-sectional areas of 481 patients were measured on knee MR images, and the corresponding demographic parameters were extracted from the patients' clinical records. The images were graded based on the modified Outerbridge arthroscopic classification that was used as ground truth. Receiver-operating characteristic (ROC) analysis was performed on the collected data. Results: ROC analysis established that age was the most accurate predictor of severe knee cartilage degeneration (corresponding to Outerbridge grades 3 and 4) with an area under the curve (AUC) of the specificity-sensitivity plot of 0.865 ± 0.02. An age over 41 years was associated with a sensitivity and specificity for severe degeneration of 82.8% (CI: 77.5-87.3%), and 76.4% (CI: 70.4-81.6%), respectively. The second-best degeneration predictor was the normalized knee cross-sectional area, with an AUC of 0.767 ± 0.04), followed by BMI (AUC = 0.739 ± 0.02), and normalized knee maximal diameter (AUC = 0.724 ± 0.05), meaning that knee degeneration increases with increasing knee diameter. Conclusions: Age is the best predictor of knee damage progression in OA and can be used as surrogate marker for knee degeneration. Knee diameters and cross-sectional area also correlate with the extent of cartilage lesions. Though less-accurate predictors of damage progression than age, they have predictive value and are therefore easily available surrogate markers of OA that can be used also by general practitioners and orthopedic surgeons.

T1 mapping of the liver and the spleen in patients with liver fibrosis-does normalization to the blood pool increase the predictive value?

PURPOSE: To analyze whether the T1 relaxation time of the liver is a good predictor of significant liver fibrosis and whether normalization to the blood pool improves the predictive value. METHODS: This prospective study was conducted between 03/2016 and 02/2018. One hundred seventy-three patients underwent multiparametric liver MRI at 3 T. The T1 relaxation time was measured in the liver and the spleen, in the aorta, the portal vein, and the inferior vena cava (IVC). T1 relaxation times with and without normalization to the blood pool were compared between patients with (n = 26) and without (n = 141) significant liver fibrosis, based on a cutoff value of 3.5 kPa in MRE as the noninvasive reference standard. For statistics, Student's t test, receiver operating characteristic (ROC) curve analysis, and Pearson's correlation were used. RESULTS: The T1 relaxation time of the liver was significantly longer in patients with liver fibrosis, both with and without blood pool normalization (p < 0.001). T1 relaxation time of the liver allowed prediction of significant liver fibrosis (AUC = 0.88), while normalization to the IVC resulted in a slightly lower performance (AUC = 0.82). The lowest performance was achieved when the T1 relaxation times of the liver were normalized to the aorta (AUC = 0.66) and to the portal vein (AUC = 0.62). The T1 relaxation time of the spleen detected significant liver fibrosis with an AUC of 0.68, and 0.51-0.64 with normalization to the blood pool. CONCLUSION: The T1 relaxation time of the liver is a good predictor of significant liver fibrosis. However, normalization of the blood pool did not improve the predictive value. KEY POINTS: • The T1 relaxation time of the liver is a good predictor of significant liver fibrosis. • Normalization to the blood pool did not improve the predictive value of T1 mapping. • If the blood pool normalization was weighted 30% to the aorta and 70% to the portal vein, the performance was better than normalization to the aorta alone but still lower than normalization to the IVC.

Radial self-navigated native magnetic resonance angiography in comparison to navigator-gated contrast-enhanced MRA of the entire thoracic aorta in an aortic patient collective.

BACKGROUND: The native balanced steady state with free precession (bSSFP) magnetic resonance angiography (MRA) technique has been shown to provide high diagnostic image quality for thoracic aortic disease. This study compares a 3D radial respiratory self-navigated native MRA (native-SN-MRA) based on a bSSFP sequence with conventional Cartesian, 3D, contrast-enhanced MRA (CE-MRA) with navigator-gated respiration control for image quality of the entire thoracic aorta. METHODS: Thirty-one aortic native-SN-MRA were compared retrospectively (63.9 ± 10.3 years) to 61 CE-MRA (63.1 ± 11.7 years) serving as a reference standard. Image quality was evaluated at the aortic root/ascending aorta, aortic arch and descending aorta. Scan time was recorded. In 10 patients with both MRA sequences, aortic pathologies were evaluated and normal and pathologic aortic diameters were measured. The influence of artifacts on image quality was analyzed. RESULTS: Compared to the overall image quality of CE-MRA, the overall image quality of native-SN-MRA was superior for all segments analyzed (aortic root/ascending, p < 0.001; arch, p < 0.001, and descending, p = 0.005). Regarding artifacts, the image quality of native-SN-MRA remained superior at the aortic root/ascending aorta and aortic arch before and after correction for confounders of surgical material (i.e., susceptibility-related artifacts) (p = 0.008 both) suggesting a benefit in terms of motion artifacts. Native-SN-MRA showed a trend towards superior intraindividual image quality, but without statistical significance. Intraindividually, the sensitivity and specificity for the detection of aortic disease were 100% for native-SN-MRA. Aortic diameters did not show a significant difference (p = 0.899). The scan time of the native-SN-MRA was significantly reduced, with a mean of 05:56 ± 01:32 min vs. 08:51 ± 02:57 min in the CE-MRA (p < 0.001). CONCLUSIONS: Superior image quality of the entire thoracic aorta, also regarding artifacts, can be achieved with native-SN-MRA, especially in motion prone segments, in addition to a shorter acquisition time.

Diagnostic Yield of Incremental Biopsy Cores and Second Lesion Sampling for In-Gantry MRI-Guided Prostate Biopsy.

BACKGROUND. In-gantry MRI-guided biopsy (MRGB) of the prostate has been shown to be more accurate than other targeted prostate biopsy methods. However, the optimal number of cores to obtain during in-gantry MRGB remains undetermined. OBJECTIVE. The purpose of this study was to assess the diagnostic yield of obtaining an incremental number of cores from the primary lesion and of second lesion sampling during in-gantry MRGB of the prostate. METHODS. This retrospective study included 128 men with 163 prostate lesions who underwent in-gantry MRGB between 2016 and 2019. The men had a total of 163 lesions sampled with two or more cores, 121 lesions sampled with three or more cores, and 52 lesions sampled with four or more cores. A total of 40 men underwent sampling of a second lesion. Upgrade on a given core was defined as a greater International Society of Urological Pathology (ISUP) grade group (GG) relative to the previously obtained cores. Clinically significant prostate cancer (csPCa) was defined as ISUP GG 2 or greater. RESULTS. The frequency of any upgrade was 12.9% (21/163) on core 2 versus 10.7% (13/121) on core 3 (p = .29 relative to core 2) and 1.9% (1/52) on core 4 (p = .03 relative to core 3). The frequency of upgrade to csPCa was 7.4% (12/163) on core 2 versus 4.1% (5/121) on core 3 (p = .13 relative to core 2) and 0% (0/52) on core 4 (p = .07 relative to core 3). The frequency of upgrade on core 2 was higher for anterior lesions (p < .001) and lesions with a higher PI-RADS score (p = .007); the frequency of upgrade on core 3 was higher for apical lesions (p = .01) and lesions with a higher PI-RADS score (p = .01). Sampling of a second lesion resulted in an upgrade in a single patient (2.5%; 1/40); both lesions were PI-RADS category 4 and showed csPCa. CONCLUSION. When performing in-gantry MRGB of the prostate, obtaining three cores from the primary lesion is warranted to optimize csPCa diagnosis. Obtaining a fourth core from the primary lesion or sampling a second lesion has very low yield in upgrading cancer diagnoses. CLINICAL IMPACT. To reduce patient discomfort and procedure times, operators may refrain from obtaining more than three cores or second lesion sampling.

Identification of ureteral stones at reduced radiation exposure: a pilot study comparing conventional versus digital low-dosage linear slot scanning (Lodox®) radiography.

PURPOSE: Digital low-dosage, linear slot scanning radiography (Lodox®) is an imaging modality that can emit down to one-tenth the radiation of conventional X-ray systems. We prospectively evaluated Lodox® as a diagnostic imaging modality in patients with ureterolithiasis. METHODS: Conventional kidney-ureter-bladder (KUB) X-ray and Lodox® were performed in 41 patients presenting with acute flank pain due to unilateral ureteral stone confirmed by computed tomography. KUB X-ray and Lodox® images were then reviewed by four blinded readers (urology expert/resident, radiology expert/resident). Identification rates were compared using Pearson's Chi square test. The impact of different parameters on stone identification by Lodox® was evaluated using logistic regression and generalized linear mixed models. Inter-reader agreement was tested using Cohen's kappa coefficient. RESULTS: Median stone size was 5 mm (range 2-12), median stone density was 800 HU (range 200-1500). The identification rates of the urology expert were 68% for KUB X-ray and 90% for Lodox® (p = 0.014), and for all four readers 61% for KUB X-ray and 62% for Lodox® (p = 0.8). Radiation exposure for KUB X-ray and Lodox® was 0.45 mSv (SD ± 0.64) and 0.027 mSv (SD ± 0.038), respectively. Multivariable analyses showed an association between stone identification by Lodox® and stone size (p < 0.001), stone density (p = 0.005), lower body mass index (p = 0.005), and reader (p < 0.001). CONCLUSIONS: The high identification rates and low radiation doses of Lodox® make it a promising imaging modality for the diagnosis of ureteral stones. Further validation in larger cohorts, including performance evaluation for renal stones, is warranted. TRIAL REGISTRATION: http://www.controlled-trails.com/ISRCTN12915426.

Virtual non-contrast for evaluation of liver parenchyma and vessels: results from 25 patients using multi-phase spectral-detector CT.

BACKGROUND: In abdominal imaging, contrast-enhanced computed tomography (CT) examinations are most commonly applied; however, unenhanced examinations are still needed for several clinical questions but require additional scanning and radiation exposure. PURPOSE: To evaluate accuracy of virtual non-contrast (VNC) from arterial and venous phase spectral-detector CT (SDCT) scans compared to true-unenhanced (TNC) images for the evaluation of liver parenchyma and vessels. MATERIAL AND METHODS: A total of 25 patients undergoing triphasic SDCT examinations were included. VNC was reconstructed from arterial and venous phases and compared to TNC images. Quantitative image analysis was performed by region of interest (ROI)-based assessment of mean and SD of attenuation (HU) in each liver segment, spleen, portal vein, common hepatic artery, and abdominal aorta. Subjectively, iodine subtraction and diagnostic assessment were rated on 5-point Likert scales. RESULTS: Attenuation and image noise measured in the liver from VNC were not significantly different from TNC (TNC: 54.6 ± 10.8 HU, VNC arterial phase: 55.7 ± 10.8 HU; VNC venous phase: 58.3 ± 10.0 HU; P > 0.05). VNC also showed accurate results regarding attenuation and image noise for spleen, portal vein, and abdominal aorta. Only iodine subtraction in the common hepatic artery in the arterial phase was insufficient which was confirmed by the subjective reading. Apart from that, subjective reading showed accurate iodine subtraction and comparable diagnostic assessment. CONCLUSION: VNC from the arterial and venous phases were very similar to TNC yielding mostly negligible differences in attenuation, image noise, and diagnostic utility. Inadequate iodine subtraction occurred in hepatic arteries in the arterial phase.

MR Fingerprinting and ADC Mapping for Characterization of Lesions in the Transition Zone of the Prostate Gland.

BackgroundPreliminary studies have shown that MR fingerprinting-based relaxometry combined with apparent diffusion coefficient (ADC) mapping can be used to differentiate normal peripheral zone from prostate cancer and prostatitis. The utility of relaxometry and ADC mapping for the transition zone (TZ) is unknown.PurposeTo evaluate the utility of MR fingerprinting combined with ADC mapping for characterizing TZ lesions.Materials and MethodsTZ lesions that were suspicious for cancer in men who underwent MRI with T2-weighted imaging and ADC mapping (b values, 50-1400 sec/mm2), MR fingerprinting with steady-state free precession, and targeted biopsy (60 in-gantry and 15 cognitive targeting) between September 2014 and August 2018 in a single university hospital were retrospectively analyzed. Two radiologists blinded to Prostate Imaging Reporting and Data System (PI-RADS) scores and pathologic diagnosis drew regions of interest on cancer-suspicious lesions and contralateral visually normal TZs (NTZs) on MR fingerprinting and ADC maps. Linear mixed models compared two-reader means of T1, T2, and ADC. Generalized estimating equations logistic regression analysis was used to evaluate both MR fingerprinting and ADC in differentiating NTZ, cancers and noncancers, clinically significant (Gleason score ≥ 7) cancers from clinically insignificant lesions (noncancers and Gleason 6 cancers), and characterizing PI-RADS version 2 category 3 lesions.ResultsIn 67 men (mean age, 66 years ± 8 [standard deviation]) with 75 lesions, targeted biopsy revealed 37 cancers (six PI-RADS category 3 cancers and 31 PI-RADS category 4 or 5 cancers) and 38 noncancers (31 PI-RADS category 3 lesions and seven PI-RADS category 4 or 5 lesions). The T1, T2, and ADC of NTZ (1800 msec ± 150, 65 msec ± 22, and [1.13 ± 0.19] × 10-3 mm2/sec, respectively) were higher than those in cancers (1450 msec ± 110, 36 msec ± 11, and [0.57 ± 0.13] × 10-3 mm2/sec, respectively; P < .001 for all). The T1, T2, and ADC in cancers were lower than those in noncancers (1620 msec ± 120, 47 msec ± 16, and [0.82 ± 0.13] × 10-3 mm2/sec, respectively; P = .001 for T1 and ADC and P = .03 for T2). The area under the receiver operating characteristic curve (AUC) for T1 plus ADC was 0.94 for separation. T1 and ADC in clinically significant cancers (1440 msec ± 140 and [0.58 ± 0.14] × 10-3 mm2/sec, respectively) were lower than those in clinically insignificant lesions (1580 msec ± 120 and [0.75 ± 0.17] × 10-3 mm2/sec, respectively; P = .001 for all). The AUC for T1 plus ADC was 0.81 for separation. Within PI-RADS category 3 lesions, T1 and ADC of cancers (1430 msec ± 220 and [0.60 ± 0.17] × 10-3 mm2/sec, respectively) were lower than those of noncancers (1630 msec ± 120 and [0.81 ± 0.13] × 10-3 mm2/sec, respectively; P = .006 for T1 and P = .004 for ADC). The AUC for T1 was 0.79 for differentiating category 3 lesions.ConclusionMR fingerprinting-based relaxometry combined with apparent diffusion coefficient mapping may improve transition zone lesion characterization.© RSNA, 2019Online supplemental material is available for this article.

Virtual Monoenergetic Images for Diagnostic Assessment of Hypodense Lesions Within the Liver: Semiautomatic Estimation of Window Settings Using Linear Models.

OBJECTIVE: The aim of the study was to establish the reference window settings for display of virtual monoenergetic images (VMIs) from spectral detector computed tomography when assessing hypodense liver lesions. METHODS: In patients with cysts (n = 24) or metastases (n = 26), objective (HU, signal-to-noise ratio [SNR]) and subjective (overall image quality, lesion conspicuity and noise) were assessed. Furthermore, 2 readers determined optimal window center/width (C/W) for conventional images (CIs) and VMIs of 40 to 120 keV. Center/width were modeled against HUliv with and without respect to the keV level (models A and B). RESULTS: Attenuation and SNR were significantly higher in low-keV VMIs and improved overall image quality and lesion conspicuity (P ≤ 0.05). Model B provided valid estimations of C/W, whereas model A was slightly less accurate. CONCLUSIONS: The increase in attenuation and SNR on low-keV VMIs requires adjustment of C/W, and they can be estimated in dependency of HUliv using linear models. Reference values for standard display of VMIs of 40 to 120 keV are reported.

Bone subtraction radiography in adult patients with cystic fibrosis.

Background Bone subtraction radiography allows reading pulmonary changes of chest radiographs more accurately without superimposition of bones. Purpose To evaluate the value of bone subtraction chest radiography using dual energy (DE) bone subtracted lung images compared to conventional radiographs (CR) in adult patients with cystic fibrosis (CF). Material and Methods Forty-nine DE radiographs of 24 patients (16 men) with CF (mean age, 32 years; age range, 18-71 years) were included. Lung function tests were performed within 10 days of the radiographs. Two radiologists evaluated all CR, DE, and CR + DE radiographs using the modified Chrispin-Norman score (CNS) and a five-point score for the confidence. Findings were statistically evaluated by Friedman ANOVA and Wilcoxon matched-pairs test. Results There was significant difference of CNS between CR and DE ( P = 0.044) as well as CR and CR + DE ( P < 0.001). CNS of CR images showed moderate correlation with FEV1% (R = 0.287, P = 0.046) while DE and CR + DE correlated poorly with FEV1% (R = 0.023, P = 0.874 and R = 0.04, P = 0.785). A higher confidence was achieved with bone-subtracted radiographs compared to radiographs alone (median, CR 3.3, DE 3.9, CR + DE 4.1, for both P < 0.001). Conclusion DE radiographs are reliable for the evaluation of adult patients with CF in acute exacerbation. For yearly surveillance, CR and DE radiographs may play a limited role. However, in clinical routine, DE radiographs are useful for adult CF patients and may depict more accurately inflammatory changes than CR.

Maximum-Intensity-Projection and Computer-Aided-Detection Algorithms as Stand-Alone Reader Devices in Lung Cancer Screening Using Different Dose Levels and Reconstruction Kernels.

OBJECTIVE: The objective of our study was to evaluate lung nodule detection rates on standard and microdose chest CT with two different computer-aided detection systems (SyngoCT-CAD, VA 20, Siemens Healthcare [CAD1]; Lung CAD, IntelliSpace Portal DX Server, Philips Healthcare [CAD2]) as well as maximum-intensity-projection (MIP) images. We also assessed the impact of different reconstruction kernels. MATERIALS AND METHODS: Standard and microdose CT using three reconstruction kernels (i30, i50, i70) was performed with an anthropomorphic chest phantom. We placed 133 ground-glass and 133 solid nodules (diameters of 5 mm, 8 mm, 10 mm, and 12 mm) in 55 phantoms. Four blinded readers evaluated the MIP images; one recorded the results of CAD1 and CAD2. Sensitivities for CAD and MIP nodule detection on standard dose and microdose CT were calculated for each reconstruction kernel. RESULTS: Dose for microdose CT was significantly less than that for standard-dose CT (0.1323 mSv vs 1.65 mSv; p < 0.0001). CAD1 delivered superior results compared with CAD2 for standard-dose and microdose CT (p < 0.0001). At microdose level, the best stand-alone sensitivity (97.6%) was comparable with CAD1 sensitivity (96.0%; p = 0.36; both with i30 reconstruction kernel). Pooled sensitivities for all nodules, doses, and reconstruction kernels on CAD1 ranged from 88.9% to 97.3% versus 49.6% to 73.9% for CAD2. The best sensitivity was achieved with standard-dose CT, i50 kernel, and CAD1 (97.3%) versus 96% with microdose CT, i30 or i50 kernel, and CAD1. MIP images and CAD1 had similar performance at both dose levels (p = 0.1313 and p = 0.48). CONCLUSION: Submillisievert CT is feasible for detecting solid and ground-glass nodules that require soft-tissue kernels for MIP and CAD systems to achieve acceptable sensitivities. MIP reconstructions remain a valuable adjunct to the interpretation of chest CT for increasing sensitivity and have the advantage of significantly lower false-positive rates.

Ovarian and uterine development and hormonal feedback mechanism in a 46 XX patient with CYP19A1 deficiency under low dose estrogen replacement.

BACKGROUND: Aromatase deficiency may result in a complete block of estrogen synthesis because of the failure to convert androgens to estrogens. In females, this results in virilisation at birth, ovarian cysts in prepuberty and lack of pubertal development but virilisation, thereafter. OBJECTIVE AND METHODS: We studied the impact of oral 17ß-estradiol treatment on ovarian and uterine development, and on LH/FSH and inhibin B during the long-term follow-up of a girl harboring compound heterozygote point mutations in the CYP19A1 gene. RESULTS: In early childhood, low doses of oral 17ß-estradiol were needed. During prepuberty treatment with slowly increasing doses of E2 resulted in normal uterine and almost normal development of ovarian volume, as well as number and size of follicles. Regarding hormonal feedback mechanisms, inhibin B levels were in the upper normal range during childhood and puberty. Low doses of estradiol did not suffice to achieve physiological gonadotropin levels in late prepuberty and puberty. However, when estradiol doses were further increased in late puberty levels of both FSH and LH declined with estradiol levels within normal range. CONCLUSION: Complete aromatase deficiency provides an excellent model of how ovarian and uterine development in relation to E2, LH, FSH and inhibin B feedback progresses from infancy to adolescence.

MSCs mediate long-term efficacy in a Crohn's disease model by sustained anti-inflammatory macrophage programming via efferocytosis.

Mesenchymal stem cells (MSCs) are novel therapeutics for the treatment of Crohn's disease. However, their mechanism of action is unclear, especially in disease-relevant chronic models of inflammation. Thus, we used SAMP-1/YitFc (SAMP), a chronic and spontaneous murine model of small intestinal inflammation, to study the therapeutic effects and mechanism of action of human bone marrow-derived MSCs (hMSC). hMSC dose-dependently inhibited naïve T lymphocyte proliferation via prostaglandin E2 (PGE2) secretion and reprogrammed macrophages to an anti-inflammatory phenotype. We found that the hMSCs promoted mucosal healing and immunologic response early after administration in SAMP when live hMSCs are present (until day 9) and resulted in a complete response characterized by mucosal, histological, immunologic, and radiological healing by day 28 when no live hMSCs are present. hMSCs mediate their effect via modulation of T cells and macrophages in the mesentery and mesenteric lymph nodes (mLN). Sc-RNAseq confirmed the anti-inflammatory phenotype of macrophages and identified macrophage efferocytosis of apoptotic hMSCs as a mechanism that explains their long-term efficacy. Taken together, our findings show that hMSCs result in healing and tissue regeneration in a chronic model of small intestinal inflammation and despite being short-lived, exert long-term effects via sustained anti-inflammatory programming of macrophages via efferocytosis.

Automated liver segmental volume ratio quantification on non-contrast T1-Vibe Dixon liver MRI using deep learning.

PURPOSE: To evaluate the effectiveness of automated liver segmental volume quantification and calculation of the liver segmental volume ratio (LSVR) on a non-contrast T1-vibe Dixon liver MRI sequence using a deep learning segmentation pipeline. METHOD: A dataset of 200 liver MRI with a non-contrast 3 mm T1-vibe Dixon sequence was manually labeledslice-by-sliceby an expert for Couinaud liver segments, while portal and hepatic veins were labeled separately. A convolutional neural networkwas trainedusing 170 liver MRI for training and 30 for evaluation. Liver segmental volumes without liver vessels were retrieved and LSVR was calculated as the liver segmental volumes I-III divided by the liver segmental volumes IV-VIII. LSVR was compared with the expert manual LSVR calculation and the LSVR calculated on CT scans in 30 patients with CT and MRI within 6 months. RESULTS: Theconvolutional neural networkclassified the Couinaud segments I-VIII with an average Dice score of 0.770 ± 0.03, ranging between 0.726 ± 0.13 (segment IVb) and 0.810 ± 0.09 (segment V). The calculated mean LSVR with liver MRI unseen by the model was 0.32 ± 0.14, as compared with manually quantified LSVR of 0.33 ± 0.15, resulting in a mean absolute error (MAE) of 0.02. A comparable LSVR of 0.35 ± 0.14 with a MAE of 0.04 resulted with the LSRV retrieved from the CT scans. The automated LSVR showed significant correlation with the manual MRI LSVR (Spearman r = 0.97, p < 0.001) and CT LSVR (Spearman r = 0.95, p < 0.001). CONCLUSIONS: A convolutional neural network allowed for accurate automated liver segmental volume quantification and calculation of LSVR based on a non-contrast T1-vibe Dixon sequence.