Dynamic Brain Imaging Response to Spinal Cord Stimulation Differential Frequencies DiFY SCS-PET Clinical Trial.

OBJECTIVES: This study with sequential 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography (PET)-computed tomography (CT) scanning was designed to investigate any objective measurable effect of differential frequency stimulation (40 Hz, 4000 Hz, and 10,000 Hz) on specific pain matrix areas in patients who underwent spinal cord stimulation (SCS) for intractable lumbar neuropathic pain. MATERIALS AND METHODS: In this single-center, randomized, blinded study, four brain 18F-FDG PET scans were performed for each patient-at baseline before SCS implant and after 40-Hz, 4000-Hz, and 10,000-Hz stimulation. After 40-Hz stimulation for four weeks, patients were randomized 1:1 (4000 Hz/10,000 Hz), crossing over at another four weeks. 18F-FDG PET-CT brain scans acquired on the GE-Discovery 710 PET system (GE Healthcare, Chicago, IL) with 128-slice CT (250-MBq dose) were analyzed using the PMOD software (PMOD Technologies Ltd, Zurich, Switzerland). A total of 18 pain regions, the right and left prefrontal cortex (PFC), insula, anterior cingulate cortex (ACC), hippocampus, amygdala, primary somatosensory cortices, secondary somatosensory cortices (SSCII), thalami, parabrachial, and periaqueductal gray (PAG), were analyzed. RESULTS: A total of 14 patients received 40 Hz for four weeks before crossing over to 10,000 Hz/4000 Hz. A total of 57 PET-CT scans (15 for baseline and 14 each for 40 Hz, 4000 Hz, and 10,000 Hz) were analyzed for maximum standardized uptake value (SUVmax), with a statistically significant difference in SUVmax between 40 Hz and baseline (p = 0.002) and 4000 Hz and baseline (p = 0.001) when pooled across 18 pain matrices. There was no statistical difference in SUVmax between 10,000 Hz and baseline. The pooled analysis showed a proportionately higher thalamic region reduction (59.5%) in metabolic activity than other pain matrices, PFC (52%), insula (50%), ACC (52%), SSCII (49%), and PAG (52%). CONCLUSION: This large cohort of brain PET scans (n = 57) shows statistically significant differences in brain metabolic activity at 40 Hz and 4000 Hz from baseline, with effect on both nociceptive and affect-cognitive pathways (proportionately higher reduction in the thalamus), highlighting the possible mechanism of SCS. CLINICAL TRIAL REGISTRATION: The Clinicaltrials.gov registration number for the study is NCT03716557.

Response prediction of neoadjuvant chemoradiation therapy in locally advanced rectal cancer using CT-based fractal dimension analysis.

OBJECTIVES: There are individual variations in neo-adjuvant chemoradiation therapy (nCRT) in patients with locally advanced rectal cancer (LARC). No reliable modality currently exists that can predict the efficacy of nCRT. The purpose of this study is to assess if CT-based fractal dimension and filtration-histogram texture analysis can predict therapeutic response to nCRT in patients with LARC. METHODS: In this retrospective study, 215 patients (average age: 57 years (18-87 years)) who received nCRT for LARC between June 2005 and December 2016 and underwent a staging diagnostic portal venous phase CT were identified. The patients were randomly divided into two datasets: a training set (n = 170), and a validation set (n = 45). Tumor heterogeneity was assessed on the CT images using fractal dimension (FD) and filtration-histogram texture analysis. In the training set, the patients with pCR and non-pCR were compared in univariate analysis. Logistic regression analysis was applied to identify the predictive value of efficacy of nCRT and receiver operating characteristic analysis determined optimal cutoff value. Subsequently, the most significant parameter was assessed in the validation set. RESULTS: Out of the 215 patients evaluated, pCR was reached in 20.9% (n = 45/215) patients. In the training set, 7 out of 37 texture parameters showed significant difference comparing between the pCR and non-pCR groups and logistic multivariable regression analysis incorporating clinical and 7 texture parameters showed that only FD was associated with pCR (p = 0.001). The area under the curve of FD was 0.76. In the validation set, we applied FD for predicting pCR and sensitivity, specificity, and accuracy were 60%, 89%, and 82%, respectively. CONCLUSION: FD on pretreatment CT is a promising parameter for predicting pCR to nCRT in patients with LARC and could be used to help make treatment decisions. KEY POINTS: • Fractal dimension analysis on pretreatment CT was associated with response to neo-adjuvant chemoradiation in patients with locally advanced rectal cancer. • Fractal dimension is a promising biomarker for predicting pCR to nCRT and may potentially select patients for individualized therapy.

Effectiveness of high dose spinal cord stimulation for non-surgical intractable lumbar radiculopathy - HIDENS Study.

OBJECTIVES: Spinal cord stimulation (SCS) is being increasingly used in non-surgical intractable low back pain. This study was designed to evaluate the efficacy of high-dose (HD) SCS utilizing sub-perception stimulation with higher frequency and pulse width in non-surgical predominant low-back pain population at 12 months. MATERIALS AND METHODS: A total of 20 patients were recruited (280 screened between March 2017 and July 2018) to undergo percutaneous fluoroscopic-guided SCS (Medtronic 8 contact standard leads and RestoreR IPG), with T8 and T9 midline anatomical parallel placement. Sixteen patients completed 12 months follow-up (500 Hz frequency, 500 µs pulse width, and 25% pulse density). Differences in patients' clinical outcome (NRS back, NRS leg, ODI, PGIC, and PSQ) and medication usage (MQS) at 1, 3, and 12 months from the baseline were assessed using non-parametric Wilcoxon paired test. RESULTS: The mean NRS scores for back pain (baseline 7.53) improved significantly at 1, 3, and 12 months; 2.78 (p < 0.001), 4.45 (p = 0.002), and 3.85 (p = 0.002), respectively. The mean NRS score for leg pain (baseline 6.09) improved significantly at 1 and 3 months; 1.86 (p < 0.001) and 3.13 (p = 0.010), respectively. Mean NRS for leg pain at 12 months was 3.85 (p = 0.057). ODI and sleep demonstrated significant improvement as there was consistent improvement in medication particularly opioid usage (MQS) at 12 months. CONCLUSIONS: This study demonstrates that anatomical placement of leads with sub-perception HD stimulation could provide effective pain relief in patients who are not candidates for spinal surgery.

FDG-PET/CT in colorectal cancer: potential for vascular-metabolic imaging to provide markers of prognosis.

PURPOSE: This study assesses the potential for vascular-metabolic imaging with FluoroDeoxyGlucose (FDG)-Positron Emission Tomography/Computed Tomography (PET/CT) perfusion to provide markers of prognosis specific to the site and stage of colorectal cancer. METHODS: This prospective observational study comprised of participants with suspected colorectal cancer categorized as either (a) non-metastatic colon cancer (M0colon), (b) non-metastatic rectal cancer (M0rectum), or (c) metastatic colorectal cancer (M+). Combined FDG-PET/CT perfusion imaging was successfully performed in 286 participants (184 males, 102 females, age: 69.60 ± 10 years) deriving vascular and metabolic imaging parameters. Vascular and metabolic imaging parameters alone and in combination were investigated with respect to overall survival. RESULTS: A vascular-metabolic signature that was significantly associated with poorer survival was identified for each patient group: M0colon - high Total Lesion Glycolysis (TLG) with increased Permeability Surface Area Product/Blood Flow (PS/BF), Hazard Ratio (HR) 3.472 (95% CI: 1.441-8.333), p = 0.006; M0rectum - high Metabolic Tumour Volume (MTV) with increased PS/BF, HR 4.567 (95% CI: 1.901-10.970), p = 0.001; M+ participants, high MTV with longer Time To Peak (TTP) enhancement, HR 2.421 (95% CI: 1.162-5.045), p = 0.018. In participants with stage 2 colon cancer as well as those with stage 3 rectal cancer, the vascular-metabolic signature could stratify the prognosis of these participants. CONCLUSION: Vascular and metabolic imaging using FDG-PET/CT can be used to synergise prognostic markers. The hazard ratios suggest that the technique may have clinical utility.

CT texture-based radiomics analysis of carotid arteries identifies vulnerable patients: a preliminary outcome study.

PURPOSE: To assess the potential role of computed tomography (CT) texture analysis (CTTA) in identifying vulnerable patients with carotid artery atherosclerosis. METHODS: In this case-control pilot study, 12 patients with carotid atherosclerosis and a subsequent history of transient ischemic attack or stroke were age and sex matched with 12 control cases with asymptomatic carotid atherosclerosis (follow-up time 103.58 ± 9.2 months). CTTA was performed using a commercially available research software package (TexRAD) by an operator blinded to clinical data. CTTA comprised a filtration-histogram technique to extract features at different scales corresponding to spatial scale filter (fine = 2 mm, medium = 3 mm, coarse = 4 mm), followed by quantification using histogram-based statistical parameters: mean, kurtosis, skewness, entropy, standard deviation, and mean value of positive pixels. A single axial slice was selected to best represent the largest cross-section of the carotid bifurcation or the greatest degree of stenosis, in presence of an atherosclerotic plaque, on each side. RESULTS: CTTA revealed a statistically significant difference in skewness between symptomatic and asymptomatic patients at the medium (0.22 ± 0.35 vs - 0.18 ± 0.39, p < 0.001) and coarse (0.23 ± 0.22 vs 0.03 ± 0.29, p = 0.003) texture scales. At the fine-texture scale, skewness (0.20 ± 0.59 vs - 0.18 ± 0.58, p = 0.009) and standard deviation (366.11 ± 117.19 vs 300.37 ± 82.51, p = 0.03) were significant before correction. CONCLUSION: Our pilot study highlights the potential of CTTA to identify vulnerable patients in stroke and TIA. CT texture may have the potential to act as a novel risk stratification tool in patients with carotid atherosclerosis.

Chest CT texture-based radiomics analysis in differentiating COVID-19 from other interstitial pneumonia.

PURPOSE: To evaluate the potential role of texture-based radiomics analysis in differentiating Coronavirus Disease-19 (COVID-19) pneumonia from pneumonia of other etiology on Chest CT. MATERIALS AND METHODS: One hundred and twenty consecutive patients admitted to Emergency Department, from March 8, 2020, to April 25, 2020, with suspicious of COVID-19 that underwent Chest CT, were retrospectively analyzed. All patients presented CT findings indicative for interstitial pneumonia. Sixty patients with positive COVID-19 real-time reverse transcription polymerase chain reaction (RT-PCR) and 60 patients with negative COVID-19 RT-PCR were enrolled. CT texture analysis (CTTA) was manually performed using dedicated software by two radiologists in consensus and textural features on filtered and unfiltered images were extracted as follows: mean intensity, standard deviation (SD), entropy, mean of positive pixels (MPP), skewness, and kurtosis. Nonparametric Mann-Whitney test assessed CTTA ability to differentiate positive from negative COVID-19 patients. Diagnostic criteria were obtained from receiver operating characteristic (ROC) curves. RESULTS: Unfiltered CTTA showed lower values of mean intensity, MPP, and kurtosis in COVID-19 positive patients compared to negative patients (p = 0.041, 0.004, and 0.002, respectively). On filtered images, fine and medium texture scales were significant differentiators; fine texture scale being most significant where COVID-19 positive patients had lower SD (p = 0.004) and MPP (p = 0.004) compared to COVID-19 negative patients. A combination of the significant texture features could identify the patients with positive COVID-19 from negative COVID-19 with a sensitivity of 60% and specificity of 80% (p = 0.001). CONCLUSIONS: Preliminary evaluation suggests potential role of CTTA in distinguishing COVID-19 pneumonia from other interstitial pneumonia on Chest CT.

Predicting outcome in childhood diffuse midline gliomas using magnetic resonance imaging based texture analysis.

BACKGROUND: Diffuse midline gliomas (DMG) are aggressive brain tumours, previously known as diffuse intrinsic pontine gliomas (DIPG), with 10% overall survival (OS) at 18 months. Predicting OS will help refine treatment strategy in this patient group. MRI based texture analysis (MRTA) is novel image analysis technique that provides objective information about spatial arrangement of MRI signal intensity (heterogeneity) and has potential to be imaging biomarker. OBJECTIVES: To investigate MRTA in predicting OS in childhood DMG. METHODS: Retrospective study of patients diagnosed with DMG, based on radiological features, treated at our institution 2007-2017. MRIs were acquired at diagnosis and 6 weeks after radiotherapy (54Gy in 30 fractions). MRTA was performed using commercial available TexRAD research software on T2W sequence and Apparent Diffusion Coefficient (ADC) maps encapsulating tumour in the largest single axial plane. MRTA comprised filtration-histogram technique using statistical and histogram metrics for quantification of texture. Kaplan-Meier survival analysis determined association of MRI texture parameters with OS. RESULTS: In all, 32 children 2-14 years (median 7 years) were included. MRTA was undertaken on T2W (n=32) and ADC (n=22). T2W-MRTA parameters were better at prognosticating than ADC-MRTA. Children with homogenous tumour texture, at medium scale on diagnostic T2W MRI, had worse prognosis (Mean of Positive Pixels (MPP): P=0.005, mean: P=0.009, SD: P=0.011, kurtosis: P=0.037, entropy: P=0.042). Best predictor MPP was able to stratify patients into poor and good prognostic groups with median survival of 7.5 months versus 17.5 months, respectively. CONCLUSIONS: DMG with more homogeneous texture on diagnostic MRI is associated with worse prognosis. Texture parameter MPP is the most predictive marker of OS in childhood DMG.

High mean entropy calculated from cardiac MRI texture analysis is associated with antitachycardia pacing failure.

BACKGROUND: Antitachycardia pacing (ATP), which may avoid unnecessary implantable cardioverter-defibrillator (ICD) shocks, does not always terminate ventricular arrhythmias (VAs). Mean entropy calculated using cardiac magnetic resonance texture analysis (CMR-TA) has been shown to predict appropriate ICD therapy. We examined whether scar heterogeneity, quantified by mean entropy, is associated with ATP failure and explore potential mechanisms using computer modeling. METHODS: A subanalysis of 114 patients undergoing CMR-TA where the primary endpoint was delivery of appropriate ICD therapy (ATP or shock therapy) was performed. Patients receiving appropriate ICD therapy (n = 33) were dichotomized into "successful ATP" versus "shock therapy" groups. In silico computer modeling was used to explore underlying mechanisms. RESULTS: A total of 16 of 33 (48.5%) patients had successful ATP to terminate VA, and 17 of 33 (51.5%) patients required shock therapy. Mean entropy was significantly higher in the shock versus successful ATP group (6.1 ± 0.5 vs 5.5 ± 0.7, P = .037). Analysis of patients receiving ATP (n = 22) showed significantly higher mean entropy in the six of 22 patients that failed ATP (followed by rescue ICD shock) compared to 16 of 22 that had successful ATP (6.3 ± 0.7 vs 5.5 ± 0.7, P = .048). Computer modeling suggested inability of the paced wavefront in ATP to successfully propagate from the electrode site through patchy fibrosis as a possible mechanism of failed ATP. CONCLUSIONS: Our findings suggest lower scar heterogeneity (mean entropy) is associated with successful ATP, whereas higher scar heterogeneity is associated with more aggressive VAs unresponsive to ATP requiring shock therapy that may be due to inability of the paced wavefront to propagate through scar and terminate the VA circuit.

Pilot study to differentiate lipoma from atypical lipomatous tumour/well-differentiated liposarcoma using MR radiomics-based texture analysis.

AIMS: This pilot study aims to determine if tumour heterogeneity assessed using magnetic resonance imaging (MRI) radiomics-based texture analysis (TA) can differentiate between lipoma and atypical lipomatous tumour (ALT)/well-differentiated liposarcoma (WDL). MATERIALS AND METHODS: Thirty consecutive ALT/WDLs and 30 lipomas were included in the study, cases diagnosed both histologically and with murine double minute 2 (MDM2) gene amplification by fluorescence in situ hybridisation (FISH) in excision specimens. Multiple patient, MRI and MRTA factors were assessed. Heterogeneity was evaluated using a filtration-histogram technique-based textural analysis on single axial proton density (PD) and coronal T1-W images of the most homogenously fatty component of the lesion. RESULTS: Thirty-three percent of the diagnoses of ALT/WDL vs lipoma were confirmed using FISH MDM2 analysis. ALT/WDLs were statistically different from lipomas in location (site in the body and depth from skin surface) and fat content, with p values of 0.021, 0.001, and 0.021 respectively. Nine of 36 (25%) texture parameters had significant differences between ALT/WDLs and lipomas on axial PD MRTA, with the most significant results at medium and coarse texture scales particularly mean intensity (p = 0.003) at SSF = 6, and kurtosis (p = 0.012) at SSF = 5. A cut-off value of < 304 for coarse-filtered texture on axial PD MRI identified ALT from lipoma with a sensitivity and specificity of 70% (AUC = 0.73, p = 0.003). CONCLUSIONS: Texture heterogeneity quantified at fine, medium, and coarse texture scales are significant differentiators of lipoma and ALT/WDL with the difference particularly marked in medium and coarse texture scales for two MR TA parameters: mean and kurtosis.

Synergistic application of pulmonary 18F-FDG PET/HRCT and computer-based CT analysis with conventional severity measures to refine current risk stratification in idiopathic pulmonary fibrosis (IPF).

INTRODUCTION: To investigate the combined performance of quantitative CT (qCT) following a computer algorithm analysis (IMBIO) and 18F-FDG PET/CT to assess survival in patients with idiopathic pulmonary fibrosis (IPF). METHODS: A total of 113 IPF patients (age 70 ± 9 years) prospectively and consecutively underwent 18F-FDG PET/CT and high-resolution CT (HRCT) at our institution. During a mean follow-up of 29.6 ± 26 months, 44 (48%) patients died. As part of the qCT analysis, pattern evaluation of HRCT (using IMBIO software) included the total extent (percentage) of the following features: normal-appearing lung, hyperlucent lung, parenchymal damage (comprising ground-glass opacification, reticular pattern and honeycombing), and the pulmonary vessels. The maximum (SUVmax) and minimum (SUVmin) standardized uptake value (SUV) for 18F-FDG uptake in the lungs, and the target-to-background (SUVmax/SUVmin) ratio (TBR) were quantified using routine region-of-interest (ROI) analysis. Pulmonary functional tests (PFTs) were acquired within 14 days of the PET/CT/HRCT scan. Kaplan-Meier (KM) survival analysis was used to identify associations with mortality. RESULTS: Data from 91 patients were available for comparative analysis. The average ± SD GAP [gender, age, physiology] score was 4.2 ± 1.7 (range 0-8). The average ± SD SUVmax, SUVmin, and TBR were 3.4 ± 1.4, 0.7 ± 0.2, and 5.6 ± 2.8, respectively. In all patients, qCT analysis demonstrated a predominantly reticular lung pattern (14.9 ± 12.4%). KM analysis showed that TBR (p = 0.018) and parenchymal damage assessed by qCT (p = 0.0002) were the best predictors of survival. Adding TBR and qCT to the GAP score significantly increased the ability to differentiate between high and low risk (p < 0.0001). CONCLUSION: 18F-FDG PET and qCT are independent and synergistic in predicting mortality in patients with IPF.

Magnetic Resonance Texture Analysis in Identifying Complete Pathological Response to Neoadjuvant Treatment in Locally Advanced Rectal Cancer.

BACKGROUND: A certain proportion of patients with locally advanced rectal cancer experience complete response after undergoing neoadjuvant chemoradiotherapy. These patients might be suitable for a conservative "watch and wait" approach, avoiding high-morbidity surgery. Texture analysis is a new modality that can assess heterogeneity in medical images by statistically analyzing gray-level intensities on a pixel-by-pixel basis. This study hypothesizes that texture analysis of magnetic resonance images can identify patients with a complete response. OBJECTIVE: This study aims to determine whether texture analysis of magnetic resonance images as a quantitative imaging biomarker can accurately identify patients with complete response. DESIGN: This is a retrospective diagnostic accuracy study. SETTINGS: This study was conducted at Colchester General Hospital, January 2003 to 2014. PATIENTS: All patients diagnosed with locally advanced rectal cancer who underwent long-course chemoradiotherapy had a posttreatment magnetic resonance scan and underwent surgery are included. INTERVENTION: Texture analysis was extracted from T2-weighted magnetic resonance images of the rectal cancer. MAIN OUTCOME MEASURES: Textural features that are able to identify complete responders were identified by a Mann-Whitney U test. Their diagnostic accuracy in identifying complete responders was determined by the area under the receiver operator characteristics curve. Cutoff values were determined by the Youden index. Pathology was the standard of reference. RESULTS: One hundred fourteen patients with first posttreatment MRI scans (6.2 weeks after completion of neoadjuvant treatment) were included. Sixty-eight patients had a second posttreatment scan (10.4 weeks). With no filtration, mean (p = 0.033), SD (p = 0.048), entropy (p = 0.007), and skewness (p = 0.000) from first posttreatment scans, and SD (p = 0.042), entropy (p = 0.014), mean of positive pixels (p = 0.032), and skewness (p = 0.000) from second posttreatment scans were all able to identify complete response. Area under the curve ranged from 0.750 to 0.88. LIMITATIONS: Texture analysis of MRI is a new modality; therefore, further studies are necessary to standardize the methodology of extraction of texture features, timing of scans, and acquisition parameters. CONCLUSIONS: Texture analysis of MRI is a potentially significant imaging biomarker that can accurately identify patients who have experienced complete response and might be suitable for a nonsurgical approach. (Cinicaltrials.gov:NCT02439086). See Video Abstract at http://links.lww.com/DCR/A760.

Texture analysis on diffusion tensor imaging: discriminating glioblastoma from single brain metastasis.

BACKGROUND: Texture analysis has been done on several radiological modalities to stage, differentiate, and predict prognosis in many oncologic tumors. PURPOSE: To determine the diagnostic accuracy of discriminating glioblastoma (GBM) from single brain metastasis (MET) by assessing the heterogeneity of both the solid tumor and the peritumoral edema with magnetic resonance imaging (MRI) texture analysis (MRTA). MATERIAL AND METHODS: Preoperative MRI examinations done on a 3-T scanner of 43 patients were included: 22 GBM and 21 MET. MRTA was performed on diffusion tensor imaging (DTI) in a representative region of interest (ROI). The MRTA was assessed using a commercially available research software program (TexRAD) which applies a filtration histogram technique for characterizing tumor and peritumoral heterogeneity. The filtration step selectively filters and extracts texture features at different anatomical scales varying from 2 mm (fine) to 6 mm (coarse). Heterogeneity quantification was obtained by the statistical parameter entropy. A threshold value to differentiate GBM from MET with sensitivity and specificity was calculated by receiver operating characteristic (ROC) analysis. RESULTS: Quantifying the heterogeneity of the solid part of the tumor showed no significant difference between GBM and MET. However, the heterogeneity of the GBMs peritumoral edema was significantly higher than the edema surrounding MET, differentiating them with a sensitivity of 80% and specificity of 90%. CONCLUSION: Assessing the peritumoral heterogeneity can increase the radiological diagnostic accuracy when discriminating GBM and MET. This will facilitate the medical staging and optimize the planning for surgical resection of the tumor and postoperative management.

Pulmonary 18F-FDG uptake helps refine current risk stratification in idiopathic pulmonary fibrosis (IPF).

PURPOSE: There is a lack of prognostic biomarkers in idiopathic pulmonary fibrosis (IPF) patients. The objective of this study is to investigate the potential of 18F-FDG-PET/ CT to predict mortality in IPF. METHODS: A total of 113 IPF patients (93 males, 20 females, mean age ± SD: 70 ± 9 years) were prospectively recruited for 18F-FDG-PET/CT. The overall maximum pulmonary uptake of 18F-FDG (SUVmax), the minimum pulmonary uptake or background lung activity (SUVmin), and target-to-background (SUVmax/ SUVmin) ratio (TBR) were quantified using routine region-of-interest analysis. Kaplan-Meier analysis was used to identify associations of PET measurements with mortality. We also compared PET associations with IPF mortality with the established GAP (gender age and physiology) scoring system. Cox analysis assessed the independence of the significant PET measurement(s) from GAP score. We investigated synergisms between pulmonary 18F-FDG-PET measurements and GAP score for risk stratification in IPF patients. RESULTS: During a mean follow-up of 29 months, there were 54 deaths. The mean TBR ± SD was 5.6 ± 2.7. Mortality was associated with high pulmonary TBR (p = 0.009), low forced vital capacity (FVC; p = 0.001), low transfer factor (TLCO; p < 0.001), high GAP index (p = 0.003), and high GAP stage (p = 0.003). Stepwise forward-Wald-Cox analysis revealed that the pulmonary TBR was independent of GAP classification (p = 0.010). The median survival in IPF patients with a TBR < 4.9 was 71 months, whilst in those with TBR > 4.9 was 24 months. Combining PET data with GAP data ("PET modified GAP score") refined the ability to predict mortality. CONCLUSIONS: A high pulmonary TBR is independently associated with increased risk of mortality in IPF patients.

Preoperative tumor texture analysis on MRI predicts high-risk disease and reduced survival in endometrial cancer.

BACKGROUND: Improved methods for preoperative risk stratification in endometrial cancer are highly requested by gynecologists. Texture analysis is a method for quantification of heterogeneity in images, increasingly reported as a promising diagnostic tool in various cancer types, but largely unexplored in endometrial cancer. PURPOSE: To explore whether tumor texture parameters from preoperative MRI are related to known prognostic features (deep myometrial invasion, cervical stroma invasion, lymph node metastases, and high-risk histological subtype) and to outcome in endometrial cancer patients. STUDY TYPE: Prospective cohort study. POPULATION/SUBJECTS: In all, 180 patients with endometrial carcinoma were included from April 2009 to November 2013 and studied until January 2017. FIELD STRENGTH/SEQUENCES: Preoperative pelvic MRI including contrast-enhanced T1 -weighted (T1 c), T2 -weighted, and diffusion-weighted imaging at 1.5T. ASSESSMENT: Tumor regions of interest (ROIs) were manually drawn on the slice displaying the largest cross-sectional tumor area, using the proprietary research software TexRAD for analysis. With a filtration-histogram technique, the texture parameters standard deviation, entropy, mean of positive pixels (MPP), skewness, and kurtosis were calculated. STATISTICAL TESTS: Associations between texture parameters and histological features were assessed by uni- and multivariable logistic regression, including models adjusting for preoperative biopsy status and conventional MRI findings. Multivariable Cox regression analysis was used for survival analysis. RESULTS: High tumor entropy in apparent diffusion coefficient (ADC) maps independently predicted deep myometrial invasion (odds ratio [OR] 3.2, P lt 0.001), and high MPP in T1 c images independently predicted high-risk histological subtype (OR 1.01, P = 0.004). High kurtosis in T1 c images predicted reduced recurrence- and progression-free survival (hazard ratio [HR] 1.5, P lt 0.001) after adjusting for MRI-measured tumor volume and histological risk at biopsy. DATA CONCLUSION: MRI-derived tumor texture parameters independently predicted deep myometrial invasion, high-risk histological subtype, and reduced survival in endometrial carcinomas, and thus, represent promising imaging biomarkers providing a more refined preoperative risk assessment that may ultimately enable better tailored treatment strategies in endometrial cancer. LEVEL OF EVIDENCE: 2 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2018;48:1637-1647.

MRI texture analysis (MRTA) of T2-weighted images in Crohn's disease may provide information on histological and MRI disease activity in patients undergoing ileal resection.

OBJECTIVES: To associate MRI textural analysis (MRTA) with MRI and histological Crohn's disease (CD) activity. METHODS: Sixteen patients (mean age 39.5 years, 9 male) undergoing MR enterography before ileal resection were retrospectively analysed. Thirty-six small (≤3 mm) ROIs were placed on T2-weighted images and location-matched histological acute inflammatory scores (AIS) measured. MRI activity (mural thickness, T2 signal, T1 enhancement) (CDA) was scored in large ROIs. MRTA features (mean, standard deviation, mean of positive pixels (MPP), entropy, kurtosis, skewness) were extracted using a filtration histogram technique. Spatial scale filtration (SSF) ranged from 2 to 5 mm. Regression (linear/logistic) tested associations between MRTA and AIS (small ROIs), and CDA/constituent parameters (large ROIs). RESULTS: Skewness (SSF = 2 mm) was associated with AIS [regression coefficient (rc) 4.27, p = 0.02]. Of 120 large ROI analyses (for each MRI, MRTA feature and SSF), 15 were significant. Entropy (SSF = 2, 3 mm) and kurtosis (SSF = 3 mm) were associated with CDA (rc 0.9, 1.0, -0.45, p = 0.006-0.01). Entropy and mean (SSF = 2-4 mm) were associated with T2 signal [odds ratio (OR) 2.32-3.16, p = 0.02-0.004], [OR 1.22-1.28, p = 0.03-0.04]. MPP (SSF = 2 mm) was associated with mural thickness (OR 0.91, p = 0.04). Kurtosis (SSF = 3 mm), standard deviation (SSF = 5 mm) were associated with decreased T1 enhancement (OR 0.59, 0.42, p = 0.004, 0.007). CONCLUSIONS: MRTA features may be associated with CD activity. KEY POINTS: • MR texture analysis features may be associated with Crohn's disease histological activity. • Texture analysis features may correlate with MR-dependent Crohn's disease activity scores. • The utility of MR texture analysis in Crohn's disease merits further investigation.

"Textural analysis of multiparametric MRI detects transition zone prostate cancer".

OBJECTIVES: To evaluate multiparametric-MRI (mpMRI) derived histogram textural-analysis parameters for detection of transition zone (TZ) prostatic tumour. METHODS: Sixty-seven consecutive men with suspected prostate cancer underwent 1.5T mpMRI prior to template-mapping-biopsy (TPM). Twenty-six men had 'significant' TZ tumour. Two radiologists in consensus matched TPM to the single axial slice best depicting tumour, or largest TZ diameter for those with benign histology, to define single-slice whole TZ-regions-of-interest (ROIs). Textural-parameter differences between single-slice whole TZ-ROI containing significant tumour versus benign/insignificant tumour were analysed using Mann Whitney U test. Diagnostic accuracy was assessed by receiver operating characteristic area under curve (ROC-AUC) analysis cross-validated with leave-one-out (LOO) analysis. RESULTS: ADC kurtosis was significantly lower (p < 0.001) in TZ containing significant tumour with ROC-AUC 0.80 (LOO-AUC 0.78); the difference became non-significant following exclusion of significant tumour from single-slice whole TZ-ROI (p = 0.23). T1-entropy was significantly lower (p = 0.004) in TZ containing significant tumour with ROC-AUC 0.70 (LOO-AUC 0.66) and was unaffected by excluding significant tumour from TZ-ROI (p = 0.004). Combining these parameters yielded ROC-AUC 0.86 (LOO-AUC 0.83). CONCLUSION: Textural features of the whole prostate TZ can discriminate significant prostatic cancer through reduced kurtosis of the ADC-histogram where significant tumour is included in TZ-ROI and reduced T1 entropy independent of tumour inclusion. KEY POINTS: • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram. • TZ containing significant tumour reveals higher post-contrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.

CT texture analysis can help differentiate between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer.

BACKGROUND: In patients with non-small-cell lung carcinoma NSCLC the lymph node staging in the mediastinum is important due to impact on management and prognosis. Computed tomography texture analysis (CTTA) is a postprocessing technique that can evaluate the heterogeneity of marked regions in images. PURPOSE: To evaluate if CTTA can differentiate between malignant and benign lymph nodes in a cohort of patients with suspected lung cancer. MATERIAL AND METHODS: With tissue sampling as reference standard, 46 lymph nodes from 29 patients were analyzed using CTTA. For each lymph node, CTTA was performed using a research software "TexRAD" by drawing a region of interest (ROI) on all available axial contrast-enhanced computed tomography (CT) slices covering the entire volume of the lymph node. Lymph node CTTA comprised image filtration-histogram analysis undertakes two stages: the first step comprised an application of a Laplacian of Gaussian filter to highlight fine to coarse textures within the ROI, followed by a quantification of textures via histogram analysis using mean gray-level intensity from the entire volume of the lymph nodes. RESULTS: CTTA demonstrated a statistically significant difference between the malignant and the benign lymph nodes (P = 0.001), and by binary logistic regression we obtained a sensitivity of 53% and specificity of 97% in the test population. The area under the receiver operating curve was 83.4% and reproducibility was excellent. CONCLUSION: CTTA may be helpful in differentiating between malignant and benign lymph nodes in the mediastinum in patients suspected for lung cancer, with a low intra-observer variance.

Predicting Overall Survival in Patients With Metastatic Melanoma on Antiangiogenic Therapy and RECIST Stable Disease on Initial Posttherapy Images Using CT Texture Analysis.

OBJECTIVE: The purpose of this study was to use CT texture analysis to predict overall survival (OS) in patients with metastatic melanoma and stable disease (SD) according to the Response Evaluation Criteria in Solid Tumors (RECIST) on initial posttherapy CT images. MATERIALS AND METHODS: This retrospective study included 42 patients with metastatic melanoma who received bevacizumab therapy in the context of a randomized prospective phase II clinical trial. Target lesions on the baseline and initial posttherapy contrast-enhanced CT examinations were evaluated by CT texture analysis using TexRAD software before and after image filtering in patients with RECIST SD on initial posttherapy images. Cox proportional hazards models were used to assess the associations of CT texture analysis measurements and of other patient factors with OS. The AUC was used to evaluate predictive accuracy. RESULTS: In multivariate analysis (in 23 patients with RECIST SD; median OS, 1.51 years), absolute change in mean positive pixels at spatial scaling filter of 4 mm, change in tumor size, and baseline serum lactate dehydrogenase (LDH) level were predictors of OS (hazard ratio [HR] = 5.05 for decrease in mean positive pixels at spatial scaling filter of 4 mm vs increase, p = 0.007; HR = 4.14 for > 5% increase in tumor size vs otherwise, p = 0.025; and HR = 1.29 for every 100 IU/L increase in baseline LDH level, p = 0.068). A prognostic index containing these three factors was highly accurate for predicting OS at 18 months (AUC = 0.917). CONCLUSION: In patients with metastatic melanoma and RECIST SD on initial post-therapy CT images, a model incorporating CT texture analysis of target lesions, tumor size changes, and baseline LDH levels was highly accurate in predicting OS.