Patient-tailored risk assessment of obstructive coronary artery disease using Rubidium-82 PET-based myocardial flow quantification with visual interpretation.

INTRODUCTION: Our aim was to estimate the probability of obstructive CAD (oCAD) for an individual patient as a function of the myocardial flow reserve (MFR) measured with Rubidium-82 (Rb-82) PET in patients with a visually normal or abnormal scan. MATERIALS AND METHODS: We included 1519 consecutive patients without a prior history of CAD referred for rest-stress Rb-82 PET/CT. All images were visually assessed by two experts and classified as normal or abnormal. We estimated the probability of oCAD for visually normal scans and scans with small (5%-10%) or larger defects (> 10%) as function of MFR. The primary endpoint was oCAD on invasive coronary angiography, when available. RESULTS: 1259 scans were classified as normal, 136 with a small defect and 136 with a larger defect. For the normal scans, the probability of oCAD increased exponentially from 1% to 10% when segmental MFR decreased from 2.1 to 1.3. For scans with small defects, the probability increased from 13% to 40% and for larger defects from 45% to > 70% when segmental MFR decreased from 2.1 to 0.7. CONCLUSION: Patients with > 10% risk of oCAD can be distinguished from patients with < 10% risk based on visual PET interpretation only. However, there is a strong dependence of MFR on patient's individual risk of oCAD. Hence, combining both visual interpretation and MFR results in a better individual risk assessment which may impact treatment strategy.

Machine learning based model to diagnose obstructive coronary artery disease using calcium scoring, PET imaging, and clinical data.

INTRODUCTION: Accurate risk stratification in patients with suspected stable coronary artery disease is essential for choosing an appropriate treatment strategy. Our aim was to develop and validate a machine learning (ML) based model to diagnose obstructive CAD (oCAD). METHOD: We retrospectively have included 1007 patients without a prior history of CAD who underwent CT-based calcium scoring (CACS) and a Rubidium-82 PET scan. The entire dataset was split 4:1 into a training and test dataset. An ML model was developed on the training set using fivefold stratified cross-validation. The test dataset was used to compare the performance of expert readers to the model. The primary endpoint was oCAD on invasive coronary angiography (ICA). RESULTS: ROC curve analysis showed an AUC of 0.92 (95% CI 0.90-0.94) for the training dataset and 0.89 (95% CI 0.84-0.93) for the test dataset. The ML model showed no significant differences as compared to the expert readers (p ≥ 0.03) in accuracy (89% vs. 88%), sensitivity (68% vs. 69%), and specificity (92% vs. 90%). CONCLUSION: The ML model resulted in a similar diagnostic performance as compared to expert readers, and may be deployed as a risk stratification tool for obstructive CAD. This study showed that utilization of ML is promising in the diagnosis of obstructive CAD.

Effect of temporal sampling protocols on myocardial blood flow measurements using Rubidium-82 PET.

BACKGROUND: A variety of temporal sampling protocols is used worldwide to measure myocardial blood flow (MBF). Both the length and number of time frames in these protocols may alter MBF and myocardial flow reserve (MFR) measurements. We aimed to assess the effect of different clinically used temporal sampling protocols on MBF and MFR quantification in Rubidium-82 (Rb-82) PET imaging. METHODS: We retrospectively included 20 patients referred for myocardial perfusion imaging using Rb-82 PET. A literature search was performed to identify appropriate sampling protocols. PET data were reconstructed using 14 selected temporal sampling protocols with time frames of 5-10 seconds in the first-pass phase and 30-120 seconds in the tissue phase. Rest and stress MBF and MFR were calculated for all protocols and compared to the reference protocol with 26 time frames. RESULTS: MBF measurements differed (P ≤ 0.003) in six (43%) protocols in comparison to the reference protocol, with mean absolute relative differences up to 16% (range 5%-31%). Statistically significant differences were most frequently found for protocols with tissue phase time frames < 90 seconds. MFR did not differ (P ≥ 0.11) for any of the protocols. CONCLUSIONS: Various temporal sampling protocols result in different MBF values using Rb-82 PET. MFR measurements were more robust to different temporal sampling protocols.

Value of SiPM PET in myocardial perfusion imaging using Rubidium-82.

BACKGROUND: PET scanners using silicon photomultipliers with digital readout (SiPM PET) have an improved temporal and spatial resolution compared to PET scanners using conventional photomultiplier tubes (PMT PET). However, the effect on image quality and visibility of perfusion defects in myocardial perfusion imaging (MPI) is unknown. Our aim was to determine the value of a SiPM PET scanner in MPI. METHODS: We prospectively included 30 patients who underwent rest and regadenoson-induced stress Rubidium-82 (Rb-82) MPI on the D690 PMT PET (GE Healthcare) and within three weeks on the Vereos SiPM PET (Philips Healthcare). Two expert readers scored the image quality and assessed the existence of possible defects. In addition, interpreter's confidence, myocardial blood flow (MBF), and myocardial flow reserve (MFR) values were compared. RESULTS: Image quality improved (P = 0.03) using the Vereos as compared to the D690. Image quality of the Vereos and the D690 was graded fair in 20% and 10%, good in 60% and 50%, and excellent in 20% and 40%, respectively. Defect interpretation and interpreter's confidence did not differ between the D690 and the Vereos (P > 0.50). There were no significant differences in rest MBF (P ≥ 0.29), stress MBF (P ≥ 0.11), and MFR (P ≥ 0.51). CONCLUSION: SiPM PET provides an improved image quality in comparison with PMT PET. Defect interpretation, interpreter's confidence, and absolute blood flow measurements were comparable between both systems. SiPM PET is therefore a reliable technique for MPI using Rb-82. TRIAL REGISTRATION: ToetsingOnline NL63853.075.17. Registered 13 November, 2017.

Automatic identification and segmentation of slice of minimal hiatal dimensions in transperineal ultrasound volumes.

OBJECTIVE: To develop and validate a tool for automatic selection of the slice of minimal hiatal dimensions (SMHD) and segmentation of the urogenital hiatus (UH) in transperineal ultrasound (TPUS) volumes. METHODS: Manual selection of the SMHD and segmentation of the UH was performed in TPUS volumes of 116 women with symptomatic pelvic organ prolapse (POP). These data were used to train two deep-learning algorithms. The first algorithm was trained to provide an estimation of the position of the SMHD. Based on this estimation, a slice was selected and fed into the second algorithm, which performed automatic segmentation of the UH. From this segmentation, measurements of the UH area (UHA), anteroposterior diameter (APD) and coronal diameter (CD) were computed automatically. The mean absolute distance between manually and automatically selected SMHD, the overlap (dice similarity index (DSI)) between manual and automatic UH segmentation and the intraclass correlation coefficient (ICC) between manual and automatic UH measurements were assessed on a test set of 30 TPUS volumes. RESULTS: The mean absolute distance between manually and automatically selected SMHD was 0.20 cm. All DSI values between manual and automatic UH segmentations were above 0.85. The ICC values between manual and automatic UH measurements were 0.94 (95% CI, 0.87-0.97) for UHA, 0.92 (95% CI, 0.78-0.97) for APD and 0.82 (95% CI, 0.66-0.91) for CD, demonstrating excellent agreement. CONCLUSIONS: Our deep-learning algorithms allowed reliable automatic selection of the SMHD and UH segmentation in TPUS volumes of women with symptomatic POP. These algorithms can be implemented in the software of TPUS machines, thus reducing clinical analysis time and simplifying the examination of TPUS data for research and clinical purposes. © 2021 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Body weight-dependent Rubidium-82 activity results in constant image quality in myocardial perfusion imaging with PET.

BACKGROUND: Clinical practice shows degrading image quality in heavier patients who undergo myocardial perfusion imaging (MPI) with Rubidium-82 (Rb-82) PET when using a fixed tracer activity. Our aim was to derive and validate a patient-specific activity protocol resulting in a constant image quality in PET MPI. METHODS: We included 251 patients who underwent rest MPI with Rb-82 PET (Discovery 670, GE Healthcare). 132 patients were included retrospectively and were scanned using a fixed activity of 740 MBq. The total number of measured prompts was normalized to activity and correlated to body weight, mass per body length and body mass index to find the best predicting parameter. Next, a patient-specific activity was derived and subsequently validated in 119 additional patients. Image quality was scored by three experts on a four-point scale. RESULTS: Both image quality and prompts decreased in heavier patients when using a fixed activity (p < .005). Body weight was used to derive a new activity formula: Activity = 8.3 MBq/kg. When applying this formula, both measured prompts and scored image quality became independent of body weight (p > .60). CONCLUSION: Administrating a Rb-82 activity that linearly depends on body weight resulted in a constant image quality across all patients and is recommended.

Correction to: No need for frame-wise attenuation correction in dynamic Rubidium-82 PET for myocardial blood flow quantification.

Due to the typesetter not carrying out the author's corrections at proof stage, there are two errors in the published article: where "mL × min × g" appears, it should be "mL/min/g". One error is in the Figure 3 caption, and one error is in the second sentence under the heading "MBF Quantification". The original article has been corrected.

Impact of regadenoson-induced myocardial creep on dynamic Rubidium-82 PET myocardial blood flow quantification.

BACKGROUND: Repositioning of the heart during myocardial perfusion imaging (MPI) using Rubidium-82 (Rb-82) PET may occur when using regadenoson. Our aim was to determine the prevalence and the effect of correcting for this myocardial creep on myocardial blood flow (MBF) quantification. METHODS: We retrospectively included 119 consecutive patients who underwent dynamic rest- and regadenoson-induced stress MPI using Rb-82 PET. The presence of myocardial creep was visually assessed in the dynamic stress PET series by identifying differences between the automatically drawn myocardium contour and the activity. Uncorrected and corrected stress MBFs were compared for the three vascular territories (LAD, LCX, and RCA) and for the whole myocardium. RESULTS: Myocardial creep was observed in 52% of the patients during stress. Mean MBF values decreased after correction in the RCA from 4.0 to 2.7 mL/min/g (P  < 0.001), in the whole myocardium from 2.7 to 2.6 mL/min/g (P  = 0.01), and increased in the LAD from 2.5 to 2.6 mL/min/g (P  = 0.03) and remained comparable in the LCX (P  = 0.3). CONCLUSIONS: Myocardial creep is a frequent phenomenon when performing regadenoson-induced stress Rb-82 PET and has a significant impact on MBF values, especially in the RCA territory. As this may hamper diagnostic accuracy, myocardial creep correction seems necessary for reliable quantification.

How to detect and correct myocardial creep in myocardial perfusion imaging using Rubidium-82 PET?

Reliability of myocardial blood flow (MBF) quantification in myocardial perfusion imaging (MPI) using PET can majorly be affected by the occurrence of myocardial creep when using pharmacologically induced stress. In this paper, we provide instructions on how to detect and correct for myocardial creep. For example, in each time frame of the PET images the myocardium contour and the observed activity have to be compared to check for misalignments. In addition, we provide an overview of the functionality of commonly used software packages to perform this quality control step as not all software packages currently provide this functionality. Furthermore, important clinical considerations to obtain accurate MBF measurements are given.

No need for frame-wise attenuation correction in dynamic Rubidium-82 PET for myocardial blood flow quantification.

BACKGROUND: Regadenoson-induced stress causes a repositioning of the heart, myocardial creep, in half of the patients undergoing Rubidium-82 (Rb-82) positron emission tomography (PET). As a result, misalignment of dynamic PET and computer tomography (CT) may occur, possibly affecting CT-based attenuation correction (AC) and thereby PET-based myocardial blood flow (MBF) quantification. Our aim was to determine the need for frame-wise PET-CT AC to obtain reliable MBF measurements. METHODS: 31 Out of 64 consecutive patients had myocardial creep during regadenoson-induced stress Rb-82 PET-CT and were included. Prior to PET image reconstruction, we applied two AC methods; single PET-CT alignment and frame-wise alignment in which PET time-frames with myocardial creep were individually co-registered with CT. The PET-CT misalignment was then quantified and MBFs for the three vascular territories and whole myocardium were calculated and compared between both methods. RESULTS: The magnitude of misalignment due to myocardial creep was 13.8 ± 4.5 mm in caudal-cranial direction, 1.8 ± 2.1 mm in medial-lateral and 2.5 ± 1.8 mm in anterior-posterior direction. Frame-wise PET-CT registration did not result in different MBF measurements (P ≥ .07) and the magnitude of misalignment and MBF differences did not correlate (P ≥ .58). CONCLUSION: There is no need for frame-wise AC in dynamic Rb-82 PET for MBF quantification. Single alignment seems sufficient in patients with myocardial creep.

Deep learning enables automatic quantitative assessment of puborectalis muscle and urogenital hiatus in plane of minimal hiatal dimensions.

OBJECTIVES: To measure the length, width and area of the urogenital hiatus (UH), and the length and mean echogenicity (MEP) of the puborectalis muscle (PRM), automatically and observer-independently, in the plane of minimal hiatal dimensions on transperineal ultrasound (TPUS) images, by automatic segmentation of the UH and the PRM using deep learning. METHODS: In 1318 three- and four-dimensional (3D/4D) TPUS volume datasets from 253 nulliparae at 12 and 36 weeks' gestation, two-dimensional (2D) images in the plane of minimal hiatal dimensions with the PRM at rest, on maximum contraction and on maximum Valsalva maneuver, were obtained manually and the UH and PRM were segmented manually. In total, 713 of the images were used to train a convolutional neural network (CNN) to segment automatically the UH and PRM in the plane of minimal hiatal dimensions. In the remainder of the dataset (test set 1 (TS1); 601 images, four having been excluded), the performance of the CNN was evaluated by comparing automatic and manual segmentations. The performance of the CNN was also tested on 117 images from an independent dataset (test set 2 (TS2); two images having been excluded) from 40 nulliparae at 12 weeks' gestation, which were acquired and segmented manually by a different observer. The success of automatic segmentation was assessed visually. Based on the CNN segmentations, the following clinically relevant parameters were measured: the length, width and area of the UH, the length of the PRM and MEP. The overlap (Dice similarity index (DSI)) and surface distance (mean absolute distance (MAD) and Hausdorff distance (HDD)) between manual and CNN segmentations were measured to investigate their similarity. For the measured clinically relevant parameters, the intraclass correlation coefficients (ICCs) between manual and CNN results were determined. RESULTS: Fully automatic CNN segmentation was successful in 99.0% and 93.2% of images in TS1 and TS2, respectively. DSI, MAD and HDD showed good overlap and distance between manual and CNN segmentations in both test sets. This was reflected in the respective ICC values in TS1 and TS2 for the length (0.96 and 0.95), width (0.77 and 0.87) and area (0.96 and 0.91) of the UH, the length of the PRM (0.87 and 0.73) and MEP (0.95 and 0.97), which showed good to very good agreement. CONCLUSION: Deep learning can be used to segment automatically and reliably the PRM and UH on 2D ultrasound images of the nulliparous pelvic floor in the plane of minimal hiatal dimensions. These segmentations can be used to measure reliably UH dimensions as well as PRM length and MEP. © 2018 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Automatic segmentation of puborectalis muscle on three-dimensional transperineal ultrasound.

OBJECTIVES: The introduction of three-dimensional (3D) analysis of the puborectalis muscle (PRM) for diagnostic purposes into daily practice is hindered by the need for appropriate training of observers. Automatic segmentation of the PRM on 3D transperineal ultrasound may aid its integration into clinical practice. The aims of this study were to present and assess a protocol for manual 3D segmentation of the PRM on 3D transperineal ultrasound, and to use this for training of automatic 3D segmentation method of the PRM. METHODS: The data used in this study were derived from 3D transperineal ultrasound sequences of the pelvic floor acquired at 12 weeks' gestation from nulliparous women with a singleton pregnancy. A manual 3D segmentation protocol was developed for the PRM based on a validated two-dimensional segmentation protocol. For automatic segmentation, active appearance models of the PRM were developed, trained using manual segmentation data from 50 women. The performances of both manual and automatic segmentation were analyzed by measuring the overlap and distance between the segmentations. Intraclass correlation coefficients (ICCs) and their 95% CIs were determined for mean echogenicity and volume of the puborectalis muscle, in order to assess inter- and intraobserver reliabilities of the manual method using data from 20 women, as well as to compare the manual and automatic methods. RESULTS: Interobserver reliabilities for mean echogenicity and volume were very good for manual segmentation (ICCs 0.987 and 0.910, respectively), as were intraobserver reliabilities (ICCs 0.991 and 0.877, respectively). ICCs for mean echogenicity and volume were very good and good, respectively, for the comparison of manual vs automatic segmentation (0.968 and 0.626, respectively). The overlap and distance results for manual segmentation were as expected, showing an average mismatch of only 2-3 pixels and reasonable overlap. Based on overlap and distance, five mismatches were detected for automatic segmentation, resulting in an automatic segmentation success rate of 90%. CONCLUSIONS: This study presents a reliable manual segmentation protocol and automatic 3D segmentation method for the PRM, which will facilitate future investigation of the PRM, allowing for the reliable measurement of potentially clinically valuable parameters such as mean echogenicity. © 2017 The Authors. Ultrasound in Obstetrics & Gynecology Published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.

Value of attenuation correction in stress-only myocardial perfusion imaging using CZT-SPECT.

BACKGROUND: Attenuation correction (AC) improves the diagnostic outcome of stress-only myocardial perfusion imaging (MPI) using conventional SPECT. Our aim was to determine the value of AC using a cadmium zinc telluride-based (CZT)-SPECT camera. METHODS AND RESULTS: We retrospectively included 107 consecutive patients who underwent stress-optional rest MPI CZT-SPECT/CT. Next, we created three types of images for each patient; (1) only displaying reconstructed data without the CT-based AC (NC), (2) only displaying AC, and (3) with both NC and AC (NC + AC). Next, two experienced physicians visually interpreted these 321 randomized images as normal, equivocal, or abnormal. Image outcome was compared with all hard events over a mean follow-up time of 47.7 ± 9.8 months. The percentage of images interpreted as normal increased from 45% using the NC images to 72% using AC and to 67% using NC + AC images (P < .001). Hard event hazard ratios for images interpreted as normal were not different between using NC and AC (1.01, P = .99), or NC and NC + AC images (0.97, P = .97). CONCLUSIONS: AC lowers the need for additional rest imaging in stress-first MPI using CZT-SPECT, while long-term patient outcome remained identical. Use of AC reduces the need for additional rest imaging, decreasing the mean effective dose by up to 1.2 mSv.

Low-dose CT imaging of a total hip arthroplasty phantom using model-based iterative reconstruction and orthopedic metal artifact reduction.

OBJECTIVE: To compare quantitative measures of image quality, in terms of CT number accuracy, noise, signal-to-noise-ratios (SNRs), and contrast-to-noise ratios (CNRs), at different dose levels with filtered-back-projection (FBP), iterative reconstruction (IR), and model-based iterative reconstruction (MBIR) alone and in combination with orthopedic metal artifact reduction (O-MAR) in a total hip arthroplasty (THA) phantom. MATERIALS AND METHODS: Scans were acquired from high- to low-dose (CTDIvol: 40.0, 32.0, 24.0, 16.0, 8.0, and 4.0 mGy) at 120- and 140- kVp. Images were reconstructed using FBP, IR (iDose4 level 2, 4, and 6) and MBIR (IMR, level 1, 2, and 3) with and without O-MAR. CT number accuracy in Hounsfield Units (HU), noise or standard deviation, SNRs, and CNRs were analyzed. RESULTS: The IMR technique showed lower noise levels (p < 0.01), higher SNRs (p < 0.001) and CNRs (p < 0.001) compared with FBP and iDose4 in all acquisitions from high- to low-dose with constant CT numbers. O-MAR reduced noise (p < 0.01) and improved SNRs (p < 0.01) and CNRs (p < 0.001) while improving CT number accuracy only at a low dose. At the low dose of 4.0 mGy, IMR level 1, 2, and 3 showed 83%, 89%, and 95% lower noise values, a factor 6.0, 9.2, and 17.9 higher SNRs, and 5.7, 8.8, and 18.2 higher CNRs compared with FBP respectively. CONCLUSIONS: Based on quantitative analysis of CT number accuracy, noise values, SNRs, and CNRs, we conclude that the combined use of IMR and O-MAR enables a reduction in radiation dose of 83% compared with FBP and iDose4 in the CT imaging of a THA phantom.

Aortic Curvature Instead of Angulation Allows Improved Estimation of the True Aorto-iliac Trajectory.

OBJECTIVE: Supra- and infrarenal aortic neck angulation have been associated with complications after endovascular aortic aneurysm repair. However, a uniform angulation measurement method is lacking and the concept of angulation suggests a triangular oversimplification of the aortic anatomy. (Semi-)automated calculation of curvature along the center luminal line describes the actual trajectory of the aorta. This study proposes a methodology for calculating aortic (neck) curvature and suggests an additional method based on available tools in current workstations: curvature by digital calipers (CDC). METHODS: Proprietary custom software was developed for automatic calculation of the severity and location of the largest supra- and infrarenal curvature over the center luminal line. Twenty-four patients with severe supra- or infrarenal angulations (≥45°) and 11 patients with small to moderate angulations (<45°) were included. Both CDC and angulation were measured by two independent observers on the pre- and postoperative computed tomographic angiography scans. The relationships between actual curvature and CDC and angulation were visualized and tested with Pearson's correlation coefficient. The CDC was also fully automatically calculated with proprietary custom software. The difference between manual and automatic determination of CDC was tested with a paired Student t test. A p-value was considered significant when two-tailed α < .05. RESULTS: The correlation between actual curvature and manual CDC is strong (.586-.962) and even stronger for automatic CDC (.865-.961). The correlation between actual curvature and angulation is much lower (.410-.737). Flow direction angulation values overestimate CDC measurements by 60%, with larger variance. No significant difference was found in automatically calculated CDC values and manually measured CDC values. CONCLUSION: Curvature calculation of the aortic neck improves determination of the true aortic trajectory. Automatic calculation of the actual curvature is preferable, but measurement or calculation of the curvature by digital calipers is a valid alternative if actual curvature is not at hand.

Changes in Aortoiliac Anatomy After Elective Treatment of Infrarenal Abdominal Aortic Aneurysms with a Sac Anchoring Endoprosthesis.

OBJECTIVE: Endovascular aortic sealing (EVAS) with the Nellix endosystem (Endologix, Irvine, CA, USA) is a new concept to treat infrarenal abdominal aortic aneurysms (AAAs). By sealing the aneurysm, potential endoleaks may be avoided. Early results of EVAS are good, but no data have been published regarding peri-procedural changes in aortoiliac anatomy. In this study, 27 consecutive patients who underwent elective EVAS repair of an AAA were reviewed. METHOD: Specific AAA (diameter, length from renal arteries to aortic bifurcation, supra- and infrarenal neck angulation, AAA volume, thrombus volume, and flow lumen volume), and iliac artery characteristics (length, angulation, location of most severe angulation with reference to the origin of the common iliac artery) were determined from pre- and post-procedural reconstructed computed tomography angiograms. RESULTS: No type I or II endoleaks were seen at 30 day follow up. Total AAA volume, suprarenal and infrarenal angulation, as well as aortic neck diameter did not change significantly post-EVAS. AAA flow lumen increased significantly (mean difference -4.4 mL, 95% CI 2.0 to -8.6 mL) and AAA thrombus volume decreased (mean difference 3.2 mL, 95% CI 2.0 to -1.1 mL). AAA length (125.7 mm vs. 123.1 mm), left common iliac artery length (57.6 mm vs. 55.3 mm), and right and left maximum iliac artery angulation (right 37.4° vs. 32.2°; left: 43.9° vs. 38.4°) were reduced significantly and the location of maximum angulation was further from the iliac artery origin post-EVAS, suggesting slight straightening of the aortoiliac anatomy. CONCLUSION: Most aortoiliac anatomic characteristics remained unchanged post-EVAS. Filling of the endobags to a pressure of 180 mmHg may lead to lost thrombus volume in some patients, probably because liquid is squeezed into lumbar or the inferior mesenteric artery. The absolute differences in pre- and post-EVAS aortoiliac lengths were small, so pre-operative sizing is accurate for determining stent length.

Development and validation of a patient-tailored dose regime in myocardial perfusion imaging using conventional SPECT.

BACKGROUND: The decreasing image quality in heavier patients can be compensated by administration of a patient-specific dose in myocardial perfusion imaging (MPI) using a cadmium zinc telluride-based SPECT camera. Our aim was to determine if the same can be achieved when using a conventional SPECT camera. METHODS: 148 patients underwent SPECT stress MPI using a fixed Tc-99m tetrofosmin tracer dose. Measured photon counts were normalized to administered tracer dose and scan time and were correlated with body weight, body mass index, and mass per length to find the best predicting parameter. From these data, a protocol to provide constant image quality was derived, and subsequently validated in 125 new patients. RESULTS: Body weight was found to be the best predicting parameter for image quality and was used to derive a new dose formula; A admin (MBq) = 223·body weight (kg)(0.65)/T scan (min). The measured photon counts decreased in heavier patients when using a fixed dose (P < .01) but this was no longer observed after applying a body-weight-dependent protocol (P = .20). CONCLUSIONS: Application of a patient-specific protocol resulted in an image quality less depending on patient's weight. The results are most likely independent of the type of SPECT camera used, and, hence, adoption of patient-specific dose and scan time protocols is recommended.

Skeletal muscle mass and quality as risk factors for postoperative outcome after open colon resection for cancer.

BACKGROUND: The prevalence of colorectal cancer in the elderly is increasing and, therefore, surgical interventions with a risk of potential complications are more frequently performed. This study investigated the role of low skeletal muscle mass (sarcopenia), muscle quality, and the sarcopenic obesity as prognostic factors for postoperative complications and survival in patients with resectable colon cancer. METHODS: We conducted a retrospective chart review of 91 consecutive patients who underwent an elective open colon resection for cancer with primary anastomosis between 2011 and 2013. Skeletal muscle mass was measured as total psoas area (TPA) and total abdominal muscle area (TAMA) at three anatomical levels on the preoperative CT scan. Skeletal muscle quality was measured using corresponding mean Hounsfield units (HU) for TAMA. Their relation with complications (none vs one or more), severe complications, and survival was analyzed. RESULTS: The study included 91 patients with a mean age of 71.2 ± 9.7 years. Complications were noted in 55 patients (60 %), of which 15 (16.4 %) were severe. Lower HU for TAMA, as an indicator for impaired skeletal muscle quality, was an independent risk factor for one or more complications (all P ≤ 0.002), while sarcopenic obesity (TPA) was an independent risk factor for severe complications (all P ≤ 0.008). Sarcopenia was an independent predictor of worse overall survival (HR 8.54; 95 % confidence interval (CI) 1.07-68.32). CONCLUSION: Skeletal muscle quality is a predictor for overall complications, whereas sarcopenic obesity is a predictor for severe postoperative complications after open colon resection for cancer. Sarcopenia on itself is a predictor for worse overall survival.

A non-invasive cardiac output measurement as an alternative to the test bolus technique during CT angiography.

AIM: To investigate the association between a non-invasive cardiac output (CO) measurement and the scan delay, as derived from a test bolus injection protocol. The secondary objective was to determine which factors affect the relationship between the CO and scan delay. MATERIALS AND METHODS: Fifty-five patients referred for a contrast-enhanced (thorax-)abdomen CT examination were included in this feasibility study. A test bolus examination was performed prior to the abdominal CT. During the test bolus injection, the CO of the patient was measured using a non-invasive finger-cuff measurement. Associations were analysed using linear regression analyses. Age, gender, height, weight, and blood pressure were included as potential confounders. RESULTS: Linear regression analysis showed a negative and significant association between CO and delay. The regression formula was as follows: scan delay (seconds) = 26.8-1.6 CO (l/min), with a 95% CI between -2.3 and -1.0 (p<0.001). Weight appeared to be a confounder in this relation, and gender and blood pressure were effect modifiers. There was no interaction between scan delay and age, height and weight. CONCLUSIONS: There is a negative and significant association between the non-invasive CO measurement and the CT scan delay; however, to validate these findings a larger cohort study is needed to investigate whether the non-invasively determined scan delay is as accurate as the use of a test bolus.