Pectoral muscle mass is not a robust prognostic factor for survival after left ventricular assist device (LVAD) implantation.

BACKGROUND: Left ventricular assist devices (LVAD) are an established treatment for end-stage left ventricular heart failure. Parameters are needed to identify the most appropriate patients for LVADs. This study aimed to evaluate pectoral muscle mass and density as prognostic parameters. METHODS: This single-center study included all patients with LVAD implantation between January 2010 and October 2017 and a preoperative chest CT scan. Pectoral muscle mass was assessed using the Pectoralis Muscle Index (PMI, surface area indexed to height, cm2/m2) and pectoral muscle density by Hounsfield Units (HU). Overall mortality was analyzed with Kaplan-Meier survival analysis and 1-year and 3-year mortality with receiver operating characteristic (ROC) curves and Cox regression models. RESULTS: 57 patients (89.5% male, mean age 57.8 years) were included. 64.9% of patients had end-stage left ventricular failure due to ischemic heart disease and 35.1% due to dilated cardiomyopathy. 49.2% of patients had preoperative INTERMACS profile of 1 or 2 and 33.3% received mechanical circulatory support prior to LVAD implantation. Total mean PMI was 4.7 cm2/m2 (± 1.6), overall HU of the major pectoral muscle was 39.0 (± 14.9) and of the minor pectoral muscle 37.1 (± 16.6). Mean follow-up was 2.8 years (± 0.2). Mortality rates were 37.5% at 1 year and 48.0% at 3 years. Neither PMI nor HU were significantly associated with overall mortality at 1-year or 3-year. CONCLUSIONS: The results of our study do not confirm the association between higher pectoral muscle mass and better survival after LVAD implantation previously described in the literature.

Impact of psoas muscle evaluation on clinical outcomes in patients undergoing left ventricular assist device implantation.

AIMS: The measurement of muscle mass reflects the physical components of frailty, which might affect postoperative outcomes in patients undergoing left ventricular assist device (LVAD) implantation. The aim of this study was to investigate the relationship between preoperative skeletal muscle evaluation and clinical outcomes in patients undergoing LVAD implantation. METHODS: From January 2010 to December 2017, a total of 63 patients were enrolled in this single-centre study. A retrospective analysis of preoperative abdominal computed tomography (CT) for psoas muscle index (PSMI) and Hounsfield-Units of the Psoas Muscle (PSHU) at the level of the mid-L4 vertebra was performed. RESULTS: Sixty-three patients (male; n = 49, 78%), with a mean age of 58.0 ±â€Š11.8 years, were treated with LVAD due to dilated (32%) or ischemic cardiomyopathy (68%). Among them, 43 patients (68.3%) were categorized in the Interagency Registry for Mechanically Assisted Circulatory Support profile I. The survival rate was 73.0% at 30 days and 44.4% at 1 year. Receiver-operating characteristic (ROC) curve analyses revealed that PSMI was a significant numeric predictor of 1-year mortality (P = 0.04). In contrast, PSHU displayed a significant predictive potential for pericardial effusion (P = 0.03) and respiratory insufficiency (P = 0.01). In addition, comparative ROC curve analysis revealed no significant difference in the predictive potential of PSMI and PSHU. CONCLUSION: Preoperative PSMI might be a predictor of 1-year mortality in patients undergoing LVAD implantation. In contrast, the PSHU seemed to potentially assume postoperative adverse events in this study. Thus, the evaluation of the preoperative psoas muscle using CT appears to be promising.

Influence of a Deep Learning Noise Reduction on the CT Values, Image Noise and Characterization of Kidney and Ureter Stones.

Deep-learning (DL) noise reduction techniques in computed tomography (CT) are expected to reduce the image noise while maintaining the clinically relevant information in reduced dose acquisitions. This study aimed to assess the size, attenuation, and objective image quality of reno-ureteric stones denoised using DL-software in comparison to traditionally reconstructed low-dose abdominal CT-images and evaluated its clinical impact. In this institutional review-board-approved retrospective study, 45 patients with renal and/or ureteral stones were included. All patients had undergone abdominal CT between August 2019 and October 2019. CT-images were reconstructed using the following three methods: filtered back-projection, iterative reconstruction, and PixelShine (DL-software) with both sharp and soft kernels. Stone size, CT attenuation, and objective image quality (signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR)) were evaluated and compared using Bonferroni-corrected Friedman tests. Objective image quality was measured in six regions-of-interest. Stone size ranged between 4.4 × 3.1−4.4 × 3.2 mm (sharp kernel) and 5.1 × 3.8−5.6 × 4.2 mm (soft kernel). Mean attenuation ranged between 704−717 Hounsfield Units (HU) (soft kernel) and 915−1047 HU (sharp kernel). Differences in measured stone sizes were ≤1.3 mm. DL-processed images resulted in significantly higher CNR and SNR values (p < 0.001) by decreasing image noise significantly (p < 0.001). DL-software significantly improved objective image quality while maintaining both correct stone size and CT-attenuation values. Therefore, the clinical impact of stone assessment in denoised image data sets remains unchanged. Through the relevant noise suppression, the software additionally offers the potential to further reduce radiation exposure.

CT Findings in Patients with COVID-19-Compatible Symptoms but Initially Negative qPCR Test.

PURPOSE: To assess whether it is possible to reliably detect patients with strong suspicion of COVID-19 despite initially negative quantitative polymerase-chain-reaction (qPCR) tests by means of computed tomography (CT). MATERIALS AND METHODS: 437 patients with suspected COVID-19 but initially negative qPCR and subsequent chest CT between March 13 and November 30, 2020 were included in this retrospective study. CT findings were compared to results of successive qPCR tests (minimum of 3 qPCR tests if CT suggested infection) to determine the sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of CT for diagnosing COVID-19. RESULTS: COVID-19 was diagnosed correctly with a sensitivity of 100 % [95 % confidence interval (CI): 65-100] and a specificity of 88 % [95 % CI: 84-90]. A PPV of 12 % [95 % CI: 6-22] and an NPV of 100 % [95 % CI: 99-100] were determined. CONCLUSION: CT is able to detect COVID-19 before qPCR in initially negative patients in this special study setting. Similar CT findings in COVID-19 and other atypical pneumonias can lead to high numbers of false-positive patients, reducing the specificity of CT. KEY POINTS: · Low-dose chest CT is able to diagnose COVID-19 in symptomatic patients even in cases of an initially negative quantitative PCR result and therefore is a fast support method to detect COVID-19, especially in early disease.. · Low-dose chest CT can reliably exclude COVID-19 in a pandemic setting.. · CT does not always ensure a reliable differentiation from other viral diseases.. CITATION FORMAT: · Valentin B, Steuwe A, Wienemann T, et al. CT Findings in Patients with COVID-19-Compatible Symptoms but Initially Negative qPCR Test. Fortschr Röntgenstr 2022; 194: 1110 - 1118.

Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America.

PURPOSE: Classifications were created to facilitate radiological evaluation of the novel coronavirus disease 2019 (COVID-19) on computed tomography (CT) images. The categorical CT assessment scheme (CO-RADS) categorizes lung parenchymal changes according to their likelihood of being caused by SARS-CoV-2 infection. This study investigates the diagnostic accuracy of diagnosing COVID-19 with CO-RADS compared to the Thoracic Imaging Section of the German Radiological Society (DRG) classification and Radiological Society of North America (RSNA) classification in an anonymized patient cohort. To mimic advanced disease stages, follow-up examinations were included as well. METHOD: This study includes all patients undergoing chest CT in the case of a suspected SARS-CoV-2 infection or an already confirmed infection between March 13 and November 30, 2020. During the study period, two regional lockdowns occurred due to high incidence values, increasing the pre-test probability of COVID-19. Anonymized CT images were reviewed retrospectively and in consensus by two radiologists applying CO-RADS, DRG, and RSNA classification. Afterwards, CT findings were compared to results of sequential real-time reverse transcriptase polymerase chain reaction (qPCR) test performed during hospitalization to determine statistical analysis for diagnosing COVID-19. RESULTS: 536 CT examinations were included. CO-RADS, DRG and RSNA achieved an NPV of 96 %/94 %/95 % (CO-RADS/DRG/RSNA), PPV of 83 %/80 %/88 %, sensitivity of 86 %/76 %/80 %, and specificity of 96 %/95 %/97 %. The disease prevalence was 20 %. CONCLUSION: All applied classifications can reliably exclude a SARS-CoV-2 infection even in an anonymous setting. Nevertheless, pre-test probability was high in our study setting and has a great influence on the classifications. Therefore, the applicability of the individual classifications will become apparent in the future with lower prevalence and incidence of COVID-19. KEY POINTS: · CO-RADS, DRG, and RSNA classifications help to reliably detect infected patients in an anonymized setting. · Pre-test probability has a great influence on the individual classifications. · Difficulties in an anonymized study setting are severe pulmonary changes and residuals.. CITATION FORMAT: · Valentin B, Steuwe A, Wienemann T et al. Applicability of CO-RADS in an Anonymized Cohort Including Early and Advanced Stages of COVID-19 in Comparison to the Recommendations of the German Radiological Society and Radiological Society of North America. Fortschr Röntgenstr 2022; 194: 862 - 872.

Effect of preoperative erector spinae muscles mass on postoperative outcomes in patients with left ventricular assist devices.

BACKGROUND: Frailty influences the postoperative outcomes in patients undergoing left ventricular assist device (LVAD) implantation. Recently, erector spinae muscle (ESM) mass has been proposed as a parameter to assess frailty accurately. Thus, the purpose of the present study was to evaluate whether preoperative ESM mass is associated with short- and long-term clinical outcomes in patients with LVAD. METHODS: A total of 119 consecutive patients with LVAD were enrolled between January 2010 and October 2017 at a single heart center. The ESM area, ESM index, and Hounsfield units (HU) of the ESM were calculated by computed tomography for preoperative ESM mass evaluation. We then statistically evaluated the in-hospital mortality, major adverse cardiovascular events (MACE), duration of hospital stay, and long-term survival. RESULTS: In a multivariate Cox regression analysis, ESM mass indicated no effect on all clinical outcomes. In addition, the ESM area presented a weak but significant negative linear correlation only with the duration of hospital stay (r = -0.21, p < .05). In contrast, the Model For End-stage Liver Disease (MELD) score and preoperative venous-arterial extracorporeal membrane oxygenation (va-ECMO) were significant predictive factors for in-hospital mortality (MELD score: p < .001, hazard ratio [HR] 1.1; preoperative va-ECMO: p < .01, HR 2.72) and MACE (MELD score: p < .001, HR 1.07; preoperative va-ECMO: p < .005, HR 2.62). CONCLUSION: Preoperative ESM mass might predict the length of hospital stay in patients undergoing LVAD implantation. In contrast, it had no effect on MACE, in-hospital mortality, or long-term survival in this study.

Evaluation of split-filter dual-energy CT for characterization of urinary stones.

OBJECTIVE: To assess accuracy of dual-energy computed tomography (DECT) to differentiate uric acid from calcium urinary stones in dual-energy split filter vs sequential-spiral vs dual-source acquisition. METHODS: Thirty-four urinary stones (volume 89.0 ± 77.4 mm³; 17 calcium stones, 17 uric acid stones) were scanned in a water-filled phantom using a split-filter equipped CT scanner (SOMATOM Definition Edge, Siemens Healthineers, Forchheim, Germany) in split-filter mode at 120 kVp and sequential-spiral mode at 80 and 140 kVp. Additional DE scans were acquired at 80 and 140 kVp (tin filter) with a dual-source CT scanner (SOMATOM Definition FLASH, Siemens Healthineers). Scans were performed with a CTDIvol of 7.3 mGy in all protocols. Urinary stone categorization was based on dual energy ratio (DER) using an automated 3D segmentation. As reference standard, infrared spectroscopy was used to determine urinary stone composition. RESULTS: All three DECT techniques significantly differentiated between uric acid and calcium stones by attenuation values and DERs (p < 0.001 for all). Split-filter DECT provided higher DERs for uric acid stones, when compared with dual-source and sequential-spiral DECT, and lower DERs for calcified stones when compared with dual-source DECT (p < 0.001 for both), leading to a decreased accuracy for material differentiation. CONCLUSION: Split-filter DECT, sequential-spiral DECT and dual-source DECT all allow for the acquisition of DER to classify urinary stones. ADVANCES IN KNOWLEDGE: Split-filter DECT enables the differentiation between uric acid and calcium stones despite decreased spectral separation when compared with dual-source and dual-spiral DECT.

Within- and across-network alterations of the sensorimotor network in Parkinson's disease.

PURPOSE: Parkinson's disease (PD) is primarily defined by motor symptoms and is associated with alterations of sensorimotor areas. Evidence for network changes of the sensorimotor network (SMN) in PD is inconsistent and a systematic evaluation of SMN in PD yet missing. We investigate functional connectivity changes of the SMN in PD, both, within the network, and to other large-scale connectivity networks. METHODS: Resting-state fMRI was assessed in 38 PD patients under long-term dopaminergic treatment and 43 matched healthy controls (HC). Independent component analysis (ICA) into 20 components was conducted and the SMN was identified within the resulting networks. Functional connectivity within the SMN was analyzed using a dual regression approach. Connectivity between the SMN and the other networks from group ICA was investigated with FSLNets. We investigated for functional connectivity changes between patients and controls as well as between medication states (OFF vs. ON) in PD and for correlations with clinical parameters. RESULTS: There was decreased functional connectivity within the SMN in left inferior parietal and primary somatosensory cortex in PD OFF. Across networks, connectivity between SMN and two motor networks as well as two visual networks was diminished in PD OFF. All connectivity decreases partially normalized in PD ON. CONCLUSION: PD is accompanied by functional connectivity losses of the SMN, both, within the network and in interaction to other networks. The connectivity changes in short- and long-range connections are probably related to impaired sensory integration for motor function in PD. SMN decoupling can be partially compensated by dopaminergic therapy.

Is the prediction of one or two ipsilateral positive lymph nodes by computerized tomography and ultrasound reliable enough to restrict therapeutic neck dissection in oral squamous cell carcinoma (OSCC) patients?

INTRODUCTION: Proper management of the clinically involved neck in OSCC patients continues to be a matter of debate. Our aim was to analyze the accuracy of computerized tomography (CT) and ultrasound (US) in anticipating the exact location of lymph node (LN) metastases of OSCC patients across the AAO-HNS (American Academy of Otolaryngology-Head and Neck Surgery) levels ipsi- and contralaterally. Furthermore, we wanted to assess the suitability of therapeutic selective neck dissection (SND) in patients with one or two ipsilateral positive nodes upon clinical staging (cN1/cN2a and cN2b(2/x) patients). METHODS: We prospectively analyzed the LN status of patients with primary OSCC using CT and US from 2007 to 2013. LNs were individually assigned to a map containing the AAO-HNS levels; patients bearing a single or just two ipsilateral positive nodes (designated cN1/cN2a or cN2b(2/x) patients either by CT (CT group) or US alone (US group) or in a group combining findings of CT and US (CTUS group)) received an ipsi-ND (I-V) and a contra-ND (I-IV). 78% of the LNs were sent individually for routine histopathological examination; the remaining were dissected and analyzed per neck level. RESULTS: Upon the analysis of 1.670 LNs of 57 patients, the exact location of pathology proven LN metastases in cN1 patients was more precisely predicted by US compared to CT with confirmed findings only in levels IA, IB und IIA. Clearly decreasing the number of missed lesions, the findings in the CTUS group nearly kept the spatial reliability of the US group. The same analysis for patients with exactly two supposed ipsilateral lesions (cN2b(2/x)) yielded confirmed metastases from levels I to V for both methods individually and in combination and, therefore, render SND insufficient for these cases. CONCLUSION: Our findings stress the importance of conducting both, CT and US, in patients with primary OSCC. Only the combination of their findings warrants the application of therapeutic SND in patients with a single ipsilateral LN metastasis (cN1/cN2a patients) but not in patients with more than one lesion upon clinical staging (≥ cN2b).

Impact of increasing levels of adaptive statistical iterative reconstruction on image quality in oil-based postmortem CT angiography in coronary arteries.

INTRODUCTION: Postmortem multi-detector computed tomography (PMCT) has become an important part in forensic imaging. Modern reconstruction techniques such as iterative reconstruction (IR) are frequently used in postmortem CT angiography (PMCTA). The image quality of PMCTA depends on the strength of IR. For this purpose, we aimed to investigate the impact of different advanced IR levels on the objective and subjective PMCTA image quality. MATERIAL AND METHODS: We retrospectively analyzed the coronary arteries of 27 human cadavers undergoing whole-body postmortem CT angiography between July 2017 and March 2018 in a single center. Iterative reconstructions of the coronary arteries were processed in five different level settings (0%; 30%; 50%; 70%; 100%) by using an adaptive statistical IR method. We evaluated the objective (contrast-to-noise ratio (CNR)) and subjective image quality in several anatomical locations. RESULTS: Our results demonstrate that the increasing levels of an IR technique have relevant impact on the image quality in PMCTA scans in forensic postmortem examinations. Higher levels of IR have led to a significant reduction of image noise and therefore to a significant improvement of objective image quality (+ 70%). However, subjective image quality is inferior at higher levels of IR due to plasticized image appearance. CONCLUSION: Objective image quality in PMCTA progressively improves with increasing level of IR with the best CNR at the highest IR level. However, subjective image quality is best at low to medium levels of IR. To obtain a "classic" image appearance with optimal image quality, PMCTAs should be reconstructed at medium levels of IR.

Influence of a novel deep-learning based reconstruction software on the objective and subjective image quality in low-dose abdominal computed tomography.

OBJECTIVES: Modern reconstruction and post-processing software aims at reducing image noise in CT images, potentially allowing for a reduction of the employed radiation exposure. This study aimed at assessing the influence of a novel deep-learning based software on the subjective and objective image quality compared to two traditional methods [filtered back-projection (FBP), iterative reconstruction (IR)]. METHODS: In this institutional review board-approved retrospective study, abdominal low-dose CT images of 27 patients (mean age 38 ± 12 years, volumetric CT dose index 2.9 ± 1.8 mGy) were reconstructed with IR, FBP and, furthermore, post-processed using a novel software. For the three reconstructions, qualitative and quantitative image quality was evaluated by means of CT numbers, noise, signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR) in six different ROIs. Additionally, the reconstructions were compared using SNR, peak SNR, root mean square error and mean absolute error to assess structural differences. RESULTS: On average, CT numbers varied within 1 Hounsfield unit (HU) for the three assessed methods in the assessed ROIs. In soft tissue, image noise was up to 42% lower compared to FBP and up to 27% lower to IR when applying the novel software. Consequently, SNR and CNR were highest with the novel software. For both IR and the novel software, subjective image quality was equal but higher than the image quality of FBP-images. CONCLUSION: The assessed software reduces image noise while maintaining image information, even in comparison to IR, allowing for a potential dose reduction of approximately 20% in abdominal CT imaging. ADVANCES IN KNOWLEDGE: The assessed software reduces image noise by up to 27% compared to IR and 48% compared to FBP while maintaining the image information.The reduced image noise allows for a potential dose reduction of approximately 20% in abdominal imaging.

Dose-optimised chest computed tomography for diagnosis of Coronavirus Disease 2019 (COVID-19) - Evaluation of image quality and diagnostic impact.

OBJECTIVES: The detection of Coronavirus Disease 2019 (COVID-19) by reverse transcription polymerase chain reaction (RT-PCR) has varying sensitivity. Computed tomography (CT) of the chest can verify infection in patients with clinical symptoms and a negative test result, accelerating treatment and actions to prevent further contagion. However, CT employs ionising radiation. The purpose of this study was to evaluate protocol settings, associated radiation exposure, image quality and diagnostic performance of a low-dose CT protocol in a university hospital setting. MATERIALS AND METHODS: Chest CT examinations were performed on a single scanner (Somatom Definition Edge, Siemens Healthineers, Germany) in 105 symptomatic patients (60 male, 45 female). Images were evaluated with regard to protocol parameters, image quality, radiation exposure and diagnostic accuracy. Serial RT-PCR served as the standard of reference. Based on this reference standard sensitivity, specificity, positive and negative predictive values of CT with 95% confidence interval were calculated. RESULTS: The mean effective dose was 1.3 ± 0.4 mSv (0.7-2.9 mSv) for the patient cohort (mean age 66.6 ± 16.7 years (19-94 years), mean body mass index (BMI) 26.6 ± 5.3 kg m-2 (16-46 kg/m2)). A sensitivity of 100 [95% CI: 82-100]%, a specificity of 78 [95% CI: 68-86]%, a positive predictive value of 50 [95% CI: 33-67]% and a negative predictive value of 100 [95% CI: 95-100]% were obtained. No COVID-19 diagnoses were missed by CT. Image noise did not strongly correlate with BMI or patient diameter and was rated as average. CONCLUSIONS: We presented a robust imaging procedure with a chest CT protocol for confident diagnosis of COVID-19. Even for an overweight patient cohort, an associated radiation exposure of only 1.3 ± 0.4 mSv was achieved with sufficient diagnostic quality to exclude COVID-19.

Impact of different iterative metal artifact reduction (iMAR) algorithms on PET/CT attenuation correction after port implementation.

PURPOSE: To evaluate the effect of various interactive metal artifact reduction (iMAR) algorithms on attenuation correction in the vicinity of port chambers in PET/CT. MATERIAL AND METHODS: In this prospective study, 30 oncological patients (12 female, 18 male, mean age 59.6 ± 10.5y) with implanted port chambers undergoing 18F-FDG PET/CT were included. CT images were reconstructed with standard weighted filtered back projection (WFBP) and three different iMAR algorithms (hip, dental filling (DF) and pacemaker (PM)). PET attenuation correction was performed with all four CT datasets. SUVmean, SUVmax and HU measurements were performed in fat and muscle tissue in the vicinity of the port chamber at the location of the strongest bright and dark band artifacts. Differences between HU and SUV values across all CT- and PET-images were investigated using a paired t-test. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.008). RESULTS: In comparison to WFBP (fat: 94.2 ± 53.9 HU, muscle: 197.6 ± 49.2 HU) all three iMAR algorithms led to a decrease of HU in bright band artifacts. iMAR-DF led to a decrease of 159.2 % (fat: -51.9 ± 58.5 HU, muscle: 94.5 ± 55.3 HU), iMAR-hip of 138.3 % (fat: -30.3 ± 58.5, muscle: 70.4 ± 28.8) and iMAR-PM of 122.3 % (fat: -21.2 ± 47.2 HU, muscle: 72.5 ± 25.1 HU; for all p < 0.008). There was no significant effect of iMAR on SUV measurements in comparison to WFBP. CONCLUSION: iMAR leads to a significant change of HU values in artifacts caused by port catheter chambers in comparison to WFBP. However, no significant differences in attenuation correction and consecutive changes in SUV measurements can be observed.

Diagnostic value and forensic relevance of a novel photorealistic 3D reconstruction technique in post-mortem CT.

OBJECTIVES: Evaluation of performance and forensic relevance of a novel, photorealistic, 3D reconstruction method (cinematic rendering, (CR)) in comparison with conventional post-mortem CT (PMCT) and volume rendering (VR) technique for visualization of traumatic injuries. METHODS: 112 pathologies (fractures, soft tissue injuries and foreign bodies) from 33 human cadavers undergoing whole body PMCT after traumatic death were retrospectively analyzed. Pathologies were reconstructed with CR and VR techniques. Fractures were classified according to their dislocation. Images were evaluated according to their expressiveness and judicial relevance by two forensic pathologists using a five-level Likert-scale (1: high expressiveness, 5: low expressiveness). They decided whether CR reconstructions were suitable for judicial reviews. The detection rate of pathologies was determined by two radiologists. RESULTS: CR was more expressive than VR for all three trauma categories (p < 0.01) and than conventional CT when used for fractures with dislocation (p < 0.001), injuries of the ventral body surface (p < 0.001), and demonstration of foreign bodies (p = 0.033). CR and VR became more expressive with a higher grade of fracture dislocation (p < 0.001). 20% of all pathologies in the CR and VR reconstructions were not detectable by radiologists. CONCLUSION: CR reconstructions are superior to VR regarding the expressiveness. For fractures with substantial dislocation, soft tissue injuries, and foreign bodies in situ, CR showed a significantly better expressiveness than conventional PMCT. CR and VR have significant limitations in cases of fractures with minor dislocations and covered soft tissue injuries. ADVANCES IN KNOWLEDGE: CR is a helpful tool to present pathologies found in PMCT for judicial reviews.

Development of size-specific institutional diagnostic reference levels for computed tomography protocols in neck imaging.

PURPOSE: To develop size-specific institutional diagnostic reference levels (DRLs) for computed tomography (CT) protocols used in neck CT imaging (cervical spine CT, cervical CT angiography (CTA) and cervical staging CT) and to compare institutional to national DRLs. MATERIALS AND METHODS: Cervical CT examinations (spine, n = 609; CTA, n = 505 and staging CT, n = 184) performed between 01/2016 and 06/2017 were included in this retrospective study. For each region and examination, the volumetric CT dose index (CTDIvol) and dose-length product (DLP) were determined and binned into size bins according to patient water-equivalent diameter (dw). Linear regression analysis was performed to calculate size-specific institutional DRLs for CTDIvol and DLP, applying the 75th percentile as the upper limit for institutional DRLs. The mean institutional CTDIvol and DLP were compared to national DRLs (CTDIvol 20 mGy for cervical spine CT (DLP 300 mGycm) and cervical CTA (DLP 600 mGycm), and CTDIvol 15 mGy for cervical staging CT (DLP 330 mGycm)). RESULTS: The mean CTDIvol and DLP (±standard deviation) were 15.2 ± 4.1 mGy and 181.5 ± 88.3 mGycm for cervical spine CT; 8.1 ± 4.3 mGy and 280.2 ± 164.3 mGycm for cervical CTA; 8.6 ± 1.9 mGy and 162.8 ± 85.0 mGycm for cervical staging CT. For all CT protocols, there was a linear increase in CTDIvol and DLP with increasing dw. For the CTDIvol, size-specific institutional DRLs increased with dw from 14 to 29 mGy for cervical spine CT, from 5 to 17 mGy for cervical CTA and from 8 to 13 mGy for cervical staging CT. For the DLP, size-specific institutional DRLs increased with dw from 130 to 510 mGycm for cervical spine CT, from 140 to 640 mGycm for cervical CTA and from 140 to 320 mGycm for cervical staging CT. Institutional DRLs were lower than national DRLs by 81% and 67% for cervical spine CT (dw = 17.8 cm), 43% and 51% for cervical CTA (dw = 19.5 cm) and 59% and 53% for cervical staging CT (dw = 18.8 cm) for CTDIvol and DLP, respectively. CONCLUSION: Size-specific institutional DRLs were generated for neck CT examinations. The mean institutional CTDIvol and DLP values were well below national DRLs.

Impact of different metal artifact reduction techniques on attenuation correction in 18F-FDG PET/CT examinations.

OBJECTIVE: To evaluate the impact of different metal artifact reduction (MAR) algorithms on Hounsfield unit (HU) and standardized uptake values (SUV) in a phantom setting and verify these results in patients with metallic implants undergoing oncological PET/CT examinations. METHODS AND MATERIALS: In this prospective study, PET-CT examinations of 28 oncological patients (14 female, 14 male, mean age 69.5 ± 15.2y) with 38 different metal implants were included. CT datasets were reconstructed using standard weighted filtered back projection (WFBP) without MAR, MAR in image space (MARIS) and iterative MAR (iMAR, hip algorithm). The three datasets were used for PET attenuation correction. SUV and HU measurements were performed at the site of the most prominent bright and dark band artifacts. Differences between HU and SUV values across the different reconstructions were compared using paired t-tests. Bonferroni correction was used to prevent alpha-error accumulation (p < 0.017). RESULTS: For bright band artifacts, MARIS led to a non-significant mean decrease of 12.0% (345 ± 315 HU) in comparison with WFBP (391 ± 293 HU), whereas iMAR led to a significant decrease of 68.3% (125 ± 185 HU, p < 0.017). For SUVmean, MARIS showed no significant effect in comparison with WFBP (WFBP: 0.99 ± 0.40, MARIS: 0.96 ± 0.39), while iMAR led to a significant decrease of 11.1% (0.88 ± 0.35, p < 0.017). Similar results were observed for dark band artifacts. CONCLUSION: iMAR significantly reduces artifacts caused by metal implants in CT and thus leads to a significant change of SUV measurements in bright and dark band artifacts compared with WFBP and MARIS, thus probably improving PET quantification. ADVANCES IN KNOWLEDGE: The present work indicates that MAR algorithms such as iMAR algorithm in integrated PET/CT scanners are useful to improve CT image quality as well as PET quantification in the evaluation of tracer uptake adjacent to large metal implants. A detailed analysis of oncological patients with various large metal implants using different MAR algorithms in PET/CT has not been conducted yet.

Implementation of Institutional Size-Specific Diagnostic Reference Levels for CT Angiography.

RATIONALE AND OBJECTIVES: To generate institutional size-specific diagnostic reference levels (DRLs) for computed tomography angiography (CTA) examinations and assess the potential for dose optimization compared to size-independent DRLs. MATERIALS AND METHODS: CTA examinations of the aorta, the pulmonary arteries and of the pelvis/lower extremity performed between January 2016 and January 2017 were included in our retrospective study. Water equivalent diameter (Dw) was automatically calculated for each patient. The relationship between Dw and computed tomography dose index (CTDIvol) was analyzed and the 75th percentile was chosen as the upper limit for institutional DRLs. Size-specific institutional DRLs were compared to national size-independent DRLs from Germany and the UK. RESULTS: A total of 1344 examinations were included in our study (n = 733 aortic CTA, n = 406 pulmonary CTA, n = 205 pelvic/lower extremity CTA). Mean Dw was 26 ± 9 cm and mean CTDIvol was 7.0 ± 4.6 mGy. For all CTA protocols, there was a linear progression of CTDIvol with increasing Dw with an R²â€¯= 0.95 in aortic CTA, R²â€¯= 0.94 in pulmonary CTA and R²â€¯= 0.93 in pelvic/lower extremity CTA. Median CTDIvol increased by 0.57 mGy per additional cm Dw in aortic CTA, by 1.1 mGy in pulmonary CTA and by 0.31 mGy in pelvic/lower extremity CTA. Institutional DRLs were lower than national DRLs for average size patients (aortic CTA: Dw 28.2 cm, CTDIvol 7.6 mGy; pulmonary CTA, Dw 27.9 cm, CTDIvol 11.8 mGy; pelvic/lower extremity CTA, Dw 20.0 cm, CTDIvol 6.4 mGy). More dose outliers in small patients were detected with size-specific DRLs compared to national size-independent DRLs (56.4% vs 16.2%). CONCLUSION: We implemented institutional size-specific DRLs for CTA examinations which enabled a more precise analysis compared to national sizeindependent DRLs.

Noise insertion in CT for cocaine body packing: where is the limit of extensive dose reduction?

BACKGROUND: To evaluate the detection rate and image quality in CT-body-packer-screening at different radiation-dose levels and to determine a dose threshold that enables a reliable detection of incorporated body packs and incidental findings with a maximum of dose saving. MATERIALS AND METHODS: We retrospectively included 27 individuals who underwent an abdominal CT with automated exposure control due to suspected body packing. CT images were reconstructed at different radiation-dose levels of 50%, 10, 5% and 1% using iterative reconstructions. All 135 CT reconstructions were evaluated by three independent readers. Reviewers determined the presence of foreign bodies and evaluated the image quality using a 5-point ranking scale. In addition, visualization of incidental findings was assessed. RESULTS: A threshold of 5% (effective dose 0.11 ± 0.07 mSv) was necessary to correctly identify all 27 patients with suspected body packing. Extensive noise insertion to a dose level of 1% (0.02 ± 0.01 mSV) led to false-positive solid cocaine findings in three patients. Image quality was comparable between 100 and 50%. The threshold for correct identification of incidental findings was 10% of the initial dose (effective dose 0.21 ± 0.13 mSv). CONCLUSIONS: Our results indicate that dose of abdominal CT for the detection of intracorporeal cocaine body packets can be markedly reduced to up to 5% of the initial dose while still providing sufficient image quality to detect ingested body packets. However, a minimum effective dose of 0.21 mSv (10% of initial dose) seems to be required to properly identify incidental findings.

Performance and clinical impact of machine learning based lung nodule detection using vessel suppression in melanoma patients.

PURPOSE: To evaluate performance and the clinical impact of a novel machine learning based vessel-suppressing computer-aided detection (CAD) software in chest computed tomography (CT) of patients with malignant melanoma. MATERIALS AND METHODS: We retrospectively included consecutive malignant melanoma patients with a chest CT between 01/2015 and 01/2016. Machine learning based CAD software was used to reconstruct additional vessel-suppressed axial images. Three radiologists independently reviewed a maximum of 15 lung nodules per patient. Vessel-suppressed reconstructions were reviewed independently and results were compared. Follow-up CT examinations and clinical follow-up were used to assess the outcome. Impact of additional nodules on clinical management was assessed. RESULTS: In 46 patients, vessel-suppressed axial images led to the detection of additional nodules in 25/46 (54.3%) patients. CT or clinical follow up was available in 25/25 (100%) patients with additionally detected nodules. 2/25 (8%) of these patients developed new pulmonary metastases. None of the additionally detected nodules were found to be metastases. None of the lung nodules detected by the radiologists was missed by the CAD software. The mean diameter of the 92 additional nodules was 1.5 ±â€¯0.8 mm. The additional nodules did not affect therapeutic management. However, in 14/46 (30.4%) of patients the additional nodules might have had an impact on the radiological follow-up recommendations. CONCLUSION: Machine learning based vessel suppression led to the detection of significantly more lung nodules in melanoma patients. Radiological follow-up recommendations were altered in 30% of the patients. However, all lung nodules turned out to be non-malignant on follow-up.

Age-related apparent diffusion coefficients of lumbar vertebrae in healthy children at 1.5 T.

BACKGROUND: Diffusion-weighted magnetic resonance imaging with apparent diffusion coefficient (ADC) calculation is important for detecting bone marrow pathologies. OBJECTIVE: To investigate age-related differences of lumbar vertebral body ADC to establish normal values for healthy children. MATERIALS AND METHODS: Forty-nine healthy children without any history of oncological or hematological diseases (10.2±4.7 years, range: 0-20 years) were included in this retrospective study. All magnetic resonance imaging (MRI) examinations were performed at 1.5 T and with similar scan parameters. The diffusion-weighted sequences were performed with b values of 50, 400 and 800 s/mm2. ADC values were measured by placing regions of interest at three different levels within each lumbar vertebral body (L1 to L5). ADC values were analyzed for different age groups (0-2 years, 3-6 years, 7-11 years, 12-14 years, 15-20 years), for each vertebral and intravertebral level. RESULTS: The mean ADC of the whole study group was 0.60±0.09 × 10-3 mm2/s. Children between the ages of 12 and 14 years had significantly higher ADC compared to the other age groups (P≤0.0003). ADC values were significantly higher in the 1st lumbar vertebral body compared to the other levels of the lumbar spine (P<0.005) with the exception of L5, and in the upper third of the vertebral bodies compared to the middle or lower thirds (P≤0.003). CONCLUSION: The age-, vertebral- and intravertebral level-dependent differences in ADC suggest a varying composition and cellularity in different age groups and in different locations.