RESUMO
OBJECTIVES: To evaluate a novel calcium-only imaging technique (VCa) with subtracted bone marrow in osteoporosis in dual-layer CT (DLCT) compared to conventional CT images (CI) and dual-energy X-ray absorptiometry (DXA). MATERIAL AND METHODS: Images of a multi-energy CT phantom with calcium inserts, quantitative CT calibration phantom, and of 55 patients (mean age: 64.6 ± 11.5 years) were acquired on a DLCT to evaluate bone mineral density (BMD). CI, calcium-suppressed images, and VCa were calculated. For investigating the association of VCa and CI with DXA a subsample of 30 patients (<90 days between DXA and CT) was used. Multiple regression analysis was performed to identify further factors improving the prediction of DXA BMD. RESULTS: The calcium concentrations of the CT phantom inserts were significantly associated with CT numbers from VCa (R2 = 0.94) and from CI (R2 = 0.89-0.92). VCa showed significantly higher CT numbers than CI in the phantom (p ≤ 0.001) and clinical setting (p < 0.001). CT numbers from VCa were significantly associated with CI (R2 = 0.95, p < 0.001) and with DXA (R2 = 0.31, p = 0.007), whereas no significant association between DXA and CI was found. Prediction of DXA BMD based on CT numbers derived from VCa yielded R2 = 0.76 in multiple regression analysis. ROC for the differentiation of normal from pathologic BMD in VCa yielded an AUC of 0.7, and a cut-off value of 126HU (sensitivity: 0.90; specificity: 0.47). CONCLUSION: VCa images showed better agreement with DXA and known calcium concentrations than CI, and could be used to estimate BMD. A VCa cut-off of 126HU could be used to identify abnormal bone mineral density.
RESUMO
OBJECTIVES: To compare metal artifacts and evaluation of metal artifact reduction algorithms during probe positioning in computed tomography (CT)-guided microwave ablation (MWA), cryoablation (CRYO), and radiofrequency ablation (RFA). MATERIALS AND METHODS: Using CT guidance, individual MWA, CRYO, and RFA ablation probes were placed into the livers of 15 pigs. CT imaging was then performed to determine the probe's position within the test subject's liver. Filtered back projection (B30f) and iterative reconstructions (I30-1) were both used with and without dedicated iterative metal artifact reduction (iMAR) to generate images from the initial data sets. Semi-automatic segmentation-based quantitative evaluation was conducted to estimate artifact percentage within the liver, while qualitative evaluation of metal artifact extent and overall image quality was performed by two observers using a 5-point Likert scale: 1-none, 2-mild, 3-moderate, 4-severe, 5-non-diagnostic. RESULTS: Among MWA, RFA, and CRYO, compared with non-iMAR in B30f reconstruction, the largest extent of artifact volume percentages were observed for CRYO (11.5-17.9%), followed by MWA (4.7-6.6%) and lastly in RFA (5.5-6.2%). iMAR significantly reduces metal artifacts for CRYO and MWA quantitatively (p = 0.0020; p = 0.0036, respectively) and qualitatively (p = 0.0001, p = 0.0005), but not for RFA. No significant reduction in metal artifact percentage was seen after applying iterative reconstructions (p > 0.05). Noise, contrast-to-noise-ratio, or overall image quality did not differ between probe types, irrespective of the application of iterative reconstruction and iMAR. CONCLUSION: A dedicated metal artifact algorithm may decrease metal artifacts and improves image quality significantly for MWA and CRYO probes. Their application alongside with dedicated metal artifact algorithm should be considered during CT-guided positioning.
Assuntos
Artefatos , Criocirurgia , Ablação por Radiofrequência , Tomografia Computadorizada por Raios X , Tomografia Computadorizada por Raios X/métodos , Algoritmos , Imageamento de Micro-Ondas , Suínos , AnimaisRESUMO
BACKGROUND: Imaging of the postoperative shoulder joint includes complex, diagnostically challenging changes regarding the anatomical structures. OBJECTIVES: Case-based presentation of common surgical procedures, expected postoperative findings, and typical complications. MATERIALS AND METHODS: Interdisciplinary evaluation of (didactically instructive) cases and discussion of pertinent literature and expert opinions. RESULTS: Presentation of normal postoperative findings and complications after subacromial decompression, surgical treatment of rotator cuff lesions, SLAP (superior labral anterior to posterior) lesions/lesions of the long biceps tendon, Bankart lesions as well as instability-related procedures and after shoulder arthroplasty. Discussion of the appropriate use of imaging methods with a focus on magnetic resonance imaging (MRI), which are supplemented by computed tomography (CT), and conventional xray images. CONCLUSION: The broad spectrum of complex findings as well as the evermore developing and thereby changing surgical procedures result in significant challenges in the radiological evaluation of the postoperative shoulder joint. To differentiate physiological reactions from pathological changes it is necessary to have general knowledge of the common surgical procedures, expected postoperative findings and possible complications. A variety imaging modalities can be used to further advance diagnostic precision.
Assuntos
Lesões do Manguito Rotador , Lesões do Ombro , Articulação do Ombro , Ombro , Tomografia Computadorizada por Raios X , Humanos , Período Pós-Operatório , Manguito Rotador/cirurgia , Lesões do Manguito Rotador/diagnóstico por imagem , Ombro/diagnóstico por imagem , Lesões do Ombro/diagnóstico por imagem , Articulação do Ombro/diagnóstico por imagemRESUMO
OBJECTIVES: To compare image quality and metal artifact reduction between virtual monochromatic spectral imaging (VMSI), linearly blended dual-energy (DE) and single-energy (SE) images, each with and without dedicated iterative metal artifact reduction (iMAR) for CT-guided biopsy. MATERIALS AND METHODS: A biopsy trocar was positioned in the liver of six pigs. DE (Sn140/100kVp) and SE (120kVp/200mAs) acquisitions were performed with equivalent dose. From dual-energy datasets DE Q30-3 images and VMSI between 40-180 keV in steps of 20 keV were generated. From SE datasets I30-3 images were reconstructed. All images were reconstructed with and without iMAR. Objective image quality was analyzed applying density measurements at standardized positions (e.g. trocar tip and liver parenchyma adjacent to the trocar tip) and semi-automated threshold based segmentation. Subjective image quality was performed using semi-quantitative scores. Analyses were performed by two observers. RESULTS: At the trocar tip quantitative image analysis revealed significant difference in CT numbers between reconstructions with iMAR compared to reconstructions without iMAR for VMSI at lower keV levels (80 and 100 keV; p = 0.03) and DE (p = 0.03). For liver parenchyma CT numbers were significantly higher in VMSI at high keV compared to low keV (p≤0.01). VMSI at high keV also showed higher CT numbers compared to DE and SE images, though not the level of statistical significance. The best signal-to-noise ratio for VMSI was at 80 keV and comparable to DE and SE. Noise was lowest at 80 keV and lower than in DE and SE. Subjective image quality was best with VMSI at 80 keV regardless of the application of iMAR. iMAR significantly improved image quality at levels of 140 keV and 160 keV. Interreader-agreement was good for quantitative and qualitative analysis. CONCLUSION: iMAR improved image quality in all settings. VMSI with iMAR provided metal artifact reduction and better image quality at 80 keV and thus could improve the accurate positioning in CT-guided needle biopsy. In comparison, DE imaging did not improve image quality compared to SE.
Assuntos
Biópsia por Agulha , Processamento de Imagem Assistida por Computador/métodos , Biópsia Guiada por Imagem , Fígado/diagnóstico por imagem , Tomografia Computadorizada por Raios X , Algoritmos , Animais , Artefatos , Variações Dependentes do Observador , Interpretação de Imagem Radiográfica Assistida por Computador/métodos , Imagem Radiográfica a Partir de Emissão de Duplo Fóton , Razão Sinal-Ruído , Suínos , Veia Cava Inferior/diagnóstico por imagemRESUMO
In clinical ion beam therapy, protons as well as heavier ions such as carbon are used for treatment. For protons, ß(+)-emitters are only induced by fragmentation reactions in the target (target fragmentation), whereas for heavy ions, they are additionally induced by fragmentations of the projectile (further referred to as autoactivation). An approach utilizing these processes for treatment verification, by comparing measured Positron Emission Tomography (PET) data to predictions from Monte Carlo simulations, has already been clinically implemented. For an accurate simulation, it is important to consider the biological washout of ß(+)-emitters due to vital functions. To date, mathematical expressions for washout have mainly been determined by using radioactive beams of (10)C- and (11)C-ions, both ß(+)-emitters, to enhance the counting statistics in the irradiated area. Still, the question of how the choice of projectile (autoactivating or non-autoactivating) influences the washout coefficients, has not been addressed. In this context, an experiment was carried out at the Heidelberg Ion Beam Therapy Center with the purpose of directly comparing irradiation-induced biological washout coefficients in mice for protons and (12)C-ions. To this aim, mice were irradiated in the brain region with protons and (12)C-ions and measured after irradiation with a PET/CT scanner (Siemens Biograph mCT). After an appropriate waiting time, the mice were sacrificed, then irradiated and measured again under similar conditions. The resulting data were processed and fitted numerically to deduce the main washout parameters. Despite the very low PET counting statistics, a consistent difference could be identified between (12)C-ion and proton irradiated mice, with the (12)C data being described best by a two component fit with a combined medium and slow washout fraction of 0.50 ± 0.05 and the proton mice data being described best by a one component fit with only one (slow) washout fraction of 0.73 ± 0.06.