Respiratory Motion Detection and Correction in ECG-Gated SPECT: a New Approach

Objective: Gated myocardial perfusion single-photon emission computed tomography (GSPECT) has been established as an accurate and reproducible diagnostic and prognostic technique for the assessment of myocardial perfusion and function. Respiratory motion is among the major factors that may affect the quality of myocardial perfusion imaging (MPI) and consequently the accuracy of the examination. In this study, we have proposed a new approach for the tracking of respiratory motion and the correction of unwanted respiratory motion by the use of respiratory-cardiac gated-SPECT (RC-GSPECT). In addition, we have evaluated the use of RC-GSPECT for quantitative and visual assessment of myocardial perfusion and function. Materials and Methods: Twenty-six patients with known or suspected coronary artery disease (CAD)-underwent two-day stress and rest 99mTc-Tetrofosmin myocardial scintigraphy using both conventional GSPECT and RC-GSPECT methods. The respiratory signals were induced by use of a CT real-time position management (RPM) respiratory gating interface. A PIO-D144 card, which is transistor-transistor logic (TTL) compatible, was used as the input interface for simultaneous detection of both ECG and respiration signals. Results: A total of 26 patients with known or suspected CAD were examined in this study. Stress and rest myocardial respiratory motion in the vertical direction was 8.8-16.6 mm (mean, 12.4 ± 2.9 mm) and 7.8-11.8 mm (mean, 9.5 ± 1.6 mm), respectively. The percentages of tracer intensity in the inferior, inferoseptal and septal walls as well as the inferior to lateral (I/L) uptake ratio was significantly higher with the use of RC-GSPECT as compared to the use of GSPECT (p < 0.01). In a left ventricular ejection fraction (LVEF) correlation analysis between the use of rest GSPECT and RC-GSPECT with echocardiography, better correlation was noted between RC-GSPECT and echocardiography as compared with the use of GSPECT (y = 0.9654x + 1.6514; r = 0.93, p < 0.001 versus y = 0.8046x + 5.1704; r = 0.89, p < 0.001). Nineteen (19/26) patients (73.1) showed abnormal myocardial perfusion scans with reversible regional myocardial defects; of the 19 patients, 14 (14/26) patients underwent coronary angiography. Conclusion: Respiratory induced motion can be successfully corrected simultaneously with the use of ECG-gated SPECT in MPI studies using this proposed technique. Moreover, the use of ECG-gated SPECT improved image quality, especially in the inferior and septal regions that are mostly affected by diaphragmatic attenuation. However, the effect of respiratory correction depends mainly on the patient respiratory pattern and may be clinically relevant in certain cases

Changing the tide in vitamin D testing: An 8-year review of a demand management approach

Graphical abstract Highlights • Adding a mandatory accompanying information in the Vitamin D ordering process led to a significant reduction overall orders • Given that about one third of mandatory information was incorrect, we assume that the sheer obstacle is sufficient to reduce test numbers, regardless of its type or content • We estimated potential cost savings ranging from € 101,292 to € 516,704 for a four-year perio

Expression of Tenascin C, EGFR, E-Cadherin, and TTF-1 in Medullary Thyroid Carcinoma and the Correlation with RET Mutation Status

Tenascin C expression correlates with tumor grade and indicates worse prognosis in several tumors. Epidermal growth factor receptor (EGFR) plays an important role in driving proliferation in many tumors. Loss of E-cadherin function is associated with tumor invasion and metastasis. Thyroid transcription factor-1 (TTF-1) is involved in rearranged during transfection (RET) transcription in Hirschsprung’s disease. Tenascin C, EGFR, E-cadherin, TTF-1-expression, and their correlations with RET mutation status were investigated in 30 patients with medullary thyroid carcinoma (MTC) (n = 26) or C-cell hyperplasia (n = 4). Tenascin C was found in all, EGFR in 4/26, E-cadherin in 23/26, and TTF-1 in 25/26 MTC. Tenascin C correlated significantly with tumor proliferation (overall, r = 0.61, p < 0.005; RET-mutated, r = 0.81, p < 0.01). E-cadherin showed weak correlation, whereas EGFR and TTF-1 showed no significant correlation with tumor proliferation. EGFR, E-cadherin, and TTF-1 showed weak correlation with proliferation of RET-mutated tumors. Correlation between TTF-1 and tenascin C, E-cadherin, and EGFR was r = −0.10, 0.37, and 0.21, respectively. In conclusion, MTC express tenascin C, E-cadherin, and TTF-1. Tenascin C correlates significantly with tumor proliferation, especially in RET-mutated tumors. EGFR is low, and tumors expressing EGFR do not exhibit higher proliferation. TTF-1 does not correlate with RET mutation status and has a weak correlation with tenascin C, E-cadherin, and EGFR expression

Survival in early lung cancer patients treated with high dose radiotherapy is independent of pathological confirmation

Background Approximately 15% of lung cancer patients are diagnosed in early stages. Microscopic proof of disease cannot always be obtained because of comorbidity or reluctance to undergo invasive diagnostic procedures. In the current study, survival data of patients with and without pathology are compared. Methods One hundred and sixty three patients with NSCLC I–IIb (T3 N0) treated between 2002 and 2016 were eligible: 123 (75%) had pathological confirmation of disease, whereas 40 (25%) did not. In accordance with international guidelines, both groups received radiotherapy. Comorbidity was assessed with the Charlson Comorbidity Index (CCI). Results The median follow‐up was 28.6 months (range: 0.3–162): 66 (40%) patients are still alive, while 97 (59%) patients died: 48 (29%) cancer‐related deaths and 49 (30%) from causes other than cancer. Median overall survival (OS) in patients without pathological confirmation was 58.6 months (range: 0.5–162), which did not differ from those with microscopic proof of disease (39.4 months, range: 0.3–147.5; logrank P = 0.481). Median cancer‐specific survival (CSS) also did not differ at 113.4 months (range: 0.5–162) in the non‐confirmation group (logrank P = 0.763) versus 51.5 months (range: 3.7–129.5) in patients with pathology. In Cox regression, a CCI of ≥ 3 was associated with poor OS (hazard ratio 2.0; range 1.2–3.4; P = 0.010) and CSS (hazard ratio 2.0; 1.0–4.0; P = 0.043). Conclusion OS and CSS in early lung cancer patients depend on comorbidity rather than on pathological confirmation of disease

[18F]FDG-PET/CT Radiomics and Artificial Intelligence in Lung Cancer: Technical Aspects and Potential Clinical Applications

Lung cancer is the second most common cancer and the leading cause of cancer-related death worldwide. Molecular imaging using [18F]fluorodeoxyglucose Positron Emission Tomography and/or Computed Tomography ([18F]FDG-PET/CT) plays an essential role in the diagnosis, evaluation of response to treatment, and prediction of outcomes. The images are evaluated using qualitative and conventional quantitative indices. However, there is far more information embedded in the images, which can be extracted by sophisticated algorithms. Recently, the concept of uncovering and analyzing the invisible data extracted from medical images, called radiomics, is gaining more attention. Currently, [18F]FDG-PET/CT radiomics is growingly evaluated in lung cancer to discover if it enhances the diagnostic performance or implication of [18F]FDG-PET/CT in the management of lung cancer. In this review, we provide a short overview of the technical aspects, as they are discussed in different articles of this special issue. We mainly focus on the diagnostic performance of the [18F]FDG-PET/CT‐based radiomics and the role of artificial intelligence in non-small cell lung cancer, impacting the early detection, staging, prediction of tumor subtypes, biomarkers, and patient's outcomes

[¹⁸F]FDG-PET/CT radiomics and artificial intelligence in lung cancer: Technical aspects and potential clinical applications

Lung cancer is the second most common cancer and the leading cause of cancer-related death worldwide. Molecular imaging using [18F]fluorodeoxyglucose Positron Emission Tomography and/or Computed Tomography ([18F]FDG-PET/CT) plays an essential role in the diagnosis, evaluation of response to treatment, and prediction of outcomes. The images are evaluated using qualitative and conventional quantitative indices. However, there is far more information embedded in the images, which can be extracted by sophisticated algorithms. Recently, the concept of uncovering and analyzing the invisible data extracted from medical images, called radiomics, is gaining more attention. Currently, [18F]FDG-PET/CT radiomics is growingly evaluated in lung cancer to discover if it enhances the diagnostic performance or implication of [18F]FDG-PET/CT in the management of lung cancer. In this review, we provide a short overview of the technical aspects, as they are discussed in different articles of this special issue. We mainly focus on the diagnostic performance of the [18F]FDG-PET/CT-based radiomics and the role of artificial intelligence in non-small cell lung cancer, impacting the early detection, staging, prediction of tumor subtypes, biomarkers, and patient's outcomes