Wikberg Emma, van Essen Martijn, Rydén Tobias, Svensson Johanna, Gjertsson Peter, Bernhardt Peter
Department of Medical Radiation Sciences, Institute of Clinical Sciences, Sahlgrenska Academy, University of Gothenburg, Gothenburg, Sweden.
Medical Physics and Medical Bioengineering, Sahlgrenska University Hospital, 413 45, Gothenburg, Sweden.
EJNMMI Phys. 2023 Jun 2;10(1):36. doi: 10.1186/s40658-023-00557-4.
Early cancer detection is crucial for patients' survival. The image quality in In-octreotide SPECT imaging could be improved by using Monte Carlo (MC)-based reconstruction. The aim of this observational study was to determine the detection rate of simulated liver lesions for MC-based ordered subset expectation maximization (OSEM) reconstruction compared to conventional attenuation-corrected OSEM reconstruction.
Thirty-seven SPECT/CT examinations with In-octreotide were randomly selected. The inclusion criterion was no liver lesions at the time of examination and for the following 3 years. SPECT images of spheres representing lesions were simulated using MC. The raw data of the spheres were added to the raw data of the established healthy patients in 26 of the examinations, and the remaining 11 examinations were not modified. The images were reconstructed using conventional OSEM reconstruction with attenuation correction and post filtering (fAC OSEM) and MC-based OSEM reconstruction without and with post filtering (MC OSEM and fMC OSEM, respectively). The images were visually and blindly evaluated by a nuclear medicine specialist. The criteria evaluated were liver lesion yes or no, including coordinates if yes, with confidence level 1-3. The percentage of detected lesions and accuracy (percentage of correctly classified cases), as well as tumor-to-normal tissue concentration (TNC) ratios and signal-to-noise ratios (SNRs), were evaluated.
The detection rates were 30.8% for fAC OSEM, 42.3% for fMC OSEM, and 50.0% for MC OSEM. The accuracies were 45.9% for fAC OSEM, 45.9% for fMC OSEM, and 54.1% for MC OSEM. The number of false positives was higher for fMC and MC OSEM. The observer's confidence level was higher in filtered images than in unfiltered images. TNC ratios were significantly higher, statistically, with MC OSEM and fMC OSEM than with AC OSEM, but SNRs were similar due to higher noise with MC OSEM.
One in two lesions were found using MC OSEM versus one in three using conventional reconstruction. TNC ratios were significantly improved, statistically, using MC-based reconstruction, but the noise levels increased and consequently the confidence level of the observer decreased. For further improvements, image noise needs to be suppressed.
早期癌症检测对患者的生存至关重要。通过基于蒙特卡罗(MC)的重建可以提高铟奥曲肽单光子发射计算机断层显像(SPECT)成像的图像质量。本观察性研究的目的是确定与传统衰减校正有序子集期望最大化(OSEM)重建相比,基于MC的OSEM重建对模拟肝脏病变的检测率。
随机选择37例进行铟奥曲肽SPECT/CT检查的患者。纳入标准为检查时及随后3年内无肝脏病变。使用MC模拟代表病变的球体的SPECT图像。在26例检查中,将球体的原始数据添加到已确定的健康患者的原始数据中,其余11例检查未作修改。使用带衰减校正和后置滤波的传统OSEM重建(fAC OSEM)以及不带和带后置滤波的基于MC的OSEM重建(分别为MC OSEM和fMC OSEM)对图像进行重建。由核医学专家对图像进行视觉和盲法评估。评估的标准为肝脏病变有无,若有则包括坐标,置信度为1至3级。评估检测到的病变百分比和准确性(正确分类病例的百分比),以及肿瘤与正常组织浓度(TNC)比值和信噪比(SNR)。
fAC OSEM的检测率为30.8%,fMC OSEM为42.3%,MC OSEM为50.0%。fAC OSEM的准确率为45.9%,fMC OSEM为45.9%,MC OSEM为54.1%。fMC OSEM和MC OSEM的假阳性数量更高。观察者对滤波后图像的置信度高于未滤波图像。从统计学上看,MC OSEM和fMC OSEM的TNC比值显著高于AC OSEM,但由于MC OSEM噪声较高,SNR相似。
使用MC OSEM可发现二分之一的病变,而使用传统重建只能发现三分之一的病变。从统计学上看,基于MC的重建显著提高了TNC比值,但噪声水平增加,因此观察者的置信度降低。为进一步改进,需要抑制图像噪声。