Accuracy of SPECT/CT-based lung dose calculation for Holmium-166 hepatic radioembolization before OSEM convergence

Improving MRI-based dosimetry for holmium-166 transarterial radioembolization using a nonrigid image registration for voxelwise Δ R 2 ∗ $\Delta R_2^*$ calculation

BACKGROUND

Transarterial radioembolization (TARE) is a treatment modality for liver tumors during which radioactive microspheres are injected into the hepatic arterial system. These microspheres distribute throughout the liver as a result of the blood flow until they are trapped in the arterioles because of their size. Holmium-166 (¹⁶⁶ Ho)-loaded microspheres used for TARE can be visualized and quantified with MRI, as holmium is a paramagnetic metal and locally increases the transverse relaxation rate R 2 ∗ $R_2^*$ . The current ¹⁶⁶ Ho quantification method does not take regional differences in baseline R 2 ∗ $R_2^*$ values (such as between tumors and healthy tissue) into account, which intrinsically results in a systematic error in the estimated absorbed dose distribution. As this estimated absorbed dose distribution can be used to predict response to treatment of tumors and potential toxicity in healthy tissue, a high accuracy of absorbed dose estimation is required.

PURPOSE

To evaluate pre-existing differences in R 2 ∗ $R_2^*$ distributions between tumor tissue and healthy tissue and assess the feasibility and accuracy of voxelwise subtraction-based Δ R 2 ∗ $\Delta R_2^*$ calculation for MRI-based dosimetry of holmium-166 transarterial radioembolization (¹⁶⁶ Ho TARE).

METHODS

MRI data obtained in six patients who underwent ¹⁶⁶ Ho TARE of the liver as part of a clinical study was retrospectively evaluated. Pretreatment differences in R 2 ∗ $R_2^*$ distributions between tumor tissue and healthy tissue were characterized. Same-day pre- and post-treatment R 2 ∗ $R_2^*$ maps were aligned using a deformable registration algorithm and subsequently subtracted to generate voxelwise Δ R 2 ∗ $\Delta R_2^*$ maps and resultant absorbed dose maps. Image registration accuracy was quantified using the dice similarity coefficient (DSC), relative overlay (RO), and surface dice (≤4 mm; SDSC). Voxelwise subtraction-based absorbed dose maps were quantitatively (root-mean-square error, RMSE) and visually compared to the current MRI-based mean subtraction method and routinely used SPECT-based dosimetry.

RESULTS

Pretreatment R 2 ∗ $R_2^*$ values were lower in tumors than in healthy liver tissue (mean 36.8 s^-1 vs. 55.7 s^-1 , P = 0.004). Image registration improved the mean DSC of 0.83 (range: 0.70-0.88) to 0.95 (range: 0.92-0.97), mean RO of 0.71 (range 0.53-0.78) to 0.90 (range: 0.86-0.94), and mean SDSC ≤4 mm of 0.47 (range: 0.28-0.67) to 0.97 (range: 0.96-0.98). Voxelwise subtraction-based absorbed dose maps yielded a higher tumor-absorbed dose (median increase of 9.0%) and lower healthy liver-absorbed dose (median decrease of 13.8%) compared to the mean subtraction method. Voxelwise subtraction-based absorbed dose maps corresponded better to SPECT-based absorbed dose maps, reflected by a lower RMSE in three of six patients.

CONCLUSIONS

Voxelwise subtraction presents a robust alternative method for MRI-based dosimetry of ¹⁶⁶ Ho microspheres that accounts for pre-existing R 2 ∗ $R_2^*$ differences, and appears to correspond better with SPECT-based dosimetry compared to the currently implemented mean subtraction method.

Correlation analysis of epicardial adipose tissue volume quantified by computed tomography images and coronary heart disease under optimized reconstruction algorithm

Objectives:

This paper was aimed to explore the adoption value of low-dose computed tomography (CT) imaging based on optimized ordered subset expectation maximization (OSEM) reconstruction algorithm in the correlation analysis between epicardial adipose tissue (EAT) volume and coronary heart disease (CHD).

Methods:

A total of 110 patients with CHD were selected for CT angiography (CTA) and coronary arteriography (CAG) examinations from October 2017 to October 2019. The predictive value of EAT for CHD was analyzed via receiver operating characteristic (ROC) curve.

Results:

The results showed that the iteration time and error of the improved OSEM reconstruction algorithm were better than that of MLEM algorithm under the same number of iterations. Age, smoking, hypertension, diabetes, and EAT in control group were obviously lower in contrast to those in CHD group (P<0.05). EAT in control group was (124.50±26.72) mL, and EAT in the CHD group was (159.41±38.51) mL. EAT (B=0.023, P=0.003) was an independent risk factor for CHD, which was suggested by Multiple linear regression analysis. Moreover, EAT was a risk factor for CHD, and was positively correlated with the degree and NSCV.

Conclusion:

The optimized OSEM algorithm was used to improve the reconstruction quality of low-dose CT images and used in quantitative measurement of epicardial fat volume. Results showed EAT was an independent risk factor for CHD, and was positively correlated with the number of coronary lesions and Gensini score. It was of great value for the prediction of CHD.

Gamma camera characterization at high holmium-166 activity in liver radioembolization

BACKGROUND

High activities of holmium-166 (¹⁶⁶Ho)-labeled microspheres are used for therapeutic radioembolization, ideally directly followed by SPECT imaging for dosimetry purposes. The resulting high-count rate potentially impacts dead time, affecting the image quality and dosimetric accuracy. This study assesses gamma camera performance and SPECT image quality at high ¹⁶⁶Ho activities of several GBq. To this purpose, the liver compartment, including two tumors, of an anthropomorphic phantom was filled with ¹⁶⁶Ho-chloride, with a tumor to non-tumorous liver activity concentration ratio of 10:1. Multiple SPECT/CT scans were acquired over a range of activities up to 2.7 GBq. Images were reconstructed using a commercially available protocol incorporating attenuation and scatter correction. Dead time effects were assessed from the observed count rate in the photopeak (81 keV, 15% width) and upper scatter (118 keV, 12% width) window. Post reconstruction, each image was scaled with an individual conversion factor to match the known total activity in the phantom at scanning time. The resulting activity concentration was measured in the tumors and non-tumorous liver. The image quality as a function of activity was assessed by a visual check of the absence of artifacts by a nuclear medicine physician. The apparent lung shunt fraction (nonzero due to scatter) was estimated on planar and SPECT images.

RESULTS

A 20% count loss due to dead time was observed around 0.7 GBq in the photopeak window. Independent of the count losses, the measured activity concentration was up to 100% of the real value for non-tumorous liver, when reconstructions were normalized to the known activity at scanning time. However, for tumor spheres, activity concentration recovery was ~80% at the lowest activity, decreasing with increasing activity in the phantom. Measured lung shunt fractions were relatively constant over the considered activity range.

CONCLUSIONS

At high ¹⁶⁶Ho count rate, all images, visually assessed, presented no artifacts, even at considerable dead time losses. A quantitative evaluation revealed the possibility of reliable dosimetry within the healthy liver, as long as a post-reconstruction scaling to scanning activity is applied. Reliable tumor dosimetry, instead, remained hampered by the dead time.

Artificial intelligence in radiotherapy: a technological review

Radiation therapy (RT) is widely used to treat cancer. Technological advances in RT have occurred in the past 30 years. These advances, such as three-dimensional image guidance, intensity modulation, and robotics, created challenges and opportunities for the next breakthrough, in which artificial intelligence (AI) will possibly play important roles. AI will replace certain repetitive and labor-intensive tasks and improve the accuracy and consistency of others, particularly those with increased complexity because of technological advances. The improvement in efficiency and consistency is important to manage the increasing cancer patient burden to the society. Furthermore, AI may provide new functionalities that facilitate satisfactory RT. The functionalities include superior images for real-time intervention and adaptive and personalized RT. AI may effectively synthesize and analyze big data for such purposes. This review describes the RT workflow and identifies areas, including imaging, treatment planning, quality assurance, and outcome prediction, that benefit from AI. This review primarily focuses on deep-learning techniques, although conventional machine-learning techniques are also mentioned.

The various therapeutic applications of the medical isotope holmium-166: a narrative review

Over the years, a broad spectrum of applications of the radionuclide holmium-166 as a medical isotope has been established. The isotope holmium-166 is attractive as it emits high-energy beta radiation which can be used for a therapeutic effect and gamma radiation which can be used for nuclear imaging purposes. Furthermore, holmium-165 can be visualized by MRI because of its paramagnetic properties and by CT because of its high density. Since holmium-165 has a natural abundance of 100%, the only by-product is metastable holmium-166 and no costly chemical purification steps are necessary for production of nuclear reactor derived holmium-166. Several compounds labelled with holmium-166 are now used in patients, such Ho¹⁶⁶-labelled microspheres for liver malignancies, Ho¹⁶⁶-labelled chitosan for hepatocellular carcinoma (HCC) and [¹⁶⁶Ho]Ho DOTMP for bone metastases. The outcomes in patients are very promising, making this isotope more and more interesting for applications in interventional oncology. Both drugs as well as medical devices labelled with radioactive holmium are used for internal radiotherapy. One of the treatment possibilities is direct intratumoural treatment, in which the radioactive compound is injected with a needle directly into the tumour. Numerous other applications have been developed, like patches for treatment of skin cancer and holmium labelled antibodies and peptides. The second major application that is currently clinically applied is selective internal radiation therapy (SIRT, also called radioembolization), a novel treatment option for liver malignancies. This review discusses medical drugs and medical devices based on the therapeutic radionuclide holmium-166.