Clinical and imaging features of 112 patients with irregular and flat bone osteosarcoma

Luo, Zhao‐Qing; Jing, Li; Qin, Genggeng; Zeng, Hui; He, Zilong; Pan, Derun; Li, Yulin; Chen, Weiguo; Shen, Xinping

doi:10.21037/qims-21-393

Cited by 2 publications

(1 citation statement)

References 35 publications

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“…Pelvic bone tumors account for about 3-4% of primary bone tumors, most of which are malignant. The irregular tumor shape and complex anatomical structure of the pelvis make it difficult to detect these tumors in their early stage (1)(2)(3)(4). The wide invasive range of such tumors also leads to a high mortality and disability rate during an operation (5).…”

Section: Introductionmentioning

confidence: 99%

Development of a 3D-printed pelvic CT phantom combined with fresh pathological tissues of bone tumor

Li¹,

Wu²,

Zou³

et al. 2022

Quant Imaging Med Surg

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Background: Computed tomography (CT) imaging is the most important and common means of detecting and diagnosing pelvic bone tumors. While phantoms with sufficient flexibility and anatomical realism are useful in CT research, using phantoms has been difficult for pelvic bone tumors because of the tumors' relatively large size and highly variable shape. By combining medical 3D printing technology and fresh tumor specimens, this study aimed to design such a hybrid phantom, test its imaging properties, and demonstrate its usefulness in optimizing the CT protocols.Methods: Two phantoms were designed for 2 patients with pelvic bone tumors who underwent surgical resection. One phantom was scanned with a routine pelvic CT protocol and compared against the patient image to test the imaging properties. We optimized the imaging protocol by assessing a series of varied settings on tube voltage (80, 100, 120, and 140 kVp), tube current (80, 120, and 160 to 200 mAs), and pitch factor (0.5, 0.8, 1.1, and 1.4) using the other phantom. These were assessed in comparison to the clinical reference of 140 kVp, 240 mAs, and 1.0 pitch, respectively. Image quality was quantified in terms of CT value, image noise, signal to noise ratio (SNR), and contrast to noise ratio (CNR) in various regions of interest.Results: With the routine protocol, the phantom image showed no significant difference in CT values of the bone and soft tissues and image noise compared to the patient image (all P values >0.05). With a lower tube voltage (80, 100, and 120 kVp) than the reference protocol, the CT value of bone tissue showed significant differences (all P values <0.001). No significant difference was found when applying a reduced tube current (all P values >0.05). With an increased helical pitch, pitches of 0.5, 0.8 and 1.1 were found to be comparable to those using the reference protocol (all P values >0.05). Conclusions:The 3D-printed phantom can simulate the radiological properties of tumors in the pelvis and was successfully used in imaging studies of pelvic bone tumors. According to our preliminary findings, a low-dose pelvic CT protocol with acceptable image quality is achievable using reduced tube current or increased pitch.

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Section: Introductionmentioning

confidence: 99%

Development of a 3D-printed pelvic CT phantom combined with fresh pathological tissues of bone tumor

Li¹,

Wu²,

Zou³

et al. 2022

Quant Imaging Med Surg

View full text Add to dashboard Cite

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Monitoring early responses to neoadjuvant chemotherapy and the factors affecting neoadjuvant chemotherapy responses in primary osteosarcoma

Yu¹,

Gao²,

Shi³

et al. 2023

Quant Imaging Med Surg

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Background This study sought to predict the early responses to neoadjuvant chemotherapy (NACT) of patients with primary conventional osteosarcoma (COS) using the apparent diffusion coefficient (ADC) and to evaluate the factors affecting the tumor necrosis rate (TNR). Methods The data of 41 patients who underwent magnetic resonance imaging (MRI) and diffusion-weighted imaging sequence scans before NACT, 5 days after the end of the first phase of NACT, after the end of the whole course of chemotherapy, were prospectively collected. ADC1 refers to the ADC before chemotherapy, ADC2 refers to the ADC after the first phase of chemotherapy, and ADC3 refers to the ADC before surgery. The change in values before and after the first phase of chemotherapy was calculated as follows: ADC2-1 = ADC2 − ADC1. The change in values before and after the last phase of chemotherapy was calculated as follows: ADC3-1 = ADC3 − ADC1. The change in values after the first phase and the last phase of chemotherapy was calculated as follows: ADC3-2 = ADC3 − ADC2. We recorded the patient characteristics, including age, gender, pulmonary metastasis, alkaline phosphatase (ALP), and lactate dehydrogenase (LDH). The patients were divided into the following 2 groups based on their histological TNR after postoperative: (I) the good-response group (≥90% necrosis, n=13) and (II) the poor-response group (<90% necrosis, n=28). Changes in the ADCs were compared between the good-response and poor-response groups. The different ADCs between the 2 groups were compared, and a receiver operating characteristic analysis was performed. A correlation analysis was performed to assess the correlations of the clinical features, laboratory features, and different ADCs with patients’ histopathological responses to NACT. Results The ADC2 (P<0.001), ADC3 (P=0.004), ADC3-1 (P=0.008), ADC3-2 (P=0.047), and ALP before NACT (P=0.019) were significantly higher in the good-response group than in the poor-response group. The ADC2 [area under the curve (AUC) =0.723; P=0.023], ADC3 (AUC =0.747; P=0.012), and ADC3-1 (AUC =0.761; P=0.008) showed good diagnostic performance. Based on the univariate binary logistic regression analysis, the ADC2 (P=0.022), ADC3 (P=0.009), ADC2-1 (P=0.041), and ADC3-1 (P=0.014) were correlated with the TNR. However, based on the multivariate analysis, these parameters were not significantly correlated with the TNR. Conclusions In patients with COS who are undergoing neoadjuvant chemotherapy, the ADC2 is a promisingindicator for predicting tumor response to chemotherapy in early.

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Clinical and imaging features of 112 patients with irregular and flat bone osteosarcoma

Cited by 2 publications

References 35 publications

Development of a 3D-printed pelvic CT phantom combined with fresh pathological tissues of bone tumor

Development of a 3D-printed pelvic CT phantom combined with fresh pathological tissues of bone tumor

Monitoring early responses to neoadjuvant chemotherapy and the factors affecting neoadjuvant chemotherapy responses in primary osteosarcoma

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