Clinical Comparison of Bone Scintigraphy with 99Tcm-DPD, 99Tcm-HDP and 99Tcm-MDP

Bergqvist, Lennart; Brismar, J.; Cederquist, Ebbe; Darte, L.; Naversten, Y.; Palmer, John

doi:10.1177/028418518402500310

Cited by 13 publications

(9 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In contrast, in our study, imaging was performed with another similar radiopharmaceutical 99m Tc-2,3-dicarboxypropane-1,1-diphosphonate. We did not expect this difference to have any significant effect due to comparable pharmacokinetics and accumulation patterns reported by studies conducted during the approval process of the corresponding pharmaceuticals [36][37][38].…”

Section: Discussionmentioning

confidence: 83%

Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm—Evaluation of Diagnostic Performance

Wuestemann

Hupfeld

Kupitz

et al. 2020

Cancers

View full text Add to dashboard Cite

The bone scan index (BSI), initially introduced for metastatic prostate cancer, quantifies the osseous tumor load from planar bone scans. Following the basic idea of radiomics, this method incorporates specific deep-learning techniques (artificial neural network) in its development to provide automatic calculation, feature extraction, and diagnostic support. As its performance in tumor entities, not including prostate cancer, remains unclear, our aim was to obtain more data about this aspect. The results of BSI evaluation of bone scans from 951 consecutive patients with different tumors were retrospectively compared to clinical reports (bone metastases, yes/no). Statistical analysis included entity-specific receiver operating characteristics to determine optimized BSI cut-off values. In addition to prostate cancer (cut-off = 0.27%, sensitivity (SN) = 87%, specificity (SP) = 99%), the algorithm used provided comparable results for breast cancer (cut-off 0.18%, SN = 83%, SP = 87%) and colorectal cancer (cut-off = 0.10%, SN = 100%, SP = 90%). Worse performance was observed for lung cancer (cut-off = 0.06%, SN = 63%, SP = 70%) and renal cell carcinoma (cut-off = 0.30%, SN = 75%, SP = 84%). The algorithm did not perform satisfactorily in melanoma (SN = 60%). For most entities, a high negative predictive value (NPV ≥ 87.5%, melanoma 80%) was determined, whereas positive predictive value (PPV) was clinically not applicable. Automatically determined BSI showed good sensitivity and specificity in prostate cancer and various other entities. Particularly, the high NPV encourages applying BSI as a tool for computer-aided diagnostic in various tumor entities.

show abstract

Section: Discussionmentioning

confidence: 83%

Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm—Evaluation of Diagnostic Performance

Wuestemann

Hupfeld

Kupitz

et al. 2020

Cancers

View full text Add to dashboard Cite

show abstract

“…Bergqvist et al . () found higher uptake ratio of metastatic to normal bone for MDP compared with DPD and HDP in patients with prostate cancer. The observed difference was, however, minor.…”

Section: Discussionmentioning

confidence: 93%

“…Some BSI studies do not describe how the bone scans were performed (Dennis et al ., ; Reza et al ., ; Petersen et al ., ), when images from multiple hospitals were used. Previous studies have compared bone scans performed with different tracers (Bergqvist et al ., ; Fruhling et al ., ). Bergqvist et al .…”

Section: Discussionmentioning

confidence: 99%

Evaluation of changes in Bone Scan Index at different acquisition time‐points in bone scintigraphy

Kaboteh

Minarik

Reza

et al. 2018

Clin Physio Funct Imaging

View full text Add to dashboard Cite

Bone Scan Index (BSI) is a validated imaging biomarker to objectively assess tumour burden in bone in patients with prostate cancer, and can be used to monitor treatment response. It is not known if BSI is significantly altered when images are acquired at a time difference of 1 h. The aim of this study was to investigate if automatic calculation of BSI is affected when images are acquired 1 hour apart, after approximately 3 and 4 h. We prospectively studied patients with prostate cancer who were referred for bone scintigraphy according to clinical routine. The patients performed a whole-body bone scan at approximately 3 h after injection of radiolabelled bisphosphonate and a second 1 h after the first. BSI values for each bone scintigraphy were obtained using EXINI bone software. A total of 25 patients were included. Median BSI for the first acquisition was 0·05 (range 0-11·93) and for the second acquisition 0·21 (range 0-13·06). There was a statistically significant increase in BSI at the second image acquisition compared to the first (P<0·001). In seven of 25 patients (28%) and in seven of 13 patients with BSI > 0 (54%), a clinically significant increase (>0·3) was observed. The time between injection and scanning should be fixed when changes in BSI are important, for example when monitoring therapeutic efficacy.

show abstract

“…Bone scintigraphy was initially reported for facial and skull imaging, not least by Bergstedt and co-workers (65), who in seven articles in 1975-1981 described in detail bone scintigraphy of the facial skeleton. In the following years, different 99m Tc compounds were compared (66), and imaging of occult fractures became one of the main applications of bone scintigraphy (67)(68)(69). The possibility for whole-body imaging, coupled with the high sensitivity for bone remodeling, made bone scintigraphy an excellent modality for staging bone involvement in malignant disease, reported in several papers (70)(71)(72).…”

Section: Techniquesmentioning

confidence: 99%

The development of musculoskeletal radiology for 100 years as presented in the pages of Acta Radiologica

et al. 2021

View full text Add to dashboard Cite

During the last 100 years, musculoskeletal radiology has developed from bone-only radiography performed by everyone to a dedicated subspecialty, still secure in its origins in radiography but having expanded into all modalities of imaging. Like other subspecialties in radiology, it has become heavily dependent on cross-sectional and functional imaging, and musculoskeletal interventions play an important role in tumor diagnosis and treatment and in joint diseases. All these developments are reflected in the pages in Acta Radiologica, as shown in this review.

show abstract

Clinical Comparison of Bone Scintigraphy with ⁹⁹Tc^m-DPD, ⁹⁹Tc^m-HDP and ⁹⁹Tc^m-MDP

Cited by 13 publications

References 4 publications

Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm—Evaluation of Diagnostic Performance

Analysis of Bone Scans in Various Tumor Entities Using a Deep-Learning-Based Artificial Neural Network Algorithm—Evaluation of Diagnostic Performance

Evaluation of changes in Bone Scan Index at different acquisition time‐points in bone scintigraphy

The development of musculoskeletal radiology for 100 years as presented in the pages of Acta Radiologica

Contact Info

Product

Resources

About