Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features?
OBJECTIVE: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS).
METHODS: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times.
RESULTS: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation.
CONCLUSIONS: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection.
Medienart: |
E-Artikel |
---|
Erscheinungsjahr: |
2023 |
---|---|
Erschienen: |
2023 |
Enthalten in: |
Zur Gesamtaufnahme - volume:15 |
---|---|
Enthalten in: |
Cancers - 15(2023), 22 vom: 19. Nov. |
Sprache: |
Englisch |
---|
Beteiligte Personen: |
Laudicella, Riccardo [VerfasserIn] |
---|
Links: |
---|
Themen: |
Generalized linear mixed model |
---|
Anmerkungen: |
Date Revised 27.11.2023 published: Electronic Citation Status PubMed-not-MEDLINE |
---|
doi: |
10.3390/cancers15225471 |
---|
funding: |
|
---|---|
Förderinstitution / Projekttitel: |
|
PPN (Katalog-ID): |
NLM364929499 |
---|
LEADER | 01000naa a22002652 4500 | ||
---|---|---|---|
001 | NLM364929499 | ||
003 | DE-627 | ||
005 | 20231226100604.0 | ||
007 | cr uuu---uuuuu | ||
008 | 231226s2023 xx |||||o 00| ||eng c | ||
024 | 7 | |a 10.3390/cancers15225471 |2 doi | |
028 | 5 | 2 | |a pubmed24n1216.xml |
035 | |a (DE-627)NLM364929499 | ||
035 | |a (NLM)38001731 | ||
035 | |a (PII)5471 | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
100 | 1 | |a Laudicella, Riccardo |e verfasserin |4 aut | |
245 | 1 | 0 | |a Can We Predict Skeletal Lesion on Bone Scan Based on Quantitative PSMA PET/CT Features? |
264 | 1 | |c 2023 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ƒaComputermedien |b c |2 rdamedia | ||
338 | |a ƒa Online-Ressource |b cr |2 rdacarrier | ||
500 | |a Date Revised 27.11.2023 | ||
500 | |a published: Electronic | ||
500 | |a Citation Status PubMed-not-MEDLINE | ||
520 | |a OBJECTIVE: The increasing use of PSMA-PET/CT for restaging prostate cancer (PCa) leads to a patient shift from a non-metastatic situation based on conventional imaging (CI) to a metastatic situation. Since established therapeutic pathways have been designed according to CI, it is unclear how this should be translated to the PSMA-PET/CT results. This study aimed to investigate whether PSMA-PET/CT and clinical parameters could predict the visibility of PSMA-positive lesions on a bone scan (BS) | ||
520 | |a METHODS: In four different centers, all PCa patients with BS and PSMA-PET/CT within 6 months without any change in therapy or significant disease progression were retrospectively selected. Up to 10 non-confluent clear bone metastases were selected per PSMA-PET/CT and SUVmax, SUVmean, PSMAtot, PSMAvol, density, diameter on CT, and presence of cortical erosion were collected. Clinical variables (age, PSA, Gleason Score) were also considered. Two experienced double-board physicians decided whether a bone metastasis was visible on the BS, with a consensus readout for discordant findings. For predictive performance, a random forest was fit on all available predictors, and its accuracy was assessed using 10-fold cross-validation performed 10 times | ||
520 | |a RESULTS: A total of 43 patients were identified with 222 bone lesions on PSMA-PET/CT. A total of 129 (58.1%) lesions were visible on the BS. In the univariate analysis, all PSMA-PET/CT parameters were significantly associated with the visibility on the BS (p < 0.001). The random forest reached a mean accuracy of 77.6% in a 10-fold cross-validation | ||
520 | |a CONCLUSIONS: These preliminary results indicate that there might be a way to predict the BS results based on PSMA-PET/CT, potentially improving the comparability between both examinations and supporting decisions for therapy selection | ||
650 | 4 | |a Journal Article | |
650 | 4 | |a PSMA PET | |
650 | 4 | |a generalized linear mixed model | |
650 | 4 | |a prediction | |
650 | 4 | |a prostate cancer | |
650 | 4 | |a staging | |
700 | 1 | |a Bauckneht, Matteo |e verfasserin |4 aut | |
700 | 1 | |a Maurer, Alexander |e verfasserin |4 aut | |
700 | 1 | |a Heimer, Jakob |e verfasserin |4 aut | |
700 | 1 | |a Gennari, Antonio G |e verfasserin |4 aut | |
700 | 1 | |a Di Raimondo, Tania |e verfasserin |4 aut | |
700 | 1 | |a Paone, Gaetano |e verfasserin |4 aut | |
700 | 1 | |a Cuzzocrea, Marco |e verfasserin |4 aut | |
700 | 1 | |a Messerli, Michael |e verfasserin |4 aut | |
700 | 1 | |a Eberli, Daniel |e verfasserin |4 aut | |
700 | 1 | |a Burger, Irene A |e verfasserin |4 aut | |
773 | 0 | 8 | |i Enthalten in |t Cancers |d 2009 |g 15(2023), 22 vom: 19. Nov. |w (DE-627)NLM198667213 |x 2072-6694 |7 nnns |
773 | 1 | 8 | |g volume:15 |g year:2023 |g number:22 |g day:19 |g month:11 |
856 | 4 | 0 | |u http://dx.doi.org/10.3390/cancers15225471 |3 Volltext |
912 | |a GBV_USEFLAG_A | ||
912 | |a GBV_NLM | ||
951 | |a AR | ||
952 | |d 15 |j 2023 |e 22 |b 19 |c 11 |