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Research ArticleClinical Investigation
Open Access

Composite Prediction Score to Interpret Bone Focal Uptake in Hormone-Sensitive Prostate Cancer Patients Imaged with [18F]PSMA-1007 PET/CT

Matteo Bauckneht, Francesca D’Amico, Domenico Albano, Michele Balma, Camilla Cabrini, Francesco Dondi, Tania Di Raimondo, Virginia Liberini, Luca Sofia, Simona Peano, Mattia Riondato, Giuseppe Fornarini, Riccardo Laudicella, Luca Carmisciano, Egesta Lopci, Roberta Zanca, Marcello Rodari, Stefano Raffa, Maria Isabella Donegani, Daniela Dubois, Leonardo Peñuela, Cecilia Marini, Francesco Bertagna, Alberto Papaleo, Silvia Morbelli, Gianmario Sambuceti, Marta Ponzano and Alessio Signori
Journal of Nuclear Medicine September 2024, jnumed.124.267751; DOI: https://doi.org/10.2967/jnumed.124.267751
Matteo Bauckneht
1Department of Health Sciences, University of Genova, Genova, Italy;
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Francesca D’Amico
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Domenico Albano
3Nuclear Medicine, ASST Spedali Civili di Brescia, Brescia, Italy;
4University of Brescia, Brescia, Italy;
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Michele Balma
5Nuclear Medicine, S. Croce e Carle Hospital, Cuneo, Italy;
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Camilla Cabrini
1Department of Health Sciences, University of Genova, Genova, Italy;
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Francesco Dondi
3Nuclear Medicine, ASST Spedali Civili di Brescia, Brescia, Italy;
4University of Brescia, Brescia, Italy;
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Tania Di Raimondo
1Department of Health Sciences, University of Genova, Genova, Italy;
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Virginia Liberini
5Nuclear Medicine, S. Croce e Carle Hospital, Cuneo, Italy;
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Luca Sofia
1Department of Health Sciences, University of Genova, Genova, Italy;
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Simona Peano
5Nuclear Medicine, S. Croce e Carle Hospital, Cuneo, Italy;
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Mattia Riondato
1Department of Health Sciences, University of Genova, Genova, Italy;
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Giuseppe Fornarini
6Medical Oncology 1, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Riccardo Laudicella
7Nuclear Medicine, Department of Biomedical and Dental Sciences and Morpho-Functional Imaging, University of Messina, Messina, Italy;
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Luca Carmisciano
8Department of Clinical and Experimental Medicine University of Pisa, Pisa, Italy;
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Egesta Lopci
9Nuclear Medicine, IRCCS, Humanitas Research Hospital, Rozzano, Italy;
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Roberta Zanca
9Nuclear Medicine, IRCCS, Humanitas Research Hospital, Rozzano, Italy;
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Marcello Rodari
9Nuclear Medicine, IRCCS, Humanitas Research Hospital, Rozzano, Italy;
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Stefano Raffa
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Maria Isabella Donegani
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Daniela Dubois
1Department of Health Sciences, University of Genova, Genova, Italy;
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Leonardo Peñuela
1Department of Health Sciences, University of Genova, Genova, Italy;
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Cecilia Marini
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
10Institute of Molecular Bioimaging and Physiology, National Research Council, Milan, Italy;
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Francesco Bertagna
3Nuclear Medicine, ASST Spedali Civili di Brescia, Brescia, Italy;
4University of Brescia, Brescia, Italy;
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Alberto Papaleo
5Nuclear Medicine, S. Croce e Carle Hospital, Cuneo, Italy;
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Silvia Morbelli
11Nuclear Medicine, AOU Città della Salute e della Scienza, Turin, Italy; and
12Department of Medical Sciences, University of Turin, Turin, Italy
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Gianmario Sambuceti
1Department of Health Sciences, University of Genova, Genova, Italy;
2Nuclear Medicine, IRCCS Ospedale Policlinico San Martino, Genova, Italy;
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Marta Ponzano
1Department of Health Sciences, University of Genova, Genova, Italy;
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Alessio Signori
1Department of Health Sciences, University of Genova, Genova, Italy;
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  • FIGURE 1.
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    FIGURE 1.

    Patient inclusion flow chart shows patient selection. Center A: University of Genova; Center B: University of Brescia; Center C: S. Croce e Carle Hospital, Cuneo; Center D: Humanitas Research Hospital, Rozzano. CRPC = castration-resistant prostate cancer.

  • FIGURE 2.
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    FIGURE 2.

    Model discrimination. Receiver-operating-characteristic (ROC) curve (red line) shows mean cvAUC, resulting after 10-fold cross-validation (dashed lines).

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    FIGURE 3.

    Internal calibration plot shows deviation from 45° line of perfect fit (red) at 95% CI (light gray) and 99% CI (dark gray).

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    FIGURE 4.

    Emblematic examples of bone uptake of [18F]PSMA-1007 lead to varying probabilities of bone metastases when BUMP score is applied. According to BUMP score results, 4 cases with increasing probabilities of bone metastases are shown in panels top to bottom.

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    FIGURE 5.

    Decision-curve analysis demonstrates clinical net benefit against threshold probability associated with using BUMP score for interpreting focal bone uptake in hormone-sensitive PCa patients imaged with [18F]PSMA-1007 PET/CT.

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    TABLE 1.

    Clinical Characteristics and Imaging Data for Bone Uptake of [18F]PSMA-1007

    Training cohort (total n = 448)External validation cohort (total n = 89)
    Clinical setting
     Primary255 (56.9)24 (27.0)
     Restaging193 (43.1)65 (73.0)
    Initial PSA (ng/mL)10.2 (6.3–22.9)10.6 (5.6–227)
    ISUP grade group
     125 (5.6)16 (18.0)
     299 (22.1)6 (6.7)
     3114 (25.5)17 (19.1)
     4112 (25.0)10 (11.2)
     566 (14.7)40 (44.9)
     Missing32 (7.1)0 (0.0)
    PSA at PET/CT (ng/mL)6.3 (1.5–16.4)3.0 (0.52–17)
    ADT at PET/CT
     No343 (76.6)63 (70.8)
     Yes104 (23.2)26 (29.2)
     Unknown1 (0.2)0 (0)
    PSMA injected dose (MBq)311 (277–342)352 (337–362)
    Uptake time (min)95.0 (90.0–117.0)73.0 (60.0–88.0)
    Bone uptake site
     Ribs145 (32.4)27 (30.3)
     Spine120 (26.7)17 (19.1)
     Pelvis132 (29.5)24 (27.0)
     Other sites51 (11.4)21 (23.6)
    HUmean192.4 (131–277.4)157 (111–248)
    HUmax663 (455–837)412 (268–669)
    SUVmax5.2 (4.0–9.7)5.6 (4–12.7)
    PSMA visual score1.0 (1.0–2.0)1.0 (1.0–3.0)
    PSMA-TV (mL)1.8 (1–3.3)1.4 (0.7–3.1)
    TL-PSMA6.6 (3.8–14.4)4.8 (2.4–14.4)
    • PSA = prostate-specific antigen; ISUP = International Society of Urological Pathology; PSMA-TV = PSMA tumor volume; TL-PSMA = total lesion PSMA.

    • Qualitative data are number and percentage. Continuous data are median and interquartile range.

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    TABLE 2.

    Univariate and Multivariate Analyses Identifying Determinants of the BUMP Score

    ParameterNonmetastatic (total n = 260)Metastatic (total n = 188)Univariate analysesMultivariate analyses
    ORPORP
    Clinical setting
     Primary staging167 (65.5)88 (34.5)1.00 (Ref)
     Restaging93 (48.2)100 (51.8)2.04 (1.18–3.52)0.010—NS
    Initial PSA (ng/mL)8.7 (6.0–16.5)14.0 (7.7–33.0)1.48 (1.16–1.88)0.001—NS
    ISUP grade group
     117 (68.0)8 (32.0)1.00 (Ref)
     277 (77.8)22 (22.2)0.61 (0.18–2.08)
     370 (61.4)44 (38.6)1.34 (0.41–4.32)
     453 (47.3)59 (52.7)2.37 (0.71–7.92)
     531 (47.0)35 (53.0)2.40 (0.70–8.26)0.009—NS
     Missing12 (37.5)20 (62.5)——
    PSA at PET/CT (ng/mL)6.2 (1.1–13.0)6.8 (3.0–27.0)1.19 (1.02–1.38)0.027—NS
    ADT at PET/CT
     No230 (67.1)113 (32.9)1.00 (Ref)1.00 (Ref)
     Yes30 (28.8)74 (71.2)5.02 (2.62–9.63)<0.0014.06 (1.91–8.67)<0.001
     Unknown0 (0)1 (100)——
    PSMA injected dose (MBq)309.0 (277.0–339.5)312.0 (281.0–343.0)1.03 (0.98–1.08)0.277
    Uptake time (min)96.0 (90.0–116.0)95.0 (90.0–117.0)1.01 (0.88–1.16)0.902
    Bone uptake site
     Ribs104 (71.7)41 (28.3)1.00 (Ref)
     Spine70 (58.3)50 (41.7)1.81 (1.19–2.76)
     Pelvis66 (50.0)66 (50.0)2.54 (1.61–3.99)
     Other sites20 (39.2)31 (60.8)3.93 (1.96–7.89)<0.001—NS
    HUmean180.6 (118.3–247.0)211.4 (150.9–320.5)1.03 (1.01–1.05)0.0011.04 (1.02–1.06)<0.001
    HUmax592.0 (420.0–790.0)744.5 (541.0–926.0)1.02 (1.01–1.02)<0.001—NS
    SUVmax4.5 (3.7–5.6)10.2 (5.2–21.9)1.35 (1.25–1.46)<0.0011.39 (1.27–1.52)<0.001
    PSMA visual score1.0 (1.0–1.0)2.0 (1.0–3.0)2.38 (1.79–3.17)<0.001—NS
    PSMA-TV (mL)*1.8 (1.1–3.0)1.8 (0.9–3.7)1.00 (0.96–1.05)0.947
    TL-PSMA*5.0 (3.4–9.2)11.1 (5.0–30.0)1.02 (1.01–1.04)0.012—NS
    • ↵* Variables were evaluated independently in multivariate analysis to avoid collinearity instability.

    • OR = odds ratio; Ref = reference value; NS = not significant; PSA = prostate-specific antigen; ISUP = International Society of Urological Pathology; PSMA-TV = PSMA tumor volume; TL-PSMA = total lesion PSMA.

    • Qualitative data are number and percentage. Continuous data are median and interquartile range. OR data are number and 95% CI in parentheses.

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    TABLE 3.

    Penalized Coefficients After 10-Fold Cross-Validation Lasso Model

    ParameterPenalized regression coefficients
    Intercept−4.660246
    ADT at time of PET/CT1.690656
    HUmean0.0043016
    SUVmax0.317027

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Composite Prediction Score to Interpret Bone Focal Uptake in Hormone-Sensitive Prostate Cancer Patients Imaged with [18F]PSMA-1007 PET/CT
Matteo Bauckneht, Francesca D’Amico, Domenico Albano, Michele Balma, Camilla Cabrini, Francesco Dondi, Tania Di Raimondo, Virginia Liberini, Luca Sofia, Simona Peano, Mattia Riondato, Giuseppe Fornarini, Riccardo Laudicella, Luca Carmisciano, Egesta Lopci, Roberta Zanca, Marcello Rodari, Stefano Raffa, Maria Isabella Donegani, Daniela Dubois, Leonardo Peñuela, Cecilia Marini, Francesco Bertagna, Alberto Papaleo, Silvia Morbelli, Gianmario Sambuceti, Marta Ponzano, Alessio Signori
Journal of Nuclear Medicine Sep 2024, jnumed.124.267751; DOI: 10.2967/jnumed.124.267751

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Composite Prediction Score to Interpret Bone Focal Uptake in Hormone-Sensitive Prostate Cancer Patients Imaged with [18F]PSMA-1007 PET/CT
Matteo Bauckneht, Francesca D’Amico, Domenico Albano, Michele Balma, Camilla Cabrini, Francesco Dondi, Tania Di Raimondo, Virginia Liberini, Luca Sofia, Simona Peano, Mattia Riondato, Giuseppe Fornarini, Riccardo Laudicella, Luca Carmisciano, Egesta Lopci, Roberta Zanca, Marcello Rodari, Stefano Raffa, Maria Isabella Donegani, Daniela Dubois, Leonardo Peñuela, Cecilia Marini, Francesco Bertagna, Alberto Papaleo, Silvia Morbelli, Gianmario Sambuceti, Marta Ponzano, Alessio Signori
Journal of Nuclear Medicine Sep 2024, jnumed.124.267751; DOI: 10.2967/jnumed.124.267751
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