Research ArticleTheranostics

qPSMA: Semiautomatic Software for Whole-Body Tumor Burden Assessment in Prostate Cancer Using 68Ga-PSMA11 PET/CT

Andrei Gafita, Marie Bieth, Markus Krönke, Giles Tetteh, Fernando Navarro, Hui Wang, Elisabeth Günther, Bjoern Menze, Wolfgang A. Weber and Matthias Eiber
Journal of Nuclear Medicine September 2019, 60 (9) 1277-1283; DOI: https://doi.org/10.2967/jnumed.118.224055

Article Figures & Data

Figures

  • FIGURE 1.
    FIGURE 1.

    The 6-step workflow of qPSMA. First, bone mask (A) and normal-uptake mask (B) are automatically computed. Then, SUVthr_st is semiautomatically computed from liver background activity (C). Bone lesions are segmented using SUVthr_bone (D), whereas soft-tissue lesions are segmented using SUVthr_st, previously calculated at third step (E). Finally, output parameters are obtained by performing general statistics (F).

  • FIGURE 2.
    FIGURE 2.

    Examples of manual corrections in 2 metastatic castration-resistant prostate cancer patients. (A) Because of their large connections with intestine, retroperitoneal lymph nodes were wrongly classified as having normal uptake and not considered when SUVthr_st was applied. After correction of normal-uptake label, lymph nodes were segmented as soft-tissue lesions. (B) Ureter segmented as soft-tissue lesions and manually changed to normal-uptake label.

  • FIGURE 3.
    FIGURE 3.

    Bland–Altman plot of qPSMA and METAVOL agreement on semiautomatic computation of SUVthr_st. Solid line indicates average mean difference, and dotted lines delineate 95% limits of agreement (mean ± 1.96 × SD). No systematic difference between the 2 software programs was found.

  • FIGURE 4.
    FIGURE 4.

    Bland–Altman plots for tumor volume (A), total lesion (B), SUVmean (C), and SUVmax (D) from 68 lesions segmented with qPSMA and Syngo.via software. Solid lines indicate average mean difference, and dotted lines delineate 95% limits of agreement (mean ± 1.96 × SD).

Tables

  • TABLE 1

    Patient Characteristics

    CharacteristicData
    Patients (n)20
    Age (y)
     Mean73
     Range65–84
    PSA (ng/mL)
     Mean369
     Range1–2,222
    Site of metastasis (n)
     Lymph node, overall12
     Lymph node only1
     Bone, overall19
     Bone only1
     Bone and lymph node12
     Local recurrence4
     Visceral, overall3
  • TABLE 2

    Intra- and Interobserver Analyses

    Intraobserver analysisInterobserver analysis
    Output parameterRead 1 vs. 2Difference (%)ICCUser 1 vs. 2Difference (%)ICC
    bPSMA-TV (mL)801.9 vs. 800.4−2.22 (−5.72;1.25)1.000 (0.999;1.000)801.9 vs. 800.12.53 (−2.60;7.68)1.000 (1.000;1.000)
    bPSMA-TL6397 vs. 6393−2.94 (−7.75;1.86)1.000 (0.999;1.000)61397 vs. 63922.37 (−1.93;6.68)1.000 (1.000;1.000)
    bPSMA SUVmean7.34 vs. 7.39−0.73 (−2.24;0.77)0.998 (0.998;1.000)7.34 vs. 7.33−0.16 (−1.99;1.67)0.998 (0.996;0.999)
    bPSMA SUVmax38.43 vs. 38.45−0.07 (−0.38;0.22)1.000 (0.999;1.000)38.43 vs. 38.430.05 (−0.20;0.31)1.000 (1.000;1.000)
    stPSMA-TV (mL)67.8 vs. 68.63.10 (−8.24;14.45)1.000 (0.999;1.000)67.8 vs. 67.19.05 (−1.49;19.61)0.999 (0.998;1.000)
    stPSMA-TL1026 vs. 10335.22 (−4.87;15.31)1.000 (0.999;1.000)1026 vs. 10168.70 (−1.37;18.77)1.000 (0.999;1.000)
    stPSMA SUVmean9.95 vs. 9.96−0.43 (−1.86;0.98)1.000 (0.999;1.000)9.95 vs.9.92−0.49 (−1.88;0.90)0.999 (0.996;0.999)
    stPSMA SUVmax31.23 vs. 31.200.18 (−0.15;0.53)1.000 (1.000;1.000)31.23 vs. 33.210.32 (−0.25;0.89)1.000 (1.000;1.000)

    • Data are mean; 95%CIs are in parentheses. P values on paired t testing are all >0.05

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