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Hamm CA, Baumgärtner GL, Padhani AR, Froböse KP, Dräger F, Beetz NL, Savic LJ, Posch H, Lenk J, Schallenberg S, Maxeiner A, Cash H, Günzel K, Hamm B, Asbach P, Penzkofer T. Reduction of false positives using zone-specific prostate-specific antigen density for prostate MRI-based biopsy decision strategies. Eur Radiol 2024:10.1007/s00330-024-10700-z. [PMID: 38538841 DOI: 10.1007/s00330-024-10700-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 02/19/2024] [Accepted: 02/22/2024] [Indexed: 04/18/2024]
Abstract
OBJECTIVES To develop and test zone-specific prostate-specific antigen density (sPSAD) combined with PI-RADS to guide prostate biopsy decision strategies (BDS). METHODS This retrospective study included consecutive patients, who underwent prostate MRI and biopsy (01/2012-10/2018). The whole gland and transition zone (TZ) were segmented at MRI using a retrained deep learning system (DLS; nnU-Net) to calculate PSAD and sPSAD, respectively. Additionally, sPSAD and PI-RADS were combined in a BDS, and diagnostic performances to detect Grade Group ≥ 2 (GG ≥ 2) prostate cancer were compared. Patient-based cancer detection using sPSAD was assessed by bootstrapping with 1000 repetitions and reported as area under the curve (AUC). Clinical utility of the BDS was tested in the hold-out test set using decision curve analysis. Statistics included nonparametric DeLong test for AUCs and Fisher-Yates test for remaining performance metrics. RESULTS A total of 1604 patients aged 67 (interquartile range, 61-73) with 48% GG ≥ 2 prevalence (774/1604) were evaluated. By employing DLS-based prostate and TZ volumes (DICE coefficients of 0.89 (95% confidence interval, 0.80-0.97) and 0.84 (0.70-0.99)), GG ≥ 2 detection using PSAD was inferior to sPSAD (AUC, 0.71 (0.68-0.74)/0.73 (0.70-0.76); p < 0.001). Combining PI-RADS with sPSAD, GG ≥ 2 detection specificity doubled from 18% (10-20%) to 43% (30-44%; p < 0.001) with similar sensitivity (93% (89-96%)/97% (94-99%); p = 0.052), when biopsies were taken in PI-RADS 4-5 and 3 only if sPSAD was ≥ 0.42 ng/mL/cc as compared to all PI-RADS 3-5 cases. Additionally, using the sPSAD-based BDS, false positives were reduced by 25% (123 (104-142)/165 (146-185); p < 0.001). CONCLUSION Using sPSAD to guide biopsy decisions in PI-RADS 3 lesions can reduce false positives at MRI while maintaining high sensitivity for GG ≥ 2 cancers. CLINICAL RELEVANCE STATEMENT Transition zone-specific prostate-specific antigen density can improve the accuracy of prostate cancer detection compared to MRI assessments alone, by lowering false-positive cases without significantly missing men with ISUP GG ≥ 2 cancers. KEY POINTS • Prostate biopsy decision strategies using PI-RADS at MRI are limited by a substantial proportion of false positives, not yielding grade group ≥ 2 prostate cancer. • PI-RADS combined with transition zone (TZ)-specific prostate-specific antigen density (PSAD) decreased the number of unproductive biopsies by 25% compared to PI-RADS only. • TZ-specific PSAD also improved the specificity of MRI-directed biopsies by 9% compared to the whole gland PSAD, while showing identical sensitivity.
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Affiliation(s)
- Charlie A Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.
- Berlin Institute of Health (BIH), Berlin, Germany.
| | - Georg L Baumgärtner
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Anwar R Padhani
- Paul Strickland Scanner Centre, Mount Vernon Hospital, Northwood, Middlesex, UK
| | - Konrad P Froböse
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Franziska Dräger
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Nick L Beetz
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Lynn J Savic
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
| | - Helena Posch
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Julian Lenk
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Simon Schallenberg
- Institute of Pathology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Andreas Maxeiner
- Department of Urology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Hannes Cash
- Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany
| | - Karsten Günzel
- Department of Urology, Vivantes Klinikum Am Urban, Berlin, Germany
| | - Bernd Hamm
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Patrick Asbach
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Tobias Penzkofer
- Department of Radiology, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
- Berlin Institute of Health (BIH), Berlin, Germany
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Hamm CA, Baumgärtner GL, Biessmann F, Beetz NL, Hartenstein A, Savic LJ, Froböse K, Dräger F, Schallenberg S, Rudolph M, Baur ADJ, Hamm B, Haas M, Hofbauer S, Cash H, Penzkofer T. Interactive Explainable Deep Learning Model Informs Prostate Cancer Diagnosis at MRI. Radiology 2023; 307:e222276. [PMID: 37039688 DOI: 10.1148/radiol.222276] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Background Clinically significant prostate cancer (PCa) diagnosis at MRI requires accurate and efficient radiologic interpretation. Although artificial intelligence may assist in this task, lack of transparency has limited clinical translation. Purpose To develop an explainable artificial intelligence (XAI) model for clinically significant PCa diagnosis at biparametric MRI using Prostate Imaging Reporting and Data System (PI-RADS) features for classification justification. Materials and Methods This retrospective study included consecutive patients with histopathologic analysis-proven prostatic lesions who underwent biparametric MRI and biopsy between January 2012 and December 2017. After image annotation by two radiologists, a deep learning model was trained to detect the index lesion; classify PCa, clinically significant PCa (Gleason score ≥ 7), and benign lesions (eg, prostatitis); and justify classifications using PI-RADS features. Lesion- and patient-based performance were assessed using fivefold cross validation and areas under the receiver operating characteristic curve. Clinical feasibility was tested in a multireader study and by using the external PROSTATEx data set. Statistical evaluation of the multireader study included Mann-Whitney U and exact Fisher-Yates test. Results Overall, 1224 men (median age, 67 years; IQR, 62-73 years) had 3260 prostatic lesions (372 lesions with Gleason score of 6; 743 lesions with Gleason score of ≥ 7; 2145 benign lesions). XAI reliably detected clinically significant PCa in internal (area under the receiver operating characteristic curve, 0.89) and external test sets (area under the receiver operating characteristic curve, 0.87) with a sensitivity of 93% (95% CI: 87, 98) and an average of one false-positive finding per patient. Accuracy of the visual and textual explanations of XAI classifications was 80% (1080 of 1352), confirmed by experts. XAI-assisted readings improved the confidence (4.1 vs 3.4 on a five-point Likert scale; P = .007) of nonexperts in assessing PI-RADS 3 lesions, reducing reading time by 58 seconds (P = .009). Conclusion The explainable AI model reliably detected and classified clinically significant prostate cancer and improved the confidence and reading time of nonexperts while providing visual and textual explanations using well-established imaging features. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Chapiro in this issue.
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Affiliation(s)
- Charlie A Hamm
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Georg L Baumgärtner
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Felix Biessmann
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Nick L Beetz
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Alexander Hartenstein
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Lynn J Savic
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Konrad Froböse
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Franziska Dräger
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Simon Schallenberg
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Madhuri Rudolph
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Alexander D J Baur
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Bernd Hamm
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Matthias Haas
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Sebastian Hofbauer
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Hannes Cash
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
| | - Tobias Penzkofer
- From the Department of Radiology, Charité-Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Campus Virchow Klinikum, Augustenburgerplatz 1, 13353 Berlin, Germany (C.A.H., G.L.B., N.L.B., A.H., L.J.S., K.F., F.D., M.R., A.D.J.B., B.H., M.H., S.H., T.P.); Berlin Institute of Health (BIH), Berlin, Germany (C.A.H., N.L.B., L.J.S., T.P.); Faculty VI-Informatics and Media, Berliner Hochschule für Technik (BHT), Einstein Center Digital Future, Berlin, Germany (G.L.B., F.B.); Bayer AG, Medical Affairs and Pharmacovigilance, Integrated Evidence Generation & Business Innovation, Berlin, Germany (A.H.); Institute of Pathology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin and Berlin Institute of Health, Berlin, Germany (S.S.); and Department of Urology, Otto-von-Guericke-University Magdeburg, Germany and PROURO, Berlin, Germany (H.C.)
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Adam LC, Savic LJ, Chapiro J, Letzen B, Lin M, Georgiades C, Hong KK, Nezami N. Response assessment methods for patients with hepatic metastasis from rare tumor primaries undergoing transarterial chemoembolization. Clin Imaging 2022; 89:112-119. [PMID: 35777239 PMCID: PMC9470015 DOI: 10.1016/j.clinimag.2022.06.013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2022] [Revised: 06/17/2022] [Accepted: 06/19/2022] [Indexed: 11/03/2022]
Abstract
PURPOSE This study assessed the response to conventional transarterial chemoembolization (cTACE) in patients with liver metastases from rare tumor primaries using one-dimensional (1D) and three-dimensional (3D) quantitative response assessment methods, and investigate the relationship of lipiodol deposition in predicting response. MATERIALS AND METHODS This retrospective bicentric study included 16 patients with hepatic metastases from rare tumors treated with cTACE between 2002 and 2017. Multi-phasic MR imaging obtained before and after cTACE was used for assessment of response. Response evaluation criteria in solid tumors (RECIST) and modified-RECIST (mRECIST) were utilized for 1D response assessment, and volumetric RECIST (vRECIST) and enhancement-based quantitative European Association for Study of the Liver EASL (qEASL) were used for 3D response assessment. The same day post-cTACE CT scan was analyzed to quantify intratumoral lipiodol deposition (%). RESULTS The mean and standard deviation (SD) of diameter of treated lesions per targeted area was 7.5 ± 5.4 cm, and the mean and SD of number of metastases in each targeted area was 4.2 ± 4.6. cTACE was technically successful in all patients, without major complications. While RECIST and vRECIST methods did not allocate patients with partial response, mRECIST and qEASL identified patients with partial response. Intratumoral lipiodol deposition significantly predicted treatment response according qEASL (R2 = 0.470, p < 0.01), while no association was shown between lipiodol deposition within treated tumor area and RECIST or mRECIST (p > 0.212). CONCLUSION 3D quantitative volumetric response analysis can be used for stratification of response to cTACE in patients with hepatic metastases originating from rare primary tumors. Lipiodol deposition could potentially be used as an early surrogate to predict response to cTACE.
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Affiliation(s)
- Lucas C Adam
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA; Institute of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117 Berlin, Germany
| | - Lynn J Savic
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA; Institute of Radiology, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117 Berlin, Germany; Berlin Institute of Health at Charité - Universitätsmedizin Berlin, BIH Biomedical Innovation Academy, BIH Charité (Junior) (Digital) Clinician Scientist Program, Charitéplatz 1, 10117 Berlin, Germany
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - Brian Letzen
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA; Visage Imaging, Inc., San Diego, CA, USA
| | - Christos Georgiades
- Division of Vascular and Interventional Radiology, Russel H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Kelvin K Hong
- Division of Vascular and Interventional Radiology, Russel H. Morgan Department of Radiology and Radiological Sciences, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Nariman Nezami
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, New Haven, CT, USA; Division of Vascular and Interventional Radiology, Department of Diagnostic Radiology and Nuclear Medicine, University of Maryland School of Medicine, Baltimore, MD, USA; Experimental Therapeutics Program, University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA.
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4
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Berz AM, Santana JG, Iseke S, Gross M, Pekurovsky V, Laage Gaupp F, Savic LJ, Borde T, Gottwald LA, Boustani AM, Gebauer B, Lin M, Zhang X, Schlachter T, Madoff DC, Chapiro J. Impact of Chemoembolic Regimen on Immune Cell Recruitment and Immune Checkpoint Marker Expression following Transcatheter Arterial Chemoembolization in a VX2 Rabbit Liver Tumor Model. J Vasc Interv Radiol 2022; 33:764-774.e4. [PMID: 35346859 PMCID: PMC9344951 DOI: 10.1016/j.jvir.2022.03.026] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/22/2021] [Revised: 03/02/2022] [Accepted: 03/15/2022] [Indexed: 10/18/2022] Open
Abstract
PURPOSE To characterize the effects of commonly used transcatheter arterial chemoembolization (TACE) regimens on the immune response and immune checkpoint marker expression using a VX2 rabbit liver tumor model. MATERIALS AND METHODS Twenty-four VX2 liver tumor-bearing New Zealand white rabbits were assigned to 7 groups (n = 3 per group) undergoing locoregional therapy as follows: (a) bicarbonate infusion without embolization, (b) conventional TACE (cTACE) using a water-in-oil emulsion containing doxorubicin mixed 1:2 with Lipiodol, drug-eluting embolic-TACE with either (c) idarubicin-eluting Oncozene microspheres (40 μm) or (d) doxorubicin-eluting Lumi beads (40-90 μm). For each therapy arm (b-d), a tandem set of 3 animals with additional bicarbonate infusion before TACE was added, to evaluate the effect of pH modification on the immune response. Three untreated rabbits served as controls. Tissue was harvested 24 hours after treatment, followed by digital immunohistochemistry quantification (counts/μm2 ± SEM) of tumor-infiltrating cluster of differentiation 3+ T-lymphocytes, human leukocyte antigen DR type antigen-presenting cells (APCs), cytotoxic T-lymphocyte-associated protein-4 (CTLA-4), and programmed cell death protein-1 (PD-1)/PD-1 ligand (PD-L1) pathway axis expression. RESULTS Lumi-bead TACE induced significantly more intratumoral T-cell and APC infiltration than cTACE and Oncozene-microsphere TACE. Additionally, tumors treated with Lumi-bead TACE expressed significantly higher intratumoral immune checkpoint markers compared with cTACE and Oncozene-microsphere TACE. Neoadjuvant bicarbonate demonstrated the most pronounced effect on cTACE and resulted in a significant increase in intratumoral cluster of differentiation 3+ T-cell infiltration compared with cTACE alone. CONCLUSIONS This preclinical study revealed significant differences in evoked tumor immunogenicity depending on the choice of chemoembolic regimen for TACE.
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Affiliation(s)
- Antonia M Berz
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany
| | - Jessica G Santana
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Simon Iseke
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Diagnostic and Interventional Radiology, Pediatric Radiology and Neuroradiology, Rostock University Medical Center, Rostock, Germany
| | - Moritz Gross
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany
| | - Vasily Pekurovsky
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Fabian Laage Gaupp
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Lynn J Savic
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany; Berlin Institute of Health at Charité-Universitätsmedizin Berlin, Berlin, Germany
| | - Tabea Borde
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany
| | - Luzie A Gottwald
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany
| | - Anne Marie Boustani
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Bernhard Gebauer
- Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin and Humboldt-Universität zu Berlin, Department of Radiology Berlin, Germany
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Visage Imaging, Inc., San Diego, California
| | - Xuchen Zhang
- Department of Pathology, Yale School of Medicine, New Haven, Connecticut
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - David C Madoff
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut; Department of Internal Medicine, Yale School of Medicine, New Haven, Connecticut
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.
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5
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Doemel LA, Santana JG, Savic LJ, Gaupp FML, Borde T, Petukhova-Greenstein A, Kucukkaya AS, Schobert IT, Hamm CA, Gebauer B, Walsh JJ, Rexha I, Hyder F, Lin M, Madoff DC, Schlachter T, Chapiro J, Coman D. Comparison of metabolic and immunologic responses to transarterial chemoembolization with different chemoembolic regimens in a rabbit VX2 liver tumor model. Eur Radiol 2022; 32:2437-2447. [PMID: 34718844 PMCID: PMC9359419 DOI: 10.1007/s00330-021-08337-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2021] [Revised: 08/12/2021] [Accepted: 09/09/2021] [Indexed: 12/30/2022]
Abstract
OBJECTIVES The goal of this study was to investigate the effects of TACE using Lipiodol, Oncozene™ drug-eluting embolics (DEEs), or LUMI™-DEEs alone, or combined with bicarbonate on the metabolic and immunological tumor microenvironment in a rabbit VX2 tumor model. METHODS VX2 liver tumor-bearing rabbits were assigned to five groups. MRI and extracellular pH (pHe) mapping using Biosensor Imaging of Redundant Deviation in Shifts (BIRDS) were performed before and after intra-arterial therapy with conventional TACE (cTACE), DEE-TACE with Idarubicin-eluting Oncozene™-DEEs, or Doxorubicin-eluting LUMI™-DEEs, each with or without prior bicarbonate infusion, and in untreated rabbits or treated with intra-arterial bicarbonate only. Imaging results were validated with immunohistochemistry (IHC) staining of cell viability (PCNA, TUNEL) and immune response (HLA-DR, CD3). Statistical analysis was performed using Mann-Whitney U test. RESULTS pHe mapping revealed that combining cTACE with prior bicarbonate infusion significantly increased tumor pHe compared to control (p = 0.0175) and cTACE alone (p = 0.0025). IHC staining revealed peritumoral accumulation of HLA-DR+ antigen-presenting cells and CD3 + T-lymphocytes in controls. cTACE-treated tumors showed reduced immune infiltration, which was restored through combination with bicarbonate. DEE-TACE with Oncozene™-DEEs induced moderate intratumoral and marked peritumoral infiltration, which was slightly reduced with bicarbonate. Addition of bicarbonate prior to LUMI™-beads enhanced peritumoral immune cell infiltration compared to LUMI™-beads alone and resulted in the strongest intratumoral immune cell infiltration across all treated groups. CONCLUSIONS The choice of chemoembolic regimen for TACE strongly affects post-treatment TME pHe and the ability of immune cells to accumulate and infiltrate the tumor tissue. KEY POINTS • Combining conventional transarterial chemotherapy with prior bicarbonate infusion increases the pHe towards a more physiological value (p = 0.0025). • Peritumoral infiltration and intratumoral accumulation patterns of antigen-presenting cells and T-lymphocytes after transarterial chemotherapy were dependent on the choice of the chemoembolic regimen. • Combination of intra-arterial treatment with Doxorubicin-eluting LUMI™-beads and bicarbonate infusion resulted in the strongest intratumoral presence of immune cells (positivity index of 0.47 for HLADR+-cells and 0.62 for CD3+-cells).
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Affiliation(s)
- Luzie A Doemel
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - Jessica G Santana
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Lynn J Savic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
- Berlin Institute of Health, 10178, Berlin, Germany
| | - Fabian M Laage Gaupp
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Tabea Borde
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Klinikum Rechts Der Isar, Technische Universitat München, Munich, Germany
| | - Alexandra Petukhova-Greenstein
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - Ahmet S Kucukkaya
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - Isabel T Schobert
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - Charlie A Hamm
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
- Institute for Diagnostic Radiology and Neuroradiology, Greifswald University Hospital, Ferdinand-Sauerbruch-Strasse, 17475, Greifswald, Germany
| | - Bernhard Gebauer
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - John J Walsh
- Department of Biomedical Engineering, School of Engineering & Applied Science, 17 Hillhouse Avenue, New Haven, CT, 06510, USA
| | - Irvin Rexha
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Diagnostic and Interventional Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, 10117, Berlin, Germany
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Department of Biomedical Engineering, School of Engineering & Applied Science, 17 Hillhouse Avenue, New Haven, CT, 06510, USA
- Yale Cancer Center, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Visage Imaging, Inc., San Diego, CA, 92130, USA
| | - David C Madoff
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Yale Cancer Center, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Division of Medical Oncology, Department of Medicine, Yale School of Medicine, New Haven, CT, 06510, USA
- Yale Liver Center, Yale University School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Smilow Cancer Hospital Care Center - North Haven, 6 Devine Street, Fl 2, North Haven, CT, 06473, USA
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.
- Yale Cancer Center, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA.
| | - Daniel Coman
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
- Yale Cancer Center, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06510, USA
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Oestmann PM, Wang CJ, Savic LJ, Hamm CA, Stark S, Schobert I, Gebauer B, Schlachter T, Lin M, Weinreb JC, Batra R, Mulligan D, Zhang X, Duncan JS, Chapiro J. Deep learning-assisted differentiation of pathologically proven atypical and typical hepatocellular carcinoma (HCC) versus non-HCC on contrast-enhanced MRI of the liver. Eur Radiol 2021; 31:4981-4990. [PMID: 33409782 DOI: 10.1007/s00330-020-07559-1] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2020] [Revised: 11/06/2020] [Accepted: 11/23/2020] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To train a deep learning model to differentiate between pathologically proven hepatocellular carcinoma (HCC) and non-HCC lesions including lesions with atypical imaging features on MRI. METHODS This IRB-approved retrospective study included 118 patients with 150 lesions (93 (62%) HCC and 57 (38%) non-HCC) pathologically confirmed through biopsies (n = 72), resections (n = 29), liver transplants (n = 46), and autopsies (n = 3). Forty-seven percent of HCC lesions showed atypical imaging features (not meeting Liver Imaging Reporting and Data System [LI-RADS] criteria for definitive HCC/LR5). A 3D convolutional neural network (CNN) was trained on 140 lesions and tested for its ability to classify the 10 remaining lesions (5 HCC/5 non-HCC). Performance of the model was averaged over 150 runs with random sub-sampling to provide class-balanced test sets. A lesion grading system was developed to demonstrate the similarity between atypical HCC and non-HCC lesions prone to misclassification by the CNN. RESULTS The CNN demonstrated an overall accuracy of 87.3%. Sensitivities/specificities for HCC and non-HCC lesions were 92.7%/82.0% and 82.0%/92.7%, respectively. The area under the receiver operating curve was 0.912. CNN's performance was correlated with the lesion grading system, becoming less accurate the more atypical imaging features the lesions showed. CONCLUSION This study provides proof-of-concept for CNN-based classification of both typical- and atypical-appearing HCC lesions on multi-phasic MRI, utilizing pathologically confirmed lesions as "ground truth." KEY POINTS • A CNN trained on atypical appearing pathologically proven HCC lesions not meeting LI-RADS criteria for definitive HCC (LR5) can correctly differentiate HCC lesions from other liver malignancies, potentially expanding the role of image-based diagnosis in primary liver cancer with atypical features. • The trained CNN demonstrated an overall accuracy of 87.3% and a computational time of < 3 ms which paves the way for clinical application as a decision support instrument.
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Affiliation(s)
- Paula M Oestmann
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany.,Faculty of Medicine, Heinrich-Heine-University Düsseldorf, Düsseldorf, Germany
| | - Clinton J Wang
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT, 06520, USA
| | - Lynn J Savic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany
| | - Charlie A Hamm
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany
| | - Sophie Stark
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany.,Faculty of Medicine, Albert-Ludwigs-University Freiburg, Freiburg, Germany
| | - Isabel Schobert
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany
| | - Bernhard Gebauer
- Institute of Radiology, Berlin Institute of Health, Charité - Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität, 10117, Berlin, Germany
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Jeffrey C Weinreb
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Ramesh Batra
- Department of Transplantation and Immunology, 333 Cedar Street, New Haven, CT, 06520, USA
| | - David Mulligan
- Department of Transplantation and Immunology, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Xuchen Zhang
- Department of Pathology, Yale School of Medicine, 310 Cedar Street, New Haven, CT, 06520, USA
| | - James S Duncan
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.,Department of Biomedical Engineering, Yale School of Engineering and Applied Science, New Haven, CT, 06520, USA
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.
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Tegel BR, Huber S, Savic LJ, Lin M, Gebauer B, Pollak J, Chapiro J. Quantification of contrast-uptake as imaging biomarker for disease progression of renal cell carcinoma after tumor ablation. Acta Radiol 2020; 61:1708-1716. [PMID: 32216452 DOI: 10.1177/0284185120909964] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
BACKGROUND The prognosis of patients with renal cell carcinoma (RCC) depends greatly on the presence of extra-renal metastases. PURPOSE To investigate the value of total tumor volume (TTV) and enhancing tumor volume (ETV) as three-dimensional (3D) quantitative imaging biomarkers for disease aggressiveness in patients with RCC. MATERIAL AND METHODS Retrospective, HIPAA-compliant, IRB-approved study including 37 patients with RCC treated with image-guided thermal ablation during 2007-2015. TNM stage, RENAL Nephrometry Score, largest tumor diameter, TTV, and ETV were assessed on cross-sectional imaging at baseline and correlated with outcome measurements. The primary outcome was time-to-occurrence of extra-renal metastases and the secondary outcome was progression-free survival (PFS). Correlation was assessed using a Cox regression model and differences in outcomes were shown by Kaplan-Meier plots with significance and odds ratios (OR) calculated by Log-rank test/generalized Wilcoxon and continuity-corrected Woolf logit method. RESULTS Patients with a TTV or ETV > 5 cm3 were more likely to develop distant metastases compared to patients with TTV (OR 6.69, 95% confidence interval [CI] 0.33-134.4, P=0.022) or ETV (OR 8.48, 95% CI 0.42-170.1, P=0.016) < 5 cm3. Additionally, PFS was significantly worse in patients with larger ETV (P = 0.039; median PFS 51.87 months vs. 69.97 months). In contrast, stratification by median value of the established, caliper-based measurements showed no significant correlation with outcome parameters. CONCLUSION ETV, as surrogate of lesion vascularity, is a sensitive imaging biomarker for occurrence of extra-renal metastatic disease and PFS in patients with RCC.
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Affiliation(s)
- Bruno R Tegel
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - Steffen Huber
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
| | - Lynn J Savic
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - MingDe Lin
- U/S Imaging and Interventions, Philips Research North America, Cambridge, MA, USA
| | - Bernhard Gebauer
- Charité Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt Universität Berlin and Berlin Institute of Health, Institute of Radiology, Berlin, Germany
| | - Jeffrey Pollak
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
| | - Julius Chapiro
- Yale School of Medicine, Department of Radiology and Biomedical Imaging, New Haven, CT, USA
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8
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Savic LJ, Chapiro J, Funai E, Bousabarah K, Schobert IT, Isufi E, Geschwind JFH, Stark S, He P, Rudek MA, Perez Lozada JC, Ayyagari R, Pollak J, Schlachter T. Prospective study of Lipiodol distribution as an imaging marker for doxorubicin pharmacokinetics during conventional transarterial chemoembolization of liver malignancies. Eur Radiol 2020; 31:3002-3014. [PMID: 33063185 DOI: 10.1007/s00330-020-07380-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2020] [Revised: 08/19/2020] [Accepted: 10/06/2020] [Indexed: 01/24/2023]
Abstract
OBJECTIVES To evaluate the prognostic potential of Lipiodol distribution for the pharmacokinetic (PK) profiles of doxorubicin (DOX) and doxorubicinol (DOXOL) after conventional transarterial chemoembolization (cTACE). METHODS This prospective clinical trial ( ClinicalTrials.gov : NCT02753881) included 30 consecutive participants with liver malignancies treated with cTACE (5/2016-10/2018) using 50 mg DOX/10 mg mitomycin C emulsified 1:2 with ethiodized oil (Lipiodol). Peripheral blood was sampled at 10 timepoints for standard non-compartmental analysis of peak concentrations (Cmax) and area under the curve (AUC) with dose normalization (DN). Imaging markers included Lipiodol distribution on post-cTACE CT for patient stratification into 1 segment (n = 10), ≥ 2 segments (n = 10), and lobar cTACE (n = 10), and baseline enhancing tumor volume (ETV). Adverse events (AEs) and tumor response on MRI were recorded 3-4 weeks post-cTACE. Statistics included repeated measurement ANOVA (RM-ANOVA), Mann-Whitney, Kruskal-Wallis, Fisher's exact test, and Pearson correlation. RESULTS Hepatocellular (n = 26), cholangiocarcinoma (n = 1), and neuroendocrine metastases (n = 3) were included. Stratified according to Lipiodol distribution, DOX-Cmax increased from 1 segment (DOX-Cmax, 83.94 ± 75.09 ng/mL; DN-DOX-Cmax, 2.67 ± 2.02 ng/mL/mg) to ≥ 2 segments (DOX-Cmax, 139.66 ± 117.73 ng/mL; DN-DOX-Cmax, 3.68 ± 4.20 ng/mL/mg) to lobar distribution (DOX-Cmax, 334.35 ± 215.18 ng/mL; DN-DOX-Cmax, 7.11 ± 4.24 ng/mL/mg; p = 0.036). While differences in DN-DOX-AUC remained insignificant, RM-ANOVA revealed significant separation of time concentration curves for DOX (p = 0.023) and DOXOL (p = 0.041) comparing 1, ≥ 2 segments, and lobar cTACE. Additional indicators of higher DN-DOX-Cmax were high ETV (p = 0.047) and Child-Pugh B (p = 0.009). High ETV and tumoral Lipiodol coverage also correlated with tumor response. AE occurred less frequently after segmental cTACE. CONCLUSIONS This prospective clinical trial provides updated PK data revealing Lipiodol distribution as an imaging marker predictive of DOX-Cmax and tumor response after cTACE in liver cancer. KEY POINTS • Prospective pharmacokinetic analysis after conventional TACE revealed Lipiodol distribution (1 vs. ≥ 2 segments vs. lobar) as an imaging marker predictive of doxorubicin peak concentrations (Cmax). • Child-Pugh B class and tumor hypervascularization, measurable as enhancing tumor volume (ETV) at baseline, were identified as additional predictors for higher dose-normalized doxorubicin Cmax after conventional TACE. • ETV at baseline and tumoral Lipiodol coverage can serve as predictors of volumetric tumor response after conventional TACE according to quantitative European Association for the Study of the Liver (qEASL) criteria.
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Affiliation(s)
- Lynn J Savic
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
- Institute of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Eliot Funai
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Khaled Bousabarah
- Department of Stereotactic and Functional Neurosurgery, University Hospital of Cologne, Cologne, Germany
| | - Isabel T Schobert
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
- Institute of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany
| | - Edvin Isufi
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | | | - Sophie Stark
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
- Institute of Radiology, Charité - Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany
| | - Ping He
- Sidney Kimmel Comprehensive Cancer Center at Department of Oncology, Johns Hopkins University, Baltimore, MD, USA
| | - Michelle A Rudek
- Sidney Kimmel Comprehensive Cancer Center at Department of Oncology, Johns Hopkins University, Baltimore, MD, USA
| | - Juan Carlos Perez Lozada
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Rajasekhara Ayyagari
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Jeffrey Pollak
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Division of Interventional Radiology, Yale School of Medicine, 333 Cedar Street, New Haven, CT, 06520, USA.
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9
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Borde T, Laage Gaupp F, Geschwind JF, Savic LJ, Miszczuk M, Rexha I, Adam L, Walsh JJ, Huber S, Duncan JS, Peters DC, Sinusas A, Schlachter T, Gebauer B, Hyder F, Coman D, van Breugel JMM, Chapiro J. Idarubicin-Loaded ONCOZENE Drug-Eluting Bead Chemoembolization in a Rabbit Liver Tumor Model: Investigating Safety, Therapeutic Efficacy, and Effects on Tumor Microenvironment. J Vasc Interv Radiol 2020; 31:1706-1716.e1. [PMID: 32684417 DOI: 10.1016/j.jvir.2020.04.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2019] [Revised: 04/06/2020] [Accepted: 04/13/2020] [Indexed: 02/07/2023] Open
Abstract
PURPOSE To investigate toxicity, efficacy, and microenvironmental effects of idarubicin-loaded 40-μm and 100-μm drug-eluting embolic (DEE) transarterial chemoembolization in a rabbit liver tumor model. MATERIALS AND METHODS Twelve male New Zealand White rabbits with orthotopically implanted VX2 liver tumors were assigned to DEE chemoembolization with 40-μm (n = 5) or 100-μm (n = 4) ONCOZENE microspheres or no treatment (control; n = 3). At 24-72 hours postprocedurally, multiparametric magnetic resonance (MR) imaging including dynamic contrast-enhanced (DCE), diffusion-weighted imaging (DWI), and biosensor imaging of redundant deviation in shifts (BIRDS) was performed to assess extracellular pH (pHe), followed by immediate euthanasia. Laboratory parameters and histopathologic ex vivo analysis included fluorescence confocal microscopy and immunohistochemistry. RESULTS DCE MR imaging demonstrated a similar degree of devascularization of embolized tumors for both microsphere sizes (mean arterial enhancement, 8% ± 12 vs 36% ± 51 in controls; P = .07). Similarly, DWI showed postprocedural increases in diffusion across the entire lesion (apparent diffusion coefficient, 1.89 × 10-3 mm2/s ± 0.18 vs 2.34 × 10-3 mm2/s ± 0.18 in liver; P = .002). BIRDS demonstrated profound tumor acidosis at baseline (mean pHe, 6.79 ± 0.08 in tumor vs 7.13 ± 0.08 in liver; P = .02) and after chemoembolization (6.8 ± 0.06 in tumor vs 7.1 ± 0.04 in liver; P = .007). Laboratory and ex vivo analyses showed central tumor core penetration and greater increase in liver enzymes for 40-μm vs 100-μm microspheres. Inhibition of cell proliferation, intratumoral hypoxia, and limited idarubicin elution were equally observed with both sphere sizes. CONCLUSIONS Noninvasive multiparametric MR imaging visualized chemoembolic effects in tumor and tumor microenvironment following DEE chemoembolization. Devascularization, increased hypoxia, coagulative necrosis, tumor acidosis, and limited idarubicin elution suggest ischemia as the predominant therapeutic mechanism. Substantial size-dependent differences indicate greater toxicity with the smaller microsphere diameter.
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Affiliation(s)
- Tabea Borde
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510; Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Fabian Laage Gaupp
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | | | - Lynn J Savic
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510; Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Milena Miszczuk
- Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Irvin Rexha
- Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Lucas Adam
- Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - John J Walsh
- Department of Biomedical Engineering, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Steffen Huber
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - James S Duncan
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510; Department of Biomedical Engineering, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Dana C Peters
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Albert Sinusas
- Department of Cardiology, Yale Translational Research Imaging Center, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Bernhard Gebauer
- Institute of Radiology, Charité-Universitätsmedizin Berlin, corporate member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany
| | - Fahmeed Hyder
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Daniel Coman
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510
| | - Johanna M M van Breugel
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510; Department of Radiology, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale University School of Medicine, 333 Cedar St., New Haven, CT 06510.
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Özdirik B, Kayser A, Ullrich A, Savic LJ, Reiss M, Tacke F, Wiedenmann B, Jann H, Roderburg C. Primary Neuroendocrine Neoplasms of the Breast: Case Series and Literature Review. Cancers (Basel) 2020; 12:cancers12030733. [PMID: 32244940 PMCID: PMC7140078 DOI: 10.3390/cancers12030733] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 02/28/2020] [Accepted: 03/16/2020] [Indexed: 11/16/2022] Open
Abstract
Primary neuroendocrine carcinoma of the breast (NECB) as defined by the World Health Organization (WHO) in 2012 is a rare, but possibly under-diagnosed entity. It is heterogeneous as it entails a wide spectrum of diseases comprising both well-differentiated neuroendocrine tumors of the breast as well as highly aggressive small cell carcinomas. Retrospective screening of hospital charts of 612 patients (2008–2019) from our specialized outpatient unit for neuroendocrine neoplasia revealed five patients diagnosed with NECB. Given the low prevalence of these malignancies, correct diagnosis remains a challenge that requires an interdisciplinary approach. Specifically, NECB may be misclassified as carcinoma of the breast with neuroendocrine differentiation, carcinomas of the breast of no special type/invasive ductal carcinoma, or a metastasis to the breast. Therefore, this study presents multifaceted characteristics as well as the clinical course of these patients and discusses the five cases from our institution in the context of available literature.
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Affiliation(s)
- Burcin Özdirik
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Antonin Kayser
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Andrea Ullrich
- Department of Pathology, Charité University Medicine Berlin, Charitéplatz 1, 10117 Berlin, Germany;
| | - Lynn J. Savic
- Department of Diagnostic and Interventional Radiology, Charité University Medicine Berlin, Augustenburgerplatz 1, 13353 Berlin, Germany;
| | - Markus Reiss
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Frank Tacke
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Bertram Wiedenmann
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Henning Jann
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
| | - Christoph Roderburg
- Department of Gastroenterology/Hepatology, Charité University Medical Center Berlin, Campus Virchow Klinikum and Charité Mitte, Augustenburger Platz 1, 13353 Berlin, Germany; (B.Ö.); (A.K.); (M.R.); (F.T.); (B.W.); (H.J.)
- Correspondence:
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11
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Coman D, Peters DC, Walsh JJ, Savic LJ, Huber S, Sinusas AJ, Lin M, Chapiro J, Constable RT, Rothman DL, Duncan JS, Hyder F. Extracellular pH mapping of liver cancer on a clinical 3T MRI scanner. Magn Reson Med 2019; 83:1553-1564. [PMID: 31691371 DOI: 10.1002/mrm.28035] [Citation(s) in RCA: 26] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2019] [Revised: 09/13/2019] [Accepted: 09/18/2019] [Indexed: 02/06/2023]
Abstract
PURPOSE To demonstrate feasibility of developing a noninvasive extracellular pH (pHe ) mapping method on a clinical MRI scanner for molecular imaging of liver cancer. METHODS In vivo pHe mapping has been demonstrated on preclinical scanners (e.g., 9.4T, 11.7T) with Biosensor Imaging of Redundant Deviation in Shifts (BIRDS), where the pHe readout by 3D chemical shift imaging (CSI) depends on hyperfine shifts emanating from paramagnetic macrocyclic chelates like TmDOTP5- which upon extravasation from blood resides in the extracellular space. We implemented BIRDS-based pHe mapping on a clinical 3T Siemens scanner, where typically diamagnetic 1 H signals are detected using millisecond-long radiofrequency (RF) pulses, and 1 H shifts span over ±10 ppm with long transverse (T2 , 102 ms) and longitudinal (T1 , 103 ms) relaxation times. We modified this 3D-CSI method for ultra-fast acquisition with microsecond-long RF pulses, because even at 3T the paramagnetic 1 H shifts of TmDOTP5- have millisecond-long T2 and T1 and ultra-wide chemical shifts (±200 ppm) as previously observed in ultra-high magnetic fields. RESULTS We validated BIRDS-based pH in vitro with a pH electrode. We measured pHe in a rabbit model for liver cancer using VX2 tumors, which are highly vascularized and hyperglycolytic. Compared to intratumoral pHe (6.8 ± 0.1; P < 10-9 ) and tumor's edge pHe (6.9 ± 0.1; P < 10-7 ), liver parenchyma pHe was significantly higher (7.2 ± 0.1). Tumor localization was confirmed with histopathological markers of necrosis (hematoxylin and eosin), glucose uptake (glucose transporter 1), and tissue acidosis (lysosome-associated membrane protein 2). CONCLUSION This work demonstrates feasibility and potential clinical translatability of high-resolution pHe mapping to monitor tumor aggressiveness and therapeutic outcome, all to improve personalized cancer treatment planning.
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Affiliation(s)
- Daniel Coman
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut
| | - Dana C Peters
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut
| | - John J Walsh
- Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - Lynn J Savic
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Institute of Radiology, Charité-Universitätsmedizin Berlin, Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany
| | - Steffen Huber
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut
| | - Albert J Sinusas
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Department of Medicine, Section of Cardiovascular Medicine, Yale University, New Haven, Connecticut
| | - MingDe Lin
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Visage Imaging, Inc., San Diego, California
| | - Julius Chapiro
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut
| | - R Todd Constable
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut
| | - Douglas L Rothman
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - James S Duncan
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut
| | - Fahmeed Hyder
- Department of Radiology & Biomedical Imaging, Yale University, New Haven, Connecticut.,Department of Biomedical Engineering, Yale University, New Haven, Connecticut
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12
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Schobert I, Chapiro J, Nezami N, Hamm CA, Gebauer B, Lin M, Pollak J, Saperstein L, Schlachter T, Savic LJ. Quantitative Imaging Biomarkers for 90Y Distribution on Bremsstrahlung SPECT After Resin-Based Radioembolization. J Nucl Med 2019; 60:1066-1072. [PMID: 30655331 DOI: 10.2967/jnumed.118.219691] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2018] [Accepted: 12/19/2018] [Indexed: 12/27/2022] Open
Abstract
Our purpose was to identify baseline imaging features in patients with liver cancer that correlate with 90Y distribution on postprocedural SPECT and predict tumor response to transarterial radioembolization (TARE). Methods: This retrospective study was approved by the institutional review board and included 38 patients with hepatocellular carcinoma (HCC) (n = 23; 18/23 men; mean age, 62.39 ± 8.62 y; 34 dominant tumors) and non-HCC hepatic malignancies (n = 15; 9/15 men; mean age, 61.13 ± 11.51 y; 24 dominant tumors) who underwent 40 resin-based TARE treatments (August 2012 to January 2018). Multiphasic contrast-enhanced MRI or CT was obtained before and Bremsstrahlung SPECT within 2 h after TARE. Total tumor volume (cm3) and enhancing tumor volume (ETV [cm3] and % of total tumor volume), and total and enhancing tumor burden (%), were volumetrically assessed on baseline imaging. Up to 2 dominant tumors per treated lobe were analyzed. After multimodal image registration of baseline imaging and SPECT/CT, 90Y distribution was quantified on SPECT as tumor-to-normal-liver ratio (TNR). Response was assessed according to RECIST1.1 and quantitative European Association for the Study of the Liver criteria. Clinical parameters were also assessed. Statistical tests included Mann-Whitney U, Pearson correlation, and linear regression. Results: In HCC patients, high baseline ETV% significantly correlated with high TNR on SPECT, demonstrating greater 90Y uptake in the tumor relative to the liver parenchyma (P < 0.001). In non-HCC patients, a correlation between ETV% and TNR was observed as well (P = 0.039). Follow-up imaging for response assessments within 1-4 mo after TARE was available for 23 patients with 25 treatments. The change of ETV% significantly correlated with TNR in HCC (P = 0.039) but not in non-HCC patients (P = 0.886). Additionally, Child-Pugh class B patients demonstrated significantly more 90Y deposition in nontumorous liver than Child-Pugh A patients (P = 0.021). Conclusion: This study identified ETV% as a quantifiable imaging biomarker on preprocedural MRI and CT to predict 90Y distribution on postprocedural SPECT in HCC and non-HCC. However, the relationship between the preferential uptake of 90Y to the tumor and tumor response after radioembolization could be validated only for HCC.
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Affiliation(s)
- Isabel Schobert
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.,Institute of Radiology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany; and
| | - Julius Chapiro
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Nariman Nezami
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Charlie A Hamm
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.,Institute of Radiology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany; and
| | - Bernhard Gebauer
- Institute of Radiology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany; and
| | - MingDe Lin
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.,Visage Imaging Inc., San Diego, California
| | - Jeffrey Pollak
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Lawrence Saperstein
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Todd Schlachter
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut
| | - Lynn J Savic
- Department of Radiology and Biomedical Imaging, Yale School of Medicine, New Haven, Connecticut.,Institute of Radiology, Charité Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität, and Berlin Institute of Health, Berlin, Germany; and
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13
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Savic LJ, Chapiro J, Hamm B, Gebauer B, Collettini F. Irreversible Electroporation in Interventional Oncology: Where We Stand and Where We Go. ROFO-FORTSCHR RONTG 2016; 188:735-45. [PMID: 27074423 DOI: 10.1055/s-0042-104203] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
UNLABELLED Irreversible electroporation (IRE) is the latest in the series of image-guided locoregional tumor ablation therapies. IRE is performed in a nearly non-thermal fashion that circumvents the "heat sink effect" and allows for IRE application in proximity to critical structures such as bile ducts or neurovascular bundles, where other techniques are unsuitable. IRE appears generally feasible and initial reported results for tumor ablation in the liver, pancreas and prostate are promising. Additionally, IRE demonstrates a favorable safety profile. However, site-specific complications include bile leaking or vein thrombosis and may be more severe after pancreatic IRE compared to liver or prostate ablation. There is limited clinical evidence in support of the use of IRE in the kidney. In contrast, pulmonary IRE has so far failed to demonstrate efficacy due to practicability limitations. Hence, this review will provide a state-of-the-art update on available clinical evidence of IRE regarding feasibility, safety and oncologic efficacy. The future role of IRE in the minimally invasive treatment of solid tumors will be discussed. KEY POINTS • Preclinical findings of IRE have been successfully translated into clinical settings.• Non-thermal ablation is able to prevent the "heat sink effect" and collateral damage.• IRE should primarily be applied to tumors adjacent to sensitive structures (e. g. bile ducts).IRE efficacy appears promising in the liver, pancreas and prostate with tolerable morbidity.• In contrast, there are no evidential benefits of IRE in the lung parenchyma. Citation Format: • Savic LJ, Chapiro J, Hamm B et al. Irreversible Electroporation in Interventional Oncology: Where We Stand and Where We Go. Fortschr Röntgenstr 2016; 188: 735 - 745.
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Abstract
BACKGROUND AND PURPOSE No previous study compares neuroradiology training programs and teaching schedules across the globe, to our knowledge. This study was conducted to better understand international program requisites. MATERIALS AND METHODS Data from 43 countries were collected by an e-mail-based questionnaire (response rate, 84.0%). Radiologists across the world were surveyed regarding the neuroradiology training schemes in their institutions. Answers were verified by officers of the national neuroradiology societies. RESULTS While many countries do not provide fellowship training in neuroradiology (n = 16), others have formal postresidency curricula (n = 27). Many programs have few fellows and didactic sessions, but the 1- or 2-year duration of fellowship training is relatively consistent (n = 23/27, 85%). CONCLUSIONS There is a wide variety of fellowship offerings, lessons provided, and ratios of teachers to learners in neuroradiology training programs globally.
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Affiliation(s)
- T Schneider
- From the Divisions of Neuroradiology (T.S., D.M.Y.) Department of Diagnostic and Interventional Neuroradiology (T.S., J.F.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
| | | | - J Fiehler
- Department of Diagnostic and Interventional Neuroradiology (T.S., J.F.), University Medical Center Hamburg-Eppendorf, Hamburg, Germany
| | - L J Savic
- Interventional Radiology (L.J.S.), Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins University School of Medicine, Baltimore, Maryland
| | - D M Yousem
- From the Divisions of Neuroradiology (T.S., D.M.Y.)
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15
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Duran R, Chapiro J, Frangakis C, Lin M, Schlachter TR, Schernthaner RE, Wang Z, Savic LJ, Tacher V, Kamel IR, Geschwind JF. Uveal Melanoma Metastatic to the Liver: The Role of Quantitative Volumetric Contrast-Enhanced MR Imaging in the Assessment of Early Tumor Response after Transarterial Chemoembolization. Transl Oncol 2014; 7:447-55. [PMID: 24953419 PMCID: PMC4202794 DOI: 10.1016/j.tranon.2014.05.004] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2014] [Revised: 05/17/2014] [Accepted: 05/21/2014] [Indexed: 01/18/2023] Open
Abstract
PURPOSE To determine whether volumetric changes of enhancement as seen on contrast-enhanced magnetic resonance (MR) imaging can help assess early tumor response and predict survival in patients with metastatic uveal melanoma after one session of transarterial chemoembolization (TACE). MATERIALS AND METHODS Fifteen patients with 59 lesions who underwent MR imaging before and 3 to 4 weeks after the first TACE were retrospectively included. MR analysis evaluated signal intensities, World Health Organization (WHO), Response Evaluation Criteria in Solid Tumors (RECIST), European Association for the Study of the Liver (EASL), modified RECIST (mRECIST), tumor volume [volumetric RECIST (vRECIST)], and volumetric tumor enhancement [quantitative EASL (qEASL)]. qEASL was expressed in cubic centimeters [qEASL (cm3)] and as a percentage of the tumor volume [qEASL (%)]. Paired t test with its exact permutation distribution was used to compare measurements before and after TACE. The Kaplan-Meier method with the log-rank test was used to calculate overall survival for responders and non-responders. RESULTS In target lesions, mean qEASL (%) decreased from 63.9% to 42.6% (P = .016). No significant changes were observed using the other response criteria. In non-target lesions, mean WHO, RECIST, EASL, mRECIST, vRECIST, and qEASL (cm3) were significantly increased compared to baseline. qEASL (%) remained stable (P = .214). Median overall survival was 5.6 months. qEASL (cm3) was the only parameter that could predict survival based on target lesions (3.6 vs 40.5 months, P < .001) or overall (target and non-target lesions) response (4.4 vs 40.9 months, P = .001). CONCLUSION Volumetric tumor enhancement may be used as a surrogate biomarker for survival prediction in patients with uveal melanoma after the first TACE.
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Affiliation(s)
- Rafael Duran
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Julius Chapiro
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Constantine Frangakis
- Ultrasound and Interventions, Philips Research North America, Briarcliff Manor, NY, USA.
| | - MingDe Lin
- Department of Biostatistics, The Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA.
| | - Todd R Schlachter
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Rüdiger E Schernthaner
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Zhijun Wang
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Lynn J Savic
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Vania Tacher
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Ihab R Kamel
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
| | - Jean-François Geschwind
- Russell H. Morgan Department of Radiology and Radiological Science, Division of Vascular and Interventional Radiology, The Johns Hopkins Hospital, Baltimore, MD, 21287, USA.
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