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  1. Article ; Online: Re: Marcin Miszczyk, Pawel Rajawa, Takafumi Yanagisawa, et al. The Efficacy and Safety of Metastasis-directed Therapy in Patients with Prostate Cancer: A Systematic Review and Meta-analysis of Prospective Studies. Eur Urol. In press. https://doi.org/10.1016/j.eururo.2023.10.012.

    Fodor, Andrei / Brombin, Chiara / Chiti, Arturo / Di Muzio, Nadia

    European urology

    2024  

    Language English
    Publishing date 2024-03-12
    Publishing country Switzerland
    Document type Letter
    ZDB-ID 193790-x
    ISSN 1873-7560 ; 1421-993X ; 0302-2838
    ISSN (online) 1873-7560 ; 1421-993X
    ISSN 0302-2838
    DOI 10.1016/j.eururo.2024.01.033
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    Zs.A 1247: Show issues Location:
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    Zs.MO 294: Show issues

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  2. Article ; Online: Defining the Right State for a Will Rogers Phenomenon in Oligometastatic Prostate Cancer.

    Fodor, Andrei / Picchio, Maria / Di Muzio, Nadia Gisella

    JAMA oncology

    2020  Volume 6, Issue 6, Page(s) 936–937

    MeSH term(s) Humans ; Male ; Prostatic Neoplasms/therapy
    Language English
    Publishing date 2020-04-15
    Publishing country United States
    Document type Letter ; Comment
    ISSN 2374-2445
    ISSN (online) 2374-2445
    DOI 10.1001/jamaoncol.2020.0574
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  3. Article ; Online: In Regard to Wages et al and Leite et al.

    Fiorino, Claudio / Cozzarini, Cesare / Fodor, Andrei / di Muzio, Nadia G

    International journal of radiation oncology, biology, physics

    2021  Volume 110, Issue 5, Page(s) 1548–1549

    MeSH term(s) Humans ; Salaries and Fringe Benefits
    Language English
    Publishing date 2021-07-16
    Publishing country United States
    Document type Letter ; Comment
    ZDB-ID 197614-x
    ISSN 1879-355X ; 0360-3016
    ISSN (online) 1879-355X
    ISSN 0360-3016
    DOI 10.1016/j.ijrobp.2021.04.045
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    Zs.A 1218: Show issues Location:
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  4. Article ; Online: In Regard to Zureick et al.

    Fodor, Andrei / Brombin, Chiara / Mangili, Paola / Fiorino, Claudio / Di Muzio, Nadia

    International journal of radiation oncology, biology, physics

    2022  Volume 114, Issue 3, Page(s) 554–555

    Language English
    Publishing date 2022-09-21
    Publishing country United States
    Document type Letter
    ZDB-ID 197614-x
    ISSN 1879-355X ; 0360-3016
    ISSN (online) 1879-355X
    ISSN 0360-3016
    DOI 10.1016/j.ijrobp.2022.06.066
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  5. Article: Comparing Performances of Predictive Models of Toxicity after Radiotherapy for Breast Cancer Using Different Machine Learning Approaches.

    Ubeira-Gabellini, Maria Giulia / Mori, Martina / Palazzo, Gabriele / Cicchetti, Alessandro / Mangili, Paola / Pavarini, Maddalena / Rancati, Tiziana / Fodor, Andrei / Del Vecchio, Antonella / Di Muzio, Nadia Gisella / Fiorino, Claudio

    Cancers

    2024  Volume 16, Issue 5

    Abstract: Purpose: Different ML models were compared to predict toxicity in RT on a large cohort (n = 1314).: Methods: The endpoint was RTOG G2/G3 acute toxicity, resulting in 204/1314 patients with the event. The dataset, including 25 clinical, anatomical, ... ...

    Abstract Purpose: Different ML models were compared to predict toxicity in RT on a large cohort (n = 1314).
    Methods: The endpoint was RTOG G2/G3 acute toxicity, resulting in 204/1314 patients with the event. The dataset, including 25 clinical, anatomical, and dosimetric features, was split into 984 for training and 330 for internal tests. The dataset was standardized; features with a high
    Results: The model's performance was compared on a training-test dataset over different metrics: the best performance model was LightGBM. Logistic regression with three variables (LR3) selected via bootstrapping showed performances similar to the best-performing models. The AUC of test data is slightly above 0.65 for the best models (highest value: 0.662 with LightGBM).
    Conclusions: No model performed the best for all metrics: more complex ML models had better performances; however, models with just three features showed performances comparable to the best models using many (n = 13-19) features.
    Language English
    Publishing date 2024-02-25
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers16050934
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  6. Article ; Online: Skin dose-volume predictors of moderate-severe late side effects after whole breast radiotherapy.

    Cicchetti, Alessandro / Mangili, Paola / Fodor, Andrei / Gabellini, Maria Giulia Ubeira / Chiara, Anna / Deantoni, Chiara / Mori, Martina / Pasetti, Marcella / Palazzo, Gabriele / Rancati, Tiziana / Del Vecchio, Antonella / Gisella Di Muzio, Nadia / Fiorino, Claudio

    Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology

    2024  Volume 194, Page(s) 110183

    Abstract: Background: Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by ... ...

    Abstract Background: Toxicity after whole breast Radiotherapy is a relevant issue, impacting the quality-of-life of a not negligible number of patients. We aimed to develop a Normal Tissue Complication Probability (NTCP) model predicting late toxicities by combining dosimetric parameters of the breast dermis and clinical factors.
    Methods: The skin structure was defined as the outer CT body contour's 5 mm inner isotropic expansion. It was retrospectively segmented on a large mono-institutional cohort of early-stage breast cancer patients enrolled between 2009 and 2017 (n = 1066). Patients were treated with tangential-field RT, delivering 40 Gy in 15 fractions to the whole breast. Toxicity was reported during Follow-Up (FU) using SOMA/LENT scoring. The study endpoint was moderate-severe late side effects consisting of Fibrosis-Atrophy-Telangiectasia-Pain (FATP G ≥ 2) developed within 42 months after RT completion. A machine learning pipeline was designed with a logistic model combining clinical factors and absolute skin DVH (cc) parameters as output.
    Results: The FATP G2 + rate was 3.8 %, with 40/1066 patients experiencing side effects. After the preprocessing of variables, a cross-validation was applied to define the best-performing model. We selected a 4-variable model with Post-Surgery Cosmetic alterations (Odds Ratio, OR = 7.3), Aromatase Inhibitors (as a protective factor with OR = 0.45), V20 Gy (50 % of the prescribed dose, OR = 1.02), and V42 Gy (105 %, OR = 1.09). Factors were also converted into an adjusted V20Gy.
    Conclusions: The association between late reactions and skin DVH when delivering 40 Gy/15 fr was quantified, suggesting an independent role of V20 and V42. Few clinical factors heavily modulate the risk.
    MeSH term(s) Humans ; Female ; Breast Neoplasms/radiotherapy ; Middle Aged ; Skin/radiation effects ; Retrospective Studies ; Aged ; Radiotherapy Dosage ; Radiation Injuries/etiology ; Adult ; Organs at Risk/radiation effects ; Aged, 80 and over
    Language English
    Publishing date 2024-02-27
    Publishing country Ireland
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 605646-5
    ISSN 1879-0887 ; 0167-8140
    ISSN (online) 1879-0887
    ISSN 0167-8140
    DOI 10.1016/j.radonc.2024.110183
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    Zs.A 1926: Show issues Location:
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  7. Article ; Online: Granulosa cell tumors (GCTs) of the ovary: What is the role of radiotherapy?

    Barcellini, Amelia / Mangili, Giorgia / Fodor, Andrei / Secondino, Simona / Zerbetto, Flavia / Charalampopoulou, Alexandra / Pignata, Sandro / Orlandi, Ester / Bergamini, Alice

    Critical reviews in oncology/hematology

    2022  Volume 181, Page(s) 103889

    Abstract: Granulosa cell tumors of the ovary have an indolent behavior and a good prognosis, but a high incidence of local recurrence after surgery. The best treatment in the recurrent setting is unclear and randomized clinical trials on the management in the ... ...

    Abstract Granulosa cell tumors of the ovary have an indolent behavior and a good prognosis, but a high incidence of local recurrence after surgery. The best treatment in the recurrent setting is unclear and randomized clinical trials on the management in the recurrent setting are lacking. The role of radiotherapy is controversial in adjuvant settings and unknown in case of relapse after surgery. This review aims to summarize the level of evidence of the role of radiation treatments for granulosa cell tumors of the ovary.
    Language English
    Publishing date 2022-11-26
    Publishing country Netherlands
    Document type Journal Article ; Review
    ZDB-ID 605680-5
    ISSN 1879-0461 ; 0737-9587 ; 1040-8428
    ISSN (online) 1879-0461
    ISSN 0737-9587 ; 1040-8428
    DOI 10.1016/j.critrevonc.2022.103889
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    Zs.A 1931: Show issues Location:
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    Jg. 1995 - 2021: Lesesall (1.OG)
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  8. Article ; Online: Management of recurrent ovarian cancer: when platinum-based regimens are not a therapeutic option.

    Bergamini, Alice / Bocciolone, Luca / Fodor, Andrei / Candiani, Massimo / Mangili, Giorgia

    International journal of gynecological cancer : official journal of the International Gynecological Cancer Society

    2019  Volume 29, Issue 9, Page(s) 1431–1436

    Abstract: Ovarian cancer relapses have been traditionally classified according to the platinum-free interval, leading to an arbitrary categorization of possible scenarios and treatment options. Its relevance in assessing treatment strategies has been revised in ... ...

    Abstract Ovarian cancer relapses have been traditionally classified according to the platinum-free interval, leading to an arbitrary categorization of possible scenarios and treatment options. Its relevance in assessing treatment strategies has been revised in the last several years, as the panorama is constantly changing in the era of personalized medicine and targeted therapies. Factors to be considered while defining the best management of recurrent disease, and, consequently, the available treatment alternatives are increasing. Platinum remains one of the milestones of ovarian cancer treatment, but for some patients it might not be an ideal choice for several reasons other than limited platinum sensitivity. This review aims to analyze the scenarios in which platinum is not considered suitable in the management of patients with recurrent ovarian cancer, and the currently available alternatives.
    MeSH term(s) Antineoplastic Agents, Hormonal/therapeutic use ; Carcinoma, Ovarian Epithelial/drug therapy ; Carcinoma, Ovarian Epithelial/radiotherapy ; Doxorubicin/analogs & derivatives ; Doxorubicin/therapeutic use ; Female ; Humans ; Neoplasm Recurrence, Local/drug therapy ; Neoplasm Recurrence, Local/radiotherapy ; Ovarian Neoplasms/drug therapy ; Ovarian Neoplasms/radiotherapy ; Poly(ADP-ribose) Polymerase Inhibitors/therapeutic use ; Polyethylene Glycols/therapeutic use ; Randomized Controlled Trials as Topic ; Topotecan/therapeutic use
    Chemical Substances Antineoplastic Agents, Hormonal ; Poly(ADP-ribose) Polymerase Inhibitors ; liposomal doxorubicin ; Polyethylene Glycols (3WJQ0SDW1A) ; Topotecan (7M7YKX2N15) ; Doxorubicin (80168379AG)
    Language English
    Publishing date 2019-09-18
    Publishing country England
    Document type Journal Article ; Review
    ZDB-ID 1070385-8
    ISSN 1525-1438 ; 1048-891X
    ISSN (online) 1525-1438
    ISSN 1048-891X
    DOI 10.1136/ijgc-2019-000624
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    Zs.A 3198: Show issues Location:
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  9. Article: Radiation Therapy for Gestational Trophoblastic Neoplasia: Forward-Looking Lessons Learnt.

    Barcellini, Amelia / Fodor, Andrei / Charalampopoulou, Alexandra / Cassani, Chiara / Locati, Laura Deborah / Cioffi, Raffaella / Bergamini, Alice / Pignata, Sandro / Orlandi, Ester / Mangili, Giorgia

    Cancers

    2023  Volume 15, Issue 19

    Abstract: Gestational trophoblastic neoplasia (GTN) includes several rare malignant diseases occurring after pregnancy: invasive moles, choriocarcinoma, placental site trophoblastic tumours, and epithelioid trophoblastic tumours. Multidisciplinary protocols ... ...

    Abstract Gestational trophoblastic neoplasia (GTN) includes several rare malignant diseases occurring after pregnancy: invasive moles, choriocarcinoma, placental site trophoblastic tumours, and epithelioid trophoblastic tumours. Multidisciplinary protocols including multi-agent chemotherapy, surgery, and occasionally radiotherapy achieve good outcomes for some high-risk metastatic patients. In this narrative review of the published studies on the topic, we have tried to identify the role of radiotherapy. The available studies are mainly small, old, and retrospective, with incomplete data regarding radiotherapy protocols delivering low doses (which can make this disease appear radioresistant in some cases despite high response rates with palliative doses) to wide fields (whole-brain, whole-liver, etc.), which can increase toxicity. Studies considering modern techniques are needed to overcome these limitations and determine the full potential of radiotherapy beyond its antihemorrhagic and palliative roles.
    Language English
    Publishing date 2023-09-30
    Publishing country Switzerland
    Document type Journal Article ; Review
    ZDB-ID 2527080-1
    ISSN 2072-6694
    ISSN 2072-6694
    DOI 10.3390/cancers15194817
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  10. Article ; Online: Real-world validation of Artificial Intelligence-based Computed Tomography auto-contouring for prostate cancer radiotherapy planning.

    Palazzo, Gabriele / Mangili, Paola / Deantoni, Chiara / Fodor, Andrei / Broggi, Sara / Castriconi, Roberta / Ubeira Gabellini, Maria Giulia / Del Vecchio, Antonella / Di Muzio, Nadia G / Fiorino, Claudio

    Physics and imaging in radiation oncology

    2023  Volume 28, Page(s) 100501

    Abstract: Background and purpose: Artificial Intelligence (AI)-based auto-contouring for treatment planning in radiotherapy needs extensive clinical validation, including the impact of editing after automatic segmentation. The aims of this study were to assess ... ...

    Abstract Background and purpose: Artificial Intelligence (AI)-based auto-contouring for treatment planning in radiotherapy needs extensive clinical validation, including the impact of editing after automatic segmentation. The aims of this study were to assess the performance of a commercial system for Clinical Target Volumes (CTVs) (prostate/seminal vesicles) and selected Organs at Risk (OARs) (rectum/bladder/femoral heads + femurs), evaluating also inter-observer variability (manual vs automatic + editing) and the reduction of contouring time.
    Materials and methods: Two expert observers contoured CTVs/OARs of 20 patients in our Treatment Planning System (TPS). Computed Tomography (CT) images were sent to the automatic contouring workstation: automatic contours were generated and sent back to TPS, where observers could edit them if necessary. Inter- and intra-observer consistency was estimated using Dice Similarity Coefficients (DSC). Radiation oncologists were also asked to score the quality of automatic contours, ranging from 1 (complete re-contouring) to 5 (no editing). Contouring times (manual vs automatic + edit) were compared.
    Results: DSCs (manual vs automatic only) were consistent with inter-observer variability (between 0.65 for seminal vesicles and 0.94 for bladder); editing further improved performances (range: 0.76-0.94). The median clinical score was 4 (little editing) and it was <4 in 3/2 patients for the two observers respectively. Inter-observer variability of automatic + editing contours improved significantly, being lower than manual contouring (e.g.: seminal vesicles: 0.83vs0.73; prostate: 0.86vs0.83; rectum: 0.96vs0.81). Oncologist contouring time reduced from 17 to 24 min of manual contouring time to 3-7 min of editing time for the two observers (p < 0.01).
    Conclusion: Automatic contouring with a commercial AI-based system followed by editing can replace manual contouring, resulting in significantly reduced time for segmentation and better consistency between operators.
    Language English
    Publishing date 2023-10-13
    Publishing country Netherlands
    Document type Journal Article
    ISSN 2405-6316
    ISSN (online) 2405-6316
    DOI 10.1016/j.phro.2023.100501
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