Tailoring neoadjuvant systemic therapy in breast cancer: "The advent of a personalized approach"-The Breast-Gynecological and Immuno-Oncology International Cancer Conference (BGICC) consensus and recommendations.

BACKGROUND: The management of early breast cancer (BC) has witnessed an uprise in the use of neoadjuvant therapy and a remarkable reshaping of the systemic therapy postneoadjuvant treatment in the last few years, with the evolution of many controversial clinical situations that require consensus. METHODS: During the 14th Breast-Gynecological and Immuno-Oncology International Cancer Conference held in Egypt in 2022, a panel of 44 BC experts from 13 countries voted on statements concerning debatable challenges in the neo/adjuvant treatment setting. The recommendations were subsequently updated based on the most recent data emerging. A modified Delphi approach was used to develop this consensus. A consensus was achieved when ≥75% of voters selected an answer. RESULTS AND CONCLUSIONS: The consensus recommendations addressed different escalation and de-escalation strategies in the setting of neoadjuvant therapy for early BC. The recommendations recapitulate the available clinical evidence and expert opinion to individualize patient management and optimize therapy outcomes. Consensus was reached in 63% of the statements (52/83), and the rationale behind each statement was clarified.

Screening chest wall ultrasound in the mastectomy patient.

BACKGROUND: While there are clear guidelines regarding chest wall ultrasound in the symptomatic patient, there is conflicting evidence regarding the use of ultrasound in the screening of women post-mastectomy. OBJECTIVE: To assess the utility of screening chest wall ultrasound after mastectomy and to assess features of detected malignancies. METHODS: This IRB approved, retrospective study evaluates screening US examinations of the chest wall after mastectomy. Asymptomatic women presenting for screening chest wall ultrasound from January 2016 through May 2017 were included. Cases of known active malignancy were excluded. All patients had at least one year of clinical or imaging follow-up. 43 exams (8.5 %) were performed with a history of contralateral malignancy, 465 exams (91.3 %) were performed with a history of ipsilateral malignancy, and one exam (0.2 %) was performed in a patient with bilateral prophylactic mastectomy. RESULTS: During the 17-month period, there were 509 screening US in 389 mastectomy patients. 504 (99.0 %) exams were negative/benign. Five exams (1.0 %) were considered suspicious, with recommendation for biopsy, which was performed. Out of 509 exams, 3 (0.6 %) yielded benign results, while 2 (0.39 %) revealed recurrent malignancy, with a 95 % confidence interval (exact binomial) of 0.05 % to 1.41 % for screening ultrasound. Both patients who recurred had previously recurred, and both had initial cancer of lobular histology. CONCLUSION: Of 509 chest wall screening US exams performed in mastectomy, 2 malignancies were detected, and each patient had history of invasive lobular carcinoma and at least one prior recurrence prior to this study, suggesting benefit of screening ultrasound in these populations.

Characterising polymyalgia rheumatica on whole-body 18F-FDG PET/CT: an atlas.

The impact of modern imaging in uncovering the underlying pathology of PMR cannot be understated. Long dismissed as an inflammatory syndrome with links to the large vessel vasculitis giant cell arteritis (GCA), a pathognomonic pattern of musculotendinous inflammation is now attributed to PMR and may be used to confirm its diagnosis. Among the available modalities, 18F-fluorodeoxyglucose (18F-FDG) PET/CT is increasingly recognized for its high sensitivity and specificity, as well as added ability to detect concomitant large vessel GCA and exclude other relevant differentials like infection and malignancy. This atlas provides a contemporary depiction of PMR's pathology and outlines how this knowledge translates into a pattern of findings on whole body 18F-FDG PET/CT that can reliably confirm its diagnosis.

Suspicious Ultrasound-Occult Non-Calcified Mammographic Masses, Asymmetries, and Architectural Distortions Are Moderate Probability for Malignancy.

Suspicious non-calcified mammographic findings have not been evaluated with modern mammographic technique, and the purpose of this work is to compare the likelihood of malignancy for those findings. To do this, 5018 consecutive mammographically guided biopsies performed during 2016-2019 at a large metropolitan, community-based hospital system were retrospectively reviewed. In total, 4396 were excluded for targeting calcifications, insufficient follow-up, or missing data. Thirty-seven of 126 masses (29.4%) were malignant, 44 of 194 asymmetries (22.7%) were malignant, and 77 of 302 architectural distortions (AD, 25.5%) were malignant. The combined likelihood of malignancy was 25.4%. Older age was associated with a higher likelihood of malignancy for each imaging finding type (all p ≤ 0.006), and a possible ultrasound correlation was associated with a higher likelihood of malignancy when all findings were considered together (p = 0.012). Two-view asymmetries were more frequently malignant than one-view asymmetries (p = 0.03). There were two false-negative biopsies (98.7% sensitivity and 100% specificity). In conclusion, the 25.4% likelihood of malignancy confirms the recommendation for biopsy of suspicious, ultrasound-occult, mammographic findings. Mammographically guided biopsies were highly sensitive and specific in this study. Older patient age and a possible ultrasound correlation should raise concern given the increased likelihood of malignancy in those scenarios.

Breast Imaging Patient Demographics at a Major Comprehensive Cancer Center Before and During the COVID-19 Pandemic.

OBJECTIVE: The coronavirus disease of 2019 (COVID-19) pandemic disproportionately affected certain vulnerable communities. The purpose of our study was to determine how COVID-19 affected the socioeconomic demographics of breast imaging patients at a major comprehensive cancer center. METHODS: This retrospective cohort study compared female patients who underwent screening mammograms, diagnostic mammograms, breast ultrasound, or breast MRI during the following time periods: prepandemic (February 1, 2018, through February 29, 2020), acute pandemic (March 1, 2020, through June 30, 2020), subacute pandemic (August 1, 2020, through December 31, 2020), and chronic pandemic (January 1, 2021, through June 30, 2022). Statistics were performed using the generalized estimating equations approach. RESULTS: A total of 74,398 female patients (mean age, 55.6 ± 12.4 years) underwent 238,776 total breast imaging examinations. For screening mammograms, Hispanics represented 27.1% (9,197 of 33,960) of patients in the prepandemic time period compared with 16.7% (604 of 3,621) in the acute pandemic time period, 18.7% (1,835 of 9,830) in the subacute pandemic time period, and 24.3% (7,492 of 30,869) in the chronic pandemic time period (all P < .0001). Self-pay patients saw similar declines for screening mammograms during the same time periods: 21.7% (7,375 of 33,960), 7.9% (286 of 3,621), 9.5% (933 of 9,830), and 17.4% (5,357 of 30,869), respectively (all P < .0001, compared with the prepandemic time period). Similarly dramatic trends were not observed for race or other imaging examinations. DISCUSSION: At our cancer center, Hispanics and self-pay patients were disproportionately affected by the COVID-19 pandemic. Strategies to improve health inequities are needed.

Longitudinal dynamic contrast-enhanced MRI radiomic models for early prediction of response to neoadjuvant systemic therapy in triple-negative breast cancer.

Early prediction of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) patients could help oncologists select individualized treatment and avoid toxic effects associated with ineffective therapy in patients unlikely to achieve pathologic complete response (pCR). The objective of this study is to evaluate the performance of radiomic features of the peritumoral and tumoral regions from dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) acquired at different time points of NAST for early treatment response prediction in TNBC. This study included 163 Stage I-III patients with TNBC undergoing NAST as part of a prospective clinical trial (NCT02276443). Peritumoral and tumoral regions of interest were segmented on DCE images at baseline (BL) and after two (C2) and four (C4) cycles of NAST. Ten first-order (FO) radiomic features and 300 gray-level-co-occurrence matrix (GLCM) features were calculated. Area under the receiver operating characteristic curve (AUC) and Wilcoxon rank sum test were used to determine the most predictive features. Multivariate logistic regression models were used for performance assessment. Pearson correlation was used to assess intrareader and interreader variability. Seventy-eight patients (48%) had pCR (52 training, 26 testing), and 85 (52%) had non-pCR (57 training, 28 testing). Forty-six radiomic features had AUC at least 0.70, and 13 multivariate models had AUC at least 0.75 for training and testing sets. The Pearson correlation showed significant correlation between readers. In conclusion, Radiomic features from DCE-MRI are useful for differentiating pCR and non-pCR. Similarly, predictive radiomic models based on these features can improve early noninvasive treatment response prediction in TNBC patients undergoing NAST.

Deep Learning for Fully Automatic Tumor Segmentation on Serially Acquired Dynamic Contrast-Enhanced MRI Images of Triple-Negative Breast Cancer.

Accurate tumor segmentation is required for quantitative image analyses, which are increasingly used for evaluation of tumors. We developed a fully automated and high-performance segmentation model of triple-negative breast cancer using a self-configurable deep learning framework and a large set of dynamic contrast-enhanced MRI images acquired serially over the patients' treatment course. Among all models, the top-performing one that was trained with the images across different time points of a treatment course yielded a Dice similarity coefficient of 93% and a sensitivity of 96% on baseline images. The top-performing model also produced accurate tumor size measurements, which is valuable for practical clinical applications.

Diagnostic ultrasound of the chest wall in the symptomatic patient after mastectomy.

BACKGROUND: Lack of standardized imaging recommendations among mastectomy patients has led to variability in how recurrences are detected. OBJECTIVE: To describe the findings and assess the diagnostic efficacy of ultrasound in the evaluation of symptomatic post-mastectomy patients. MATERIALS AND METHODS: This single institution, retrospective study included 749 consecutive diagnostic chest wall ultrasound examinations performed in mastectomy patients, from January 2016 to June 2017. Chest wall ultrasound evaluated the mastectomy bed with or without reconstruction. Electronic health records were queried for the primary breast cancer histology prior to mastectomy, clinical symptoms prompting the diagnostic ultrasound, ultrasound findings, subsequent cytology and pathology, and follow-up data. Excluded were patients with a known recurrence, asymptomatic patients, and those with <2 years of clinical or imaging follow-up. Descriptive and comparative statistical analyses were performed. RESULTS: Among the 749 ultrasounds performed, 58 malignancies were identified for a 7.7% (58/749) malignancy rate, with a median tumor size of 20 mm. Patients diagnosed with a malignancy most often presented with a palpable abnormality (79.3%, 46/58) or skin changes (13.8%, 8/58) and rarely with pain (1.7%, 1/58). Patients who underwent a biopsy yielding a benign result most often presented with a palpable abnormality (41.5%, 287/691), pain (25.6%,177/691), or postoperative swelling/suspected fluid collection (17.8%, 123/691). Diagnostic ultrasound yielded a 91.4% sensitivity (95% CI 81.0, 97.1), 96.1% specificity (95% CI 94.4, 97.4), 66.3% PPV3 (95% CI 57.4, 74.1), and 99.3% negative predictive value (95% CI 98.3, 99.7) for cancer detection. There were 5 false negative ultrasound cases after a skin punch biopsy was performed due to clinically suspicious skin changes. CONCLUSIONS: Chest wall ultrasound has a high sensitivity and negative predictive value for detection of breast cancer recurrence in symptomatic patients after mastectomy. Skin changes remain an important clinical manifestation of a cancer recurrence.

International Interobserver Variability of Breast Density Assessment.

PURPOSE: The aim of this study was to determine variability in visually assessed mammographic breast density categorization among radiologists practicing in Indonesia, the Netherlands, South Africa, and the United States. METHODS: Two hundred consecutive 2-D full-field digital screening mammograms obtained from September to December 2017 were selected and retrospectively reviewed from four global locations, for a total of 800 mammograms. Three breast radiologists in each location (team) provided consensus density assessments of all 800 mammograms using BI-RADS® density categorization. Interreader agreement was compared using Gwet's AC2 with quadratic weighting across all four density categories and Gwet's AC1 for binary comparison of combined not dense versus dense categories. Variability of distribution among teams was calculated using the Stuart-Maxwell test of marginal homogeneity across all four categories and using the McNemar test for not dense versus dense categories. To compare readers from a particular country on their own 200 mammograms versus the other three teams, density distribution was calculated using conditional logistic regression. RESULTS: For all 800 mammograms, interreader weighted agreement for distribution among four density categories was 0.86 (Gwet's AC2 with quadratic weighting; 95% confidence interval, 0.85-0.88), and for not dense versus dense categories, it was 0.66 (Gwet's AC1; 95% confidence interval, 0.63-0.70). Density distribution across four density categories was significantly different when teams were compared with one another and one team versus the other three teams combined (P < .001). Overall, all readers placed the largest number of mammograms in the scattered and heterogeneous categories. CONCLUSIONS: Although reader teams from four different global locations had almost perfect interreader agreement in BI-RADS density categorization, variability in density distribution across four categories remained statistically significant.

An African-Specific Variant of TP53 Reveals PADI4 as a Regulator of p53-Mediated Tumor Suppression.

TP53 is the most frequently mutated gene in cancer, yet key target genes for p53-mediated tumor suppression remain unidentified. Here, we characterize a rare, African-specific germline variant of TP53 in the DNA-binding domain Tyr107His (Y107H). Nuclear magnetic resonance and crystal structures reveal that Y107H is structurally similar to wild-type p53. Consistent with this, we find that Y107H can suppress tumor colony formation and is impaired for the transactivation of only a small subset of p53 target genes; this includes the epigenetic modifier PADI4, which deiminates arginine to the nonnatural amino acid citrulline. Surprisingly, we show that Y107H mice develop spontaneous cancers and metastases and that Y107H shows impaired tumor suppression in two other models. We show that PADI4 is itself tumor suppressive and that it requires an intact immune system for tumor suppression. We identify a p53-PADI4 gene signature that is predictive of survival and the efficacy of immune-checkpoint inhibitors. SIGNIFICANCE: We analyze the African-centric Y107H hypomorphic variant and show that it confers increased cancer risk; we use Y107H in order to identify PADI4 as a key tumor-suppressive p53 target gene that contributes to an immune modulation signature and that is predictive of cancer survival and the success of immunotherapy. See related commentary by Bhatta and Cooks, p. 1518. This article is highlighted in the In This Issue feature, p. 1501.

Comparison of prone and upright, stereotactic, and tomosynthesis-guided biopsies with secondary analysis of ultrasound-occult architectural distortions.

OBJECTIVES: Compare prone and upright, stereotactic, and tomosynthesis-guided vacuum-assisted breast biopsies (prone DM-VABB, prone DBT-VABB, upright DM-VABB, and upright DBT-VABB) in a community-practice setting and review outcomes of ultrasound-occult architectural distortions (AD). METHODS: Consecutive biopsies performed at two community-based breast centers from 2016 to 2019 were retrospectively reviewed. Technical details of each procedure and patient outcomes were recorded. Separate analyses were performed for ultrasound-occult ADs. Two sample t-tests and Fisher's exact test facilitated comparisons. RESULTS: A total of 1133 patients underwent 369 prone DM-VABB, 324 prone DBT-VABB, 437 upright DM-VABB, and 123 upright DBT-VABB with 99.2%, 100%, 99.3%, and 99.2% success, respectively (p-values > 0.25). Mean lesion targeting times were greater for prone biopsy (minutes: 6.94 prone DM-VABB, 8.54 prone DBT-VABB, 5.52 upright DM-VABB, and 5.51 upright DBT-VABB; p-values < 0.001), yielding longer total prone procedure times for prone biopsy (p < 0.001). Compared to DM-VABB, DBT-VABB used fewer exposures (p < 0.001) and more commonly targeted AD, asymmetries, or masses (p < 0.001). Malignancy rates were similar between procedures: prone DM-VABB 22.4%, prone DBT-VABB 21.9%, upright DM-VABB 22.8%, and upright DBT-VABB 17.2% (p-values > 0.19). One hundred forty of the 1133 patients underwent 145 biopsies for ultrasound-occult AD (143 DBT-VABB and 2 DM-VABB). Biopsy yielded 27 malignancies and 47 high-risk lesions (74 of 145, 51%). Malignancy rate was 20.7% after surgical upgrade of one benign-discordant and two high-risk lesions. CONCLUSIONS: All biopsy procedure types were extremely successful. The 20.7% malignancy rate for ultrasound-occult AD confirms a management recommendation for tissue diagnosis. Upright biopsy was faster than prone biopsy, and DBT-VABB used fewer exposures than DM-VABB. CLINICAL RELEVANCE: Our results highlight important differences between prone DM-VABB, prone DBT-VABB, upright DM-VABB, and upright DBT-VABB. Moreover, the high likelihood of malignancy for ultrasound-occult AD will provide confidence in recommending tissue diagnosis in lieu of observation or clinical follow-up. KEY POINTS: • Upright and prone stereotactic and tomosynthesis-guided breast biopsies were safe and effective in the community-practice setting. • The malignancy rate for ultrasound-occult architectural distortion of 20.7% confirms the management recommendation for biopsy. • Upright procedures were faster than prone procedures, and tomosynthesis-guided biopsy used fewer exposures than stereotactic biopsy.

Assessment of Response to Neoadjuvant Systemic Treatment in Triple-Negative Breast Cancer Using Functional Tumor Volumes from Longitudinal Dynamic Contrast-Enhanced MRI.

Early assessment of neoadjuvant systemic therapy (NAST) response for triple-negative breast cancer (TNBC) is critical for patient care in order to avoid the unnecessary toxicity of an ineffective treatment. We assessed functional tumor volumes (FTVs) from dynamic contrast-enhanced (DCE) MRI after 2 cycles (C2) and 4 cycles (C4) of NAST as predictors of response in TNBC. A group of 100 patients with stage I-III TNBC who underwent DCE MRI at baseline, C2, and C4 were included in this study. Tumors were segmented on DCE images of 1 min and 2.5 min post-injection. FTVs were measured using the optimized percentage enhancement (PE) and signal enhancement ratio (SER) thresholds. The Mann-Whitney test was used to compare the performance of the FTVs at C2 and C4. Of the 100 patients, 49 (49%) had a pathologic complete response (pCR) and 51 (51%) had a non-pCR. The maximum area under the receiving operating characteristic curve (AUC) for predicting the treatment response was 0.84 (p < 0.001) for FTV at C4 followed by FTV at C2 (AUC = 0.82, p < 0.001). The FTV measured at baseline was not able to discriminate pCR from non-pCR. FTVs measured on DCE MRI at C2, as well as at C4, of NAST can potentially predict pCR and non-pCR in TNBC patients.

Common activities and predictive gene signature identified for genetic hypomorphs of TP53.

Missense mutations that inactivate p53 occur commonly in cancer, and germline mutations in TP53 cause Li Fraumeni syndrome, which is associated with early-onset cancer. In addition, there are over two hundred germline missense variants of p53 that remain uncharacterized. In some cases, these germline variants have been shown to encode lesser-functioning, or hypomorphic, p53 protein, and these alleles are associated with increased cancer risk in humans and mouse models. However, most hypomorphic p53 variants remain un- or mis-classified in clinical genetics databases. There thus exists a significant need to better understand the behavior of p53 hypomorphs and to develop a functional assay that can distinguish hypomorphs from wild-type p53 or benign variants. We report the surprising finding that two different African-centric genetic hypomorphs of p53 that occur in distinct functional domains of the protein share common activities. Specifically, the Pro47Ser variant, located in the transactivation domain, and the Tyr107His variant, located in the DNA binding domain, both share increased propensity to misfold into a conformation specific for mutant, misfolded p53. Additionally, cells and tissues containing these hypomorphic variants show increased NF-κB activity. We identify a common gene expression signature from unstressed lymphocyte cell lines that is shared between multiple germline hypomorphic variants of TP53, and which successfully distinguishes wild-type p53 and a benign variant from lesser-functioning hypomorphic p53 variants. Our findings will allow us to better understand the contribution of p53 hypomorphs to disease risk and should help better inform cancer risk in the carriers of p53 variants.

Nipple Discharge Imaging Evaluation with Mammography, Ultrasound, Galactography, and MRI.

RATIONALE AND OBJECTIVE: To determine the diagnostic yield of various imaging tests used to evaluate nipple discharge. MATERIALS AND METHODS: A single institution, IRB-approved, retrospective study was performed of 320 consecutive patients presenting with nipple discharge. Imaging and pathology were reviewed to determine the yield for malignancy, atypical high-risk lesions (HRLs), and intraductal papillomas (IDPs). RESULTS: Of the 320 patients, pathology or follow up confirmed 40 breast malignancies (40/320, 12.5%),14 atypical HRLs (14/320, 4.4%), 71 IDPs (71/320, 22.2%), 48 other benign pathologies (48/320,15.0%), and 147 unknown but benign cases (147/320, 45.9%). Physiologic discharge characteristics were observed in a minority of malignant cases: nonspontaneous (4/40, 10.0%); neither bloody nor clear (4/40, 10.0%); bilateral (3/40, 7.5%). Malignancy was associated with older age (p < 0.001) and bloody discharge (odds ratio 6.5, p < 0.0001). The combination of digital mammography and ultrasound had a 93% sensitivity and a 98% NPV, while contrast enhanced MRI (CE-MRI) had a 100% sensitivity and a 100% NPV for malignancy. Only three galactography examinations were performed among the malignant cohort, with minimal contribution (1 of 3) to the diagnostic evaluation. In this case, galactography findings helped determine imaging-pathology discordance, prompting a recommendation for surgical excision and subsequently a malignant diagnosis. CONCLUSION: The combination of mammography and ultrasonography detected 93% of breast malignancies associated with nipple discharge and had a 98% NPV for malignancy. The value of CE-MRI is its ability to detect the remaining malignancies, not detected on mammography or ultrasound, and its ability to obviate the need for surgical duct excision.

Deep Learning Models for Automated Assessment of Breast Density Using Multiple Mammographic Image Types.

Recently, convolutional neural network (CNN) models have been proposed to automate the assessment of breast density, breast cancer detection or risk stratification using single image modality. However, analysis of breast density using multiple mammographic types using clinical data has not been reported in the literature. In this study, we investigate pre-trained EfficientNetB0 deep learning (DL) models for automated assessment of breast density using multiple mammographic types with and without clinical information to improve reliability and versatility of reporting. 120,000 for-processing and for-presentation full-field digital mammograms (FFDM), digital breast tomosynthesis (DBT), and synthesized 2D images from 5032 women were retrospectively analyzed. Each participant underwent up to 3 screening examinations and completed a questionnaire at each screening encounter. Pre-trained EfficientNetB0 DL models with or without clinical history were optimized. The DL models were evaluated using BI-RADS (fatty, scattered fibroglandular densities, heterogeneously dense, or extremely dense) versus binary (non-dense or dense) density classification. Pre-trained EfficientNetB0 model performances were compared using inter-observer and commercial software (Volpara) variabilities. Results show that the average Fleiss' Kappa score between-observers ranged from 0.31-0.50 and 0.55-0.69 for the BI-RADS and binary classifications, respectively, showing higher uncertainty among experts. Volpara-observer agreement was 0.33 and 0.54 for BI-RADS and binary classifications, respectively, showing fair to moderate agreement. However, our proposed pre-trained EfficientNetB0 DL models-observer agreement was 0.61-0.66 and 0.70-0.75 for BI-RADS and binary classifications, respectively, showing moderate to substantial agreement. Overall results show that the best breast density estimation was achieved using for-presentation FFDM and DBT images without added clinical information. Pre-trained EfficientNetB0 model can automatically assess breast density from any images modality type, with the best results obtained from for-presentation FFDM and DBT, which are the most common image archived in clinical practice.