Galstyan et al. 3D Printing in Medicine
(2021) 7:6
https://doi.org/10.1186/s41205-021-00095-8
REVIEW
Open Access
Applications of 3D printing in breast cancer
management
Arpine Galstyan1,2, Michael J. Bunker1,2, Fluvio Lobo3, Robert Sims3, James Inziello3, Jack Stubbs3,
Rita Mukhtar1,4 and Tatiana Kelil1,2*
Abstract
Three-dimensional (3D) printing is a method by which two-dimensional (2D) virtual data is converted to 3D objects
by depositing various raw materials into successive layers. Even though the technology was invented almost 40
years ago, a rapid expansion in medical applications of 3D printing has only been observed in the last few years.
3D printing has been applied in almost every subspecialty of medicine for pre-surgical planning, production of
patient-specific surgical devices, simulation, and training. While there are multiple review articles describing
utilization of 3D printing in various disciplines, there is paucity of literature addressing applications of 3D printing in
breast cancer management. Herein, we review the current applications of 3D printing in breast cancer
management and discuss the potential impact on future practices.
Introduction
3D printing, also referred to as additive manufacturing
and rapid prototyping, involves the creation of 3D objects from 2D virtual data using material that is either
fused or deposited layer-by-layer from the ground up
[1]. Segmentation software programs identify specific
voxels within the anatomy of interest, isolate the region
of interest into its core constituents, and generate a file
that is recognizable by 3D printers. This file can then be
modified through design software programs in order to
create a model that is optimized for printing and possesses the characteristics desired by the provider [2]. 3D
printed models are particularly beneficial for surgeons
and have been utilized in almost all surgical subspecialties for pre-surgical planning, intraoperative guidance, and the productions of customized implants [1–9].
During preoperative surgical planning, the models allow
surgeons to anticipate potential difficulties and tailor
* Correspondence:
[email protected]
1
University of California, 1600 Divisadero St, C250, Box 1667, San Francisco,
CA 94115, USA
2
Department of Radiology, Center for Advanced 3D Technologies, 1600
Divisadero St, C250, Box 1667, San Francisco, CA 94115, USA
Full list of author information is available at the end of the article
their surgical approach accordingly. By extension, 3D
models help reduce overall intraoperative time, minimize
anesthetic dosage and optimize surgical outcomes [2, 5,
9]. They are also used to facilitate interdisciplinary communication between health care providers and can enhance education of trainees and patients. This article
reviews the applications of 3D printing in breast cancer
management.
Breast conservation surgery and tumor localization
Breast cancer is the most common form of noncutaneous cancer and the second most common cause
of cancer-related deaths [10]. A personalized approach
to breast cancer is important as breast cancer is a heterogeneous disease where management is dependent on
multiple patient-specific factors [11]. Surgical management usually includes either breast conservation surgery
(BCS) or mastectomy. Although mastectomy is an important and definitive treatment option for some patients, it is often associated with substantial
psychological, social, and sexual sequelae, as well as significant body image distortion [12]. BCS followed by radiation therapy has been validated as an equivalent
alternative to mastectomy, with similar survival rates,
© The Author(s). 2021, corrected publication 2021. Open Access This article is licensed under a Creative Commons Attribution
4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as
long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence,
and indicate if changes were made. The images or other third party material in this article are included in the article's Creative
Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative
Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need
to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/
licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.
0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
Galstyan et al. 3D Printing in Medicine
(2021) 7:6
acceptable rates of local recurrence, and better cosmetic
outcomes [13–15]. Approximately 60–75% of American
women with early stage breast cancer are treated with
BCS [16]. Traditionally, patients with inadequate tumor
size to breast size ratios were managed with mastectomy,
however recent advances in oncoplastic techniques allow
more patients with extensive disease to be considered
for BCS [17].
A successful BCS requires multidisciplinary communication and planning between the surgeon, radiologist,
pathologist, radiation and medical oncologist. The goal
is to safely remove the tumor with adequate surgical
margins and provide good cosmetic outcome without
compromising survival. In patients undergoing BCS,
negative margin status greatly reduces risk of local recurrence and increases relapse-free survival. Wire needle
localization and non-wire localization such as seeds are
accepted standards methods used to guide intraoperative
surgical excision of nonpalpable breast lesions. However,
determination of tumor size and extent remains imprecise regardless of the method utilized for BCS [18]. This
results in positive margins requiring re-excision 22–34%
of the time [18–20]. In addition to causing patient anxiety and extra health care expenses, re-excision for positive margins impairs cosmetic outcomes and increases
the potential for complications from surgery [21, 22].
Furthermore, localization techniques such as wires and
seeds require the surgeon to estimate the 3D location
and extent of cancer typically from 2D post localization
mammography images, which are limited by their acquisition plane or display format. Furthermore, wires may
enter the breast skin at a distance from the site of the
cancer, requiring additional estimation [23]. Supplementing wire needle and non-wire localization methods
with perioperative use of 3D printed models provides a
tangible depiction of the patient’s breast and disease extent, facilitating planning of surgical options and
Page 2 of 10
approach. The physical models also provide detailed information about anatomic relationships between the
tumor, overlying skin, nipple, and pectoralis muscle, beyond what is traditionally depicted with mammograms
and magnetic resonance imaging (MRI), and enhance
visualization of the overall breast and tumor volume
(Fig. 1). This in turn aids with achievement of negative
surgical margins [24].
Despite the high-resolution images obtained by MRI, a
natural shift occurs in both the position and shape of
the breast tumor as a patient moves from the prone position, in which the images were obtained, to the supine
position intraoperatively. The lateral displacement of the
breast observed intraoperatively may also alter anatomic
relationships used to guide resection of large areas of
disease despite the use of localization devices. With 3D
printing, tumor localization can be optimized as finite
information can be provided regarding tumor morphology, shape, and location. Barth et al. (2017) accurately
localized tumors using a 3D-printed bra-like device that
matches the breast surface when the patient is in the supine position [23]. The 3D printed bra-like device was
fabricated with features that allowed the surgeons to
mark the edges of the tumor on the skin surface and inject blue dye into the breast 1 cm from the tumor edges.
Using this device, they were able to accurately localize
18 out of 19 cancers and achieved negative margins in
all cases.
In most cases, with MRI typically obtained in the
prone position, finite element simulations can address
this problem by estimating the displacement and deformation of the breast tissue as the patient shifts from
prone to supine position [25, 26].. The resulting map is
then used to warp the original prone MRI dataset into a
simulated supine position (Fig. 2). Alternatively, a multicompartment finite element simulation can estimate the
displacement and deformation of skin, fibro-glandular
Fig. 1 a Sagittal 3D maximum intensity projection (MIP) image from a contrast enhanced MRI showing extent of abnormal non –mass
enhancement in the right upper breast (white ellipse) and surrounding vessels (arrow). b A 3D printed model derived from this breast MRI. c A
breast surgeon using the 3D printed model intraoperatively to visualize the location of the tumor as well as its relationship to adjacent vessels. d
Side by side comparison of the excised specimen and the 3D model
Galstyan et al. 3D Printing in Medicine
Page 3 of 10
(2021) 7:6
Fig. 2 a Axial contrast-enhanced MRI obtained in the prone position showing two adjacent masses in the right breast (arrows). b A photograph
from the same patient positioned supine used to create an overlying map which is then used to to warp the prone 3D virtual model (c)
obtained from the original prone MRI dataset into a simulated 3D model in the supine position (d). The expected displacement and deformation
of the two masses (arrows) from the prone (c) to the simulated supine position (d) is also shown. e, f 3D printed model fabricated from the
estimated supine position
and adipose tissue as well as the changes in the location
and shape of tumor from a prone to a supine position
(Fig. 3). Using multi-material and multi-color 3D
printers, 3D models of the estimated deformed configuration can be fabricated. These models created
with varying colors and material properties can highlight all the tissue compartments, including skin,
fibroglandular tissue, fibro-glandular tissue, and the
breast tumor (Fig. 4).
Breast reconstruction surgery
When BCS is not technically feasible or desired, mastectomy is recommended and is utilized in an estimated
28–60% of women with breast cancer; of those, approximately 30% subsequently undergo breast reconstruction
[27]. Women who undergo breast reconstruction after
mastectomy experience better psychosocial adjustment
and quality of life than women who receive mastectomy
without reconstruction [28]. Multiple methods of breast
Fig. 3 a Axial contrast-enhanced MRI of the left breast in prone position showing a central mass (arrow). b Axial cross-section of multicompartment reconstruction in prone position. The 3D reconstruction includes skin (purple), adipose tissue (green), fibroglandular tissue (blue),
and mass (yellow). c Simulated multi-compartment reconstruction in the supine or surgical position. The supine state was achieved by applying
gravity to the model (in vivo gravity loading). The entire model, including each compartment, experience displacement and deformations
proportional to their inherent mechanical properties
Galstyan et al. 3D Printing in Medicine
(2021) 7:6
Page 4 of 10
Fig. 4 3D Printed, Patient-Specific Model of Simulated Supine Position. The 3D patient specific reconstruction of the left breast in the prone
position (a). The simulated supine position of the 3D patient-specific reconstruction (b). A parasagittal cross-section of the supine model featuring
fibro-glandular tissue (yellow) and two masses (blue) (c). The 3D printed, multi-material model of the simulated supine position, featuring the skin
(translucent yellow), the fibro-glandular tissue (cyan), and the two masses (magenta) (d). Half of the 3D printed model (e), split along the
parasagittal plane used in (c)
reconstructive surgery exist. While implant-based reconstruction is the most common form accounting for approximately 80% of breast reconstructive operations,
autologous flap reconstructions have several advantages,
including creation of a more natural-appearing breast
and improved quality of life [29]. Women who underwent flap procedures report significantly greater satisfaction with their breasts, sexual well-being, and
psychosocial adjustment than women who underwent
implant reconstruction [30].
Autologous breast reconstruction with deep inferior
epigastric artery perforator (DIEP) flap has become an
integral component of the holistic treatment of breast
cancer patients. During this reconstruction, subcutaneous fat and skin from the lower abdomen are transferred
as a vascularized free flap to reconstruct the breast. Yet,
similar to other vascular anastomoses, autologous breast
reconstructions are susceptible to microvascular anastomotic failure that threatens free flap survivability. Flap
survival relies on the identification and safe harvest of
suitable perforator vessels [31]. These vessels usually
take a tortuous course through the rectus abdominis
muscle and intramuscular dissection is often timeconsuming and laden with potential unintended injury
to critical vessels. Although imaging modalities such as
preoperative computed tomography angiography (CTA),
magnetic resonance angiography (MRA) and doppler
ultrasonography have been instrumental in identifying
suitable perforators, they are displayed on a 2D surface
and do not adequately address the greater challenge to
harvesting abdominal flaps, which is the inability to
clearly conceptualize the subfascial intramuscular course
of the DIEP vascular tree [32–34]. Selection of dominant
vessels for microvascular anastomosis based on 2D images is challenging. Images displayed on 2D monitors
provide inadequate information regarding vessel trajectory, allow for subpar manipulation of the original
image, and have restricted or fixed planes of rotation
that hinder the ability to view relationships of interest,
which is particularly important when estimating the
amount of breast tissue available for reconstruction [24].
3D printed models have been shown to facilitate the
intramuscular dissection of perforator vessels by depicting the course and trajectory of the subfascial vascular
tree and allowing the surgeon to hold and view the
model from various vantage points (Figs. 5 and 6) [24,
35]. The tactile feedback rendered by the models has
also been shown to facilitate superior spatial understanding [36].
Furthermore, current methods of selecting the desired
volume and shape of breast implants or soft tissue flaps
are inaccurate as they are subjective and dependent on
the individual surgeon’s experience. Therefore, either excessive or inadequate amounts of tissue are often excised. During the preoperative period, 2D images and
physical examination are used for visual estimation of
the anticipated soft tissue flap or implant volume. Intraoperatively, surgeons then match the volume of the
Galstyan et al. 3D Printing in Medicine
(2021) 7:6
Page 5 of 10
Fig. 5 a Axial Maximum intensity Projection (MIP) image from a CTA demonstrating the deep inferior epigastric perforating vessels (arrow). b
Coronal and c axial projections of a 3D rendering obtained from the CTA images showing the subfascial intramuscular course of the vascular tree
Fig. 6 a Coronal, b axial, and c Sagittal images from a preoperative CTA are used to create a 3D model depicting the deep inferior epigastric
vascular tree. A segmentation software (MIMICS; Materialise, Belgium) is used isolate vessels of interest and the abdominal muscle inorder to
highlight the intramuscular course of these vessels (d, e). The virtual model is subsequently printed using the Stratasys Connex J735 3D printer
(Eden Prairie, Minn) and is shown in the coronal (f) and (g) sagittal projection. This model can be used intraoperatively to guide dissection
of vessels
Galstyan et al. 3D Printing in Medicine
(2021) 7:6
breast with the volume of the flap that is to be used.
The flap is harvested and weighed after it is detached
from the donor site and prior to anastomosis to the
chest wall vessels. The weight of the removed breast and
flap are compared and the flap is excised serially until
optimal symmetry is achieved with the contralateral
breast. If prolonged, these steps can increase the chances
of microvascular anastomosis failure and fat necrosis.
Since it is difficult to accurately estimate flap volume before excision, an excessive amount may be excised with
the remaining tissue trimmed and discarded. This is particularly problematic for lean patients, for whom excessive tissue excision may increase risk of donor site repair
and hypertrophic scarring [37]. Current methods of
matching flap volume to desired breast size involve trialand-error estimation and intraoperative revision of flap
design. This prolonged intraoperative tissue plane alteration can lead to fat necrosis and secondary procedures
may be needed to improve breast asymmetry. 3D models
can be used for accurate analysis of breast volume,
shape, and contour preoperatively, leading to symmetric
surgical outcomes [38] (Fig. 7). Another important benefit of optimizing preoperative planning with 3D printed
models is the potential to minimize the rate of fat necrosis which currently remains as high as 35% [39]. Improved understanding of the course of perforators and
perfusion characteristics may be useful in reducing the
risk of fat necrosis, unintended vessel injury, and the
need for secondary procedures [36, 40]. Patient-specific
3D printed breast molds can also be used intraoperatively to facilitate the surgeon in shaping the contour
Page 6 of 10
and positioning of the autologous tissue by placing the
free flap inside the mold in a manner that adapts to the
shape of the template [41]. This allows matching the dimensions of the desired breast volume and shape, optimizing breast reconstruction outcomes [24].
Physician-patient and interdisciplinary communication
Providers often use radiologic images and/or standardized pictures to facilitate patient understanding of the
nature and extent of disease. Yet, significant limitations
exist with these traditional approaches. First, and most
importantly, these images are 2D. In order to fully appreciate the breadth of information contained within an
image, a patient must have a general understanding of
how these images are produced and developed, and what
limitations exist within each imaging modality. In
addition, patients need a general appreciation for the
anatomical structures represented within each image.
Given the level of complexity, patients may have a difficult time understanding the nature and extent of their
disease. 3D printed models serve as great communication tools for patients who are trying to better understand their disease and treatment options and have been
shown to improve comprehension in informed consent
[42, 43]. With customized 3D models, patients can better appreciate the tumor burden relative to their breast
size, and make an informed decision regarding BCS vs
mastectomy (Fig. 8).
In breast surgery, 3D printed models facilitate communication between the patient, breast surgeon and plastic
surgeon when considering BCS with oncoplastic
Fig. 7 a Axial contrast-enhanced breast MRI and b 3D volume rendering obtained from this MRI used to analyze the volume of the right (blue)
and left (orange) breasts, prior to planned left breast mastectomy with subsequent abdominal flap reconstruction. The volume of abdominal flap
tissue that needs to be harvested to match the volume of the contralateral right breast was calculated and marked on the preoperative CTA as
shown with representative sagittal (c) and axial (d) images. A virtual 3D model (e) was then generated which was used to mark the skin
intraoperatively so that an appropriate volume of abdominal flap tissue can be harvested
Galstyan et al. 3D Printing in Medicine
Page 7 of 10
(2021) 7:6
Fig. 8 a Axial contrast-enhanced MRI showing a left breast mass with direct invasion of the toverlying nipple areolar complex (arrow). b A
patient-specific 3D printed model generated from the MRI was used for patient education and obtaining of informed consent. 3D printed models
allow patients to easily understand the extent of disease and rationale for a specific surgical approach
reconstruction. The patient specific 3D printed models
can be used in discussion between patient-surgeon,
surgeon-radiologist, and surgeon-pathologist possibly
impacting consent, preoperative planning, and assessment of pathologic concordance [24]. By improving tools
used to educate patients on their disease, patients can
make more informed decisions that will ostensibly promote better treatment decisions which in turn improve
patient satisfaction rates, help reduce the need for secondary surgeries, and improve quality of life measures.
Education and simulation
The application of 3D printing is becoming increasingly
adopted in training and simulation of complex surgical
and image guided procedures. Traditionally, surgical
training has involved direct work on cadavers or the “see
one, do one, teach one” approach. Although cadavers are
anatomically accurate, they are too-expensive, do not retain live-tissue characteristics, lack the appropriate pathology, and are limited in supply [1, 44]. Training on 3D
printed models can be done virtually anywhere, avoiding
the cost and complexity of operating in the controlled
environments required for animals and human cadavers.
3D printed models are particularly of great benefit for
novice practitioners in training by supplementing early
operating experiences with a low-risk environment in
which the trainees can learn and perfect their skills before they are allowed to work on patients [45, 46].
Similarly, 3D printed breast phantoms aid in the
teaching and training of ultrasound-guided core needle
biopsy techniques [47]. Although chicken breast has
been traditionally used for training of ultrasound guided
needle biopsy techniques, it is non-reusable, environmentally unfriendly, and unsanitary risking contamination of biopsy instruments which leads to increased
waste and cost. Phantoms made of gelatin provide lowcost alternative, however tend to be too fragile with limited shelf-life and reusability. 3D printed teaching
models not only serve as a more cost-effective alternative, but the versatility and customizability of 3D printing can also be used to generate an expansive library of
anatomical variation in breast sizes, densities and pathologies (Fig. 9).
Quality control
Physical phantoms are commonly used as surrogates
of breast tissue to evaluate performance of breast imaging systems. However, most traditional phantoms
do not reproduce the anatomic heterogeneity of real
breast tissue. 3D printing creates the opportunity to
fabricate more complex and anatomically accurate
breast phantoms that can be used for quality assurance testing as well as development and optimization
of breast imaging systems. Since 3D printed phantoms
are reproducible, customizable, and cost-efficient, a
collection of representative patient models can be fabricated to evaluate the effect of anatomic variability
on system performance [48].
Currently, the majority of phantoms are designed for
use with a single imaging modality, thus multiple phantoms are required for different imaging systems. 3D
printing overcomes this limitation by enabling the construction of multi-purpose customizable breast phantoms made of tissue-equivalent materials that are
compatible with multiple imaging modalities [49]. These
phantoms can also be embedded with various inserts for
simulating different breast pathologies such as masses
and micro-calcification [50]. Ikejimba et al. (2017) generated breast models using a 3D printer that used relatively inexpensive materials with attenuation properties
Galstyan et al. 3D Printing in Medicine
Page 8 of 10
(2021) 7:6
Fig. 9 Patient-specific molds were generated by subtracting a patient’s 3D breast model from an enclosing volume (a). Internal structures, such
as fibroglandular tissue and masses, were held in place with custom fixtures designed onto the mold (a). The mold, internal structures and
fixtures were 3D printed using polylactic acid (PLA), a common and inexpensive 3D printing material (a). Silicone was poured into the 3D printed
mold (b). Upon setting, fixtures holding internal structures were removed prior to releasing the mold. The cast was removed from the mold by
gently separating the edges and tapping on the bottom of the mold (b)
similar to that of real-life breast tissue and lesions of
varying sizes and physical characteristics. The resulting
3D printed phantoms and their respective mammographic and tomosynthesis images demonstrated breast
backgrounds comparable to that of normal fibroglandular tissue, while still demonstrating a wide range of pathologies [51].
Future directions
Personalized radiation therapy
3D printing is promising to aid in delivery of personalized radiation therapy. A bolus is an artificial object
placed over the treatment area to modify radiation dose
and shields are used to protect adjacent structures not
intended to be exposed to radiation. 3D printing can be
used to design customized patient specific boluses and
shields to allow homogeneous distribution of radiation
dose to the area of interest while sparing adjacent normal tissue [52]. Another application of 3D printing is in
brachytherapy where a radiation source is implanted
next to the area requiring treatment. The traditional
standardized implants which are currently used do not
conform to patients’ specific anatomy and precise positioning is often challenging. These implants are also
prone to shifting during movement resulting in suboptimal dose to the target and unwanted exposure to adjacent organs. 3D printed customized brachytherapy
templates provide a much better fit thereby increasing
patient comfort and reducing shifts due to movement
[53]. Customized implants with curved internal channels
can also be used to reach targets that may not be accessible with existing standardized implants [53]. In highdose-rate brachytherapy, the number and positions of
the catheters are traditionally chosen manually using
radiation planning CT or ultrasound. 3D printing allows
a simple, fast, and efficient method for real time brachytherapy treatment which utilizes a reduced number of
catheters than the traditional approach [54, 55].
Bioprinting
Bioprinting is an extension of traditional 3D printing
processes, where biomaterials such as cells and growth
factors are used to create tissue-like structures that
mimic natural tissues such as skin and blood vessels.
This novel technology is promising to address challenges
encountered with current breast reconstruction techniques [56]. For instance, 3D bioprinting can be used to
generate a biodegradable scaffold that can be combined
with autologous adipose tissue in lipofilling. Lipofilling is
a reconstructive and aesthetic technique whereby autologous fat is used for filling defects and remodeling body
contours [57]. In breast cancer surgery, lipofilling can be
used to correct defects following wide local excision, improve symmetry after lumpectomy, replace volume of
implants in unsatisfactory breast reconstruction outcomes, and even achieve whole breast reconstruction
following mastectomy with serial fat grafting [58].
Current techniques have several drawbacks including
high resorption rate of injected fat and fat necrosis due
to lack of vascularization. Bioprinting allows fabrication
of patient-specific bio-absorbable scaffolds that can be
seeded with various stem cells and growth factors,
closely resembling the extracellular matrix that can support the generation of blood vessels [59–61]. These scaffolds which subsequently get resorbed by the body,
safely contain the injected fatty tissue and minimize the
significant volume loss of breast fat usually observed in
lipofilling.
Galstyan et al. 3D Printing in Medicine
Another important promising application of bioprinting is the recreation of the nipple-areola complex (NAC)
during breast reconstruction [62]. NAC is highly correlated with patient satisfaction and body image perception after breast reconstruction, however current
techniques such as local flaps and pigmented skin grafts
have unpredictable long-term outcomes [63]. Using
adipose-derived stem cells, functional, durable, and
patient-specific tissue constructs can be generated that
closely mimic physiologic tissue, have multipotent differentiation capacity, and react to normal tissue-specific development cues. Bioprinting is promising a novel
approach to generate replacement nipple tissue, though
much work remains to be done in this area. In addition
to tissue replacements for breast reconstruction, bioprinting can also be used to engineer breast tissue
models that serve as valuable tools in cancer research
and drug screening applications [64, 65].
Conclusion
3D printing is poised to revolutionize breast cancer surgery by allowing patient-specific pre-surgical planning
and customized intraoperative surgical guides for breast
conservation and reconstruction. The enhanced understanding of anatomic relationships rendered by 3D
models has allowed better esthetic surgical outcomes
while simultaneously achieving negative surgical margins. In addition, 3D models serve as great teaching tools
for patients and trainees and enhance interdisciplinary
communication between various health care providers.
3D printed phantoms are proving to be superior to traditional phantoms that are used for quality assurance of
breast imaging systems. Bioprinting and personalized radiation therapy are emerging fields which are promising
to address challenges encountered with current breast
cancer management approaches.
Acknowledgements
Not applicable.
Authors’ contributions
AG and TK wrote the manuscript. MB, FL, RS, JI and JS participated in
creating 3D printed models. RM performed surgical procedures. All authors
read and approved the final manuscript.
Funding
Not applicable.
Availability of data and materials
Not applicable.
Ethics approval and consent to participate
Not applicable.
Consent for publication
Consent for publication of intraoperative images has been obtained.
Competing interests
Not applicable.
Page 9 of 10
(2021) 7:6
Author details
1
University of California, 1600 Divisadero St, C250, Box 1667, San Francisco,
CA 94115, USA. 2Department of Radiology, Center for Advanced 3D
Technologies, 1600 Divisadero St, C250, Box 1667, San Francisco, CA 94115,
USA. 3University of Florida, 3100 Technology Pkwy, Orlando, FL 32826, USA.
4
Department of Surgery, University of California, 1600 Divisadero St, C250,
Box 1667, San Francisco, CA 94115, USA.
Received: 30 September 2020 Accepted: 31 January 2021
References
1. Ventola CL. Medical Applications for 3D Printing: Current and Projected
Uses. P T. 2014;39(10):704–11.
2. Ballard DH, et al. Clinical Applications of 3D Printing: Primer for Radiologists.
Acad Radiol. 2018;25(1):52–65.
3. Porras D, et al. Transcatheter Mustard Revision Using Endovascular Graft
Prostheses. Ann Thorac Surg. 2017;103(6):e509–12.
4. Sheikh A, Forster BB. "Holding It in Your Hand": Musculoskeletal Applications
of 3D Printing. Can Assoc Radiol J. 2020;71(2):129–30.
5. Silberstein JL, et al. Physical models of renal malignancies using standard
cross-sectional imaging and 3-dimensional printers: a pilot study. Urology.
2014;84(2):268–72.
6. Bagaria V, et al. Use of rapid prototyping and three-dimensional
reconstruction modeling in the management of complex fractures. Eur J
Radiol. 2011;80(3):814–20.
7. Anchieta MV, et al. Skull reconstruction after resection of bone tumors in a
single surgical time by the association of the techniques of rapid
prototyping and surgical navigation. Int J Comput Assist Radiol Surg. 2016;
11(10):1919–25.
8. Ajao MO, et al. Case Report: Three-Dimensional Printed Model for Deep
Infiltrating Endometriosis. J Minim Invasive Gynecol. 2017;24(7):1239–42.
9. Zein NN, et al. Three-dimensional print of a liver for preoperative planning
in living donor liver transplantation. Liver Transpl. 2013;19(12):1304–10.
10. Bray F, et al. Global cancer statistics 2018: GLOBOCAN estimates of
incidence and mortality worldwide for 36 cancers in 185 countries. CA
Cancer J Clin. 2018;68(6):394–424.
11. Kalli S, et al. American Joint Committee on Cancer's Staging System for
Breast Cancer, Eighth Edition: What the Radiologist Needs to Know.
Radiographics. 2018;38(7):1921–33.
12. Battersby C. Psychological implications of mastectomy. Aust N Z J Surg.
1981;51(3):300–3.
13. Fisher B, et al. Eight-year results of a randomized clinical trial comparing
total mastectomy and lumpectomy with or without irradiation in the
treatment of breast cancer. N Engl J Med. 1989;320(13):822–8.
14. Sarrazin D, et al. Ten-year results of a randomized trial comparing a
conservative treatment to mastectomy in early breast cancer. Radiother
Oncol. 1989;14(3):177–84.
15. Veronesi U, et al. Twenty-year follow-up of a randomized study comparing
breast-conserving surgery with radical mastectomy for early breast cancer.
N Engl J Med. 2002;347(16):1227–32.
16. McCahill LE, et al. Variability in reexcision following breast conservation
surgery. JAMA. 2012;307(5):467–75.
17. Mathapati SN, et al. Oncoplastic Breast Reconstruction in Breast
Conservation Surgery: Improving the Oncological and Aesthetic Outcomes.
Indian J Surg Oncol. 2019;10(2):303–8.
18. Hayes MK. Update on Preoperative Breast Localization. Radiol Clin North
Am. 2017;55(3):591–603.
19. Schnabel F, et al. A randomized prospective study of lumpectomy margin
assessment with use of MarginProbe in patients with nonpalpable breast
malignancies. Ann Surg Oncol. 2014;21(5):1589–95.
20. Meier-Meitinger M, et al. Accuracy of radiological tumour size assessment
and the risk for re-excision in a cohort of primary breast cancer patients. Eur
J Surg Oncol. 2012;38(1):44–51.
21. Abe SE, et al. Margin re-excision and local recurrence in invasive breast
cancer: A cost analysis using a decision tree model. J Surg Oncol. 2015;
112(4):443–8.
22. Heil J, et al. Do reexcisions impair aesthetic outcome in breast conservation
surgery? Exploratory analysis of a prospective cohort study. Ann Surg Oncol.
2012;19(2):541–7.
Galstyan et al. 3D Printing in Medicine
Page 10 of 10
(2021) 7:6
23. Barth RJ Jr, et al. A Patient-Specific 3D-Printed Form Accurately Transfers
Supine MRI-Derived Tumor Localization Information to Guide BreastConserving Surgery. Ann Surg Oncol. 2017;24(10):2950–6.
24. Santiago L, et al. The role of three-dimensional printing in the surgical
management of breast cancer. J Surg Oncol. 2019;120(6):897–902.
25. Rajagopal V, Nielsen PMF, Nash MP. Modeling breast biomechanics for
multi-modal image analysis--successes and challenges. Wiley Interdiscip Rev
Syst Biol Med. 2010;2(3):293–304.
26. Babarenda Gamage TP, et al. An automated computational biomechanics
workflow for improving breast cancer diagnosis and treatment. Interface
Focus. 2019;9(4):20190034.
27. McGuire KP, et al. Are mastectomies on the rise? A 13-year trend analysis of
the selection of mastectomy versus breast conservation therapy in 5865
patients. Ann Surg Oncol. 2009;16(10):2682–90.
28. Ng SK, et al. Breast Reconstruction Post Mastectomy: Patient Satisfaction
and Decision Making. Ann Plast Surg. 2016;76(6):640–4.
29. Frey JD, et al. Implant-Based Breast Reconstruction: Hot Topics,
Controversies, and New Directions. Plast Reconstr Surg. 2019;143(2):
404e–16e.
30. Rosson GD, et al. Quality of life before reconstructive breast surgery: A
preoperative comparison of patients with immediate, delayed, and major
revision reconstruction. Microsurgery. 2013;33(4):253–8.
31. Nahabedian MY, et al. Breast Reconstruction with the free TRAM or DIEP
flap: patient selection, choice of flap, and outcome. Plast Reconstr Surg.
2002;110(2):466–75 discussion 476–7.
32. Schaverien MV, et al. Contrast-enhanced magnetic resonance angiography
for preoperative imaging in DIEP flap breast reconstruction. Plast Reconstr
Surg. 2011;128(1):56–62.
33. Rozen WM, et al. Does the preoperative imaging of perforators with CT
angiography improve operative outcomes in breast reconstruction?
Microsurgery. 2008;28(7):516–23.
34. Giunta RE, Geisweid A, Feller AM. The value of preoperative Doppler
sonography for planning free perforator flaps. Plast Reconstr Surg. 2000;
105(7):2381–6.
35. Jablonka EM, et al. 3-DIEPrinting: 3D-printed Models to Assist the
Intramuscular Dissection in Abdominally Based Microsurgical Breast
Reconstruction. Plast Reconstr Surg Glob Open. 2019;7(4):e2222.
36. Chae MP, et al. Emerging Applications of Bedside 3D Printing in Plastic
Surgery. Front Surg. 2015;2:25.
37. Minn KW, Hong KY, Lee SW. Preoperative TRAM free flap volume estimation
for breast reconstruction in lean patients. Ann Plast Surg. 2010;64(4):397–
401.
38. Chae MP, et al. 3D volumetric analysis for planning breast reconstructive
surgery. Breast Cancer Res Treat. 2014;146(2):457–60.
39. Peeters WJ, et al. Fat necrosis in deep inferior epigastric perforator flaps: an
ultrasound-based review of 202 cases. Plast Reconstr Surg. 2009;124(6):
1754–8.
40. Chae MP, et al. Enhanced Preoperative Deep Inferior Epigastric Artery
Perforator Flap Planning with a 3D-Printed Perforasome Template:
Technique and Case Report. Plast Reconstr Surg Glob Open. 2018;6(1):e1644.
41. Hummelink S, et al. Applications and limitations of using patient-specific 3D
printed molds in autologous breast reconstruction. Eur J Plast Surg. 2018;
41(5):571–6.
42. Yoon SH, et al. Personalized 3D-Printed Model for Informed Consent for
Stage I Lung Cancer: A Randomized Pilot Trial. Semin Thorac Cardiovasc
Surg. 2019;31(2):316–8.
43. Kim PS, et al. Obtaining Informed Consent Using Patient Specific 3D
Printing Cerebral Aneurysm Model. J Korean Neurosurg Soc. 2019;62(4):398–
404.
44. Banks J. Adding value in additive manufacturing: researchers in the United
Kingdom and Europe look to 3D printing for customization. IEEE Pulse.
2013;4(6):22–6.
45. Watson RA. A low-cost surgical application of additive fabrication. J Surg
Educ. 2014;71(1):14–7.
46. Saber R, Cheung CL. Application of 3D Printing in Medical Simulation and
Education. Bioeng Surg. 2016;Chapter 9:151–66.
47. Ali A, et al. Imaging properties of 3D printed breast phantoms for lesion
localization and Core needle biopsy training. 3D Print Med. 2020;6(1):4.
48. Badal A, Clark M, Ghammraoui B. Reproducing two-dimensional
mammograms with three-dimensional printed phantoms. J Med Imaging
(Bellingham). 2018;5(3):033501.
49. He Y, et al. 3D-printed breast phantom for multi-purpose and multimodality imaging. Quant Imaging Med Surg. 2019;9(1):63–74.
50. Kiarashi N, et al. Development of realistic physical breast phantoms
matched to virtual breast phantoms based on human subject data. Med
Phys. 2015;42(7):4116–26.
51. Ikejimba LC, et al. A novel physical anthropomorphic breast phantom for
2D and 3D x-ray imaging. Med Phys. 2017;44(2):407–16.
52. Su S, Moran K, Robar JL. Design and production of 3D printed bolus for
electron radiation therapy. J Appl Clin Med Phys. 2014;15(4):4831.
53. Garg A, Patil S, Siauw T, Cunah J. An algorithm for computing customized
3D printed implants with curvature constrained channels for enhancing
intracavitary brachytherapy radiation delivery. Madison: IEEE International
Conference on Automation Science and Engineering (CASE); 2013. p. 466–
73. 2013
54. Poulin EGL, Fenster A, Pouliot J, Beaulieu L. A Novel Approach for Real-Time,
Personalized Breast HDR Brachytherapy. Treatment Using 3D Printing
Technology. Brachytherapy, 2014;13(18):17–18.
55. Ricotti R, et al. 3D-printed applicators for high dose rate brachytherapy:
Dosimetric assessment at different infill percentage. Phys Med. 2016;32(12):
1698–706.
56. Pati F, et al. Printing three-dimensional tissue analogues with decellularized
extracellular matrix bioink. Nat Commun. 2014;5:3935.
57. Kasem A, et al. Breast lipofilling: a review of current practice. Arch Plast
Surg. 2015;42(2):126–30.
58. Hamza A, Lohsiriwat V, Rietjens M. Lipofilling in breast cancer surgery. Gland
Surg. 2013;2(1):7–14.
59. Tytgat L, et al. Extrusion-based 3D printing of photo-crosslinkable gelatin
and kappa-carrageenan hydrogel blends for adipose tissue regeneration. Int
J Biol Macromol. 2019;140:929–38.
60. Wooyeol Baek MSK, Park DB, Joo OY. Three-Dimensionally Printed Breast
Reconstruction Devices Facilitate Nanostructure Surface-Guided Healthy
Lipogenesis. ACS Biomater Sci Eng. 2019;5(10):4962–9.
61. Chhaya MP, et al. Transformation of Breast Reconstruction via Additive
Biomanufacturing. Sci Rep. 2016;6:28030.
62. Khoo D, et al. Nipple Reconstruction: A Regenerative Medicine Approach
Using 3D-Printed Tissue Scaffolds. Tissue Eng Part B Rev. 2019;25(2):126–34.
63. Lee HJ, Ock JJ. How to Improve Projection in Nipple Reconstruction: A
Modified Method Using Acellular Dermal Matrix Disk and Fragments. Plast
Reconstr Surg. 2019;143(4):698e–706e.
64. Cleversey C, Robinson M, Willerth SM. 3D Printing Breast Tissue Models: A
Review of Past Work and Directions for Future Work. Micromachines (Basel).
2019;10(8):501.
65. Knowlton S, et al. Bioprinting for cancer research. Trends Biotechnol. 2015;
33(9):504–13.
Publisher’s Note
Springer Nature remains neutral with regard to jurisdictional claims in
published maps and institutional affiliations.